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Problem-based learning and its influence on college preparation knowledge, motivation, & self-efficacy in high school students

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Problem-based learning and its influence on college preparation knowledge, motivation, & self-efficacy in high school students

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PROBLEM-BASED LEARNING AND ITS INFLUENCE ON COLLEGE
PREPARATION KNOWLEDGE, MOTIVATION, & SELF-EFFICACY IN HIGH
SCHOOL STUDENTS.

by

Marcelo F. Vazquez

A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2008

Copyright 2008 Marcelo F. Vazquez

ii

Dedication
This dissertation is dedicated to my mother and father, Cora and Fernando
Vazquez, who sacrificed much in coming to the United States. Mom, it all stared with
you when I saw you walk across the stage to receive your bachelors degree. You
planted the seed, thank you. Dad, we finally reached the end of the academic road.
From the masters to the doctorate, this degree is as much yours as it is mine. I am in
forever debt to the both of you, thank you so much and I love you both.
To Mauricio, my brother, thank you for being a motivation and role model. To
Melinda Vazquez, thank you for your time with Mauricio in listening to my ideas
throughout the dissertation process.
To my beautiful wife, thank you for your understanding and sacrifice as I spent
many a day and night working on this dissertation. To our beautiful six-week old
daughter, Soliada Jindarat-Vazquez, I hope to be the kind of role model for you that
your grandparents have been for me. This graduate program is finished, now comes the
real “graduate program”, being a father.

iii

Acknowledgements
I would like to acknowledge my committee chairperson, Dr. Robert Keim, thank
you for introducing me to problem-based learning. You helped make my dissertation
experience at the University of Southern California (USC) an incredible and
unforgettable one, thank you Dr. Keim. Dr. Mari Luna De La Rosa, thank you for the
unique and critical perspective you added to my college preparation research. Dr.
Kristan Venegas, thank you for your guidance and for strengthening my introduction
into the world of qualitative research. Dr. William Tierney, it was an honor having you
on my committee for the limited time you were available. I deeply appreciate the time
and patience you gave. I consider all of you my new role models in college preparation
research.
To Jacqueline Elliot, Fidel Ramirez, Max Valadez, Juana Maria Valdivia de
Guerrero, and Jason Roberts, thank you for helping make the logistics of this study as
smooth as possible. To Joel Trudgeon and Florentino Manzano of Los Angeles Valley
College, your assistance was invaluable. Tino, I know Ludim was with me every step
of the way.
To all my professors at the University of Southern California, thank you for your
wisdom, advice, stories and guidance; it was an honor to be in your classes. To the staff
of the Rossier School of Education, especially my trusted Program Advisors, Guadalupe
Garcia Montano and Shila Ruiz, you are the unsung perks of the program, thank you for
taking care of our class.

iv

Dr. Anthony Ross, thank you for your time and advice during the last leg of my
doctoral program. Your support and mentorship was and continues to be invaluable,
thank you.
To my close friends, thank you for your understanding and exemplifying what a
friendship should be. Finally, to my entire family, thank you so much for your support.
This accomplishment would not have been possible without you.

v

Table of Contents

Dedication ii
Acknowledgements iii
List of Tables vii
List of Figures viii
Abstract ix
Chapter I: Introduction 1
Purpose of the Study 4
Significance of the Study 5
The Potential for Problem-Based Learning 6
Research Questions 9
Methodology Overview 9
Limitations 10

Chapter II: Review of the Literature 12
Access to and Quality of College Preparation Information 12
K-16 Student Demographics and Transitions 13
Equity and Excellence 16
College Preparation Outreach and Programming 17
Problem-Based Learning 22
Problem-Based Learning and Behavioral Theories 26
Problem-Based Learning and Cognitive Theories 29
Problem-Based Learning and Humanist Theories 41
Problem-Based Learning and Multiple Perspectives on Learning 44
Problem-Based Learning and Motivation 55
Problem-Based Learning and Self-Efficacy 56
Challenges in Problem-Based Learning 58
Discussion of Literature Review 60

Chapter III: Methodology 62
Research Questions 62
Participants 62
School District Setting for High School X 65
Instrumentation 68
Procedure/Data Collection 70
Data Analysis 75

vi

Chapter IV: Findings 76
Descriptive Statistics for the Subjects 77
Research Question #1: The GSE Data 78
Research Question #2: Journaling and Grounded Theory 83
Research Question #3: The MSLQ Data 91

Chapter V: Results 97
Discussion 105
Hossler’s Three-Stage Model of College Choice 106
Data Revisited, Limitations of the Study, and
Recommendations/Modifications to the Study 108
Implications for Practice 111

References 113

Appendices 132
Appendix A: First Guided Journal Questions for High School X 132
Appendix B: Second Guided Journal Questions for High School X 135
Appendix C: Third Guided Journal Questions for High School X 139
Appendix D: General Perceived Self-Efficacy Scale 142
Appendix E: Motivated Strategies for Learning Questionnaire/
Demographic Information 143

vii

List of Tables

Table 1: Educational Level Distribution of High School X Parents. 63

Table 2: Median Incomes of Area Surrounding High School X 67

Table 3: High School X Family/Subject Income Level 77

Table 4: Levene Test Data on GSE Scale Questions from First
Administration. 78

Table 5: ANOVA Test Data on GSE Scale Questions from First
Administration. 80

Table 6: ANOVA Test Data on GSE Scale Questions from Third
Administration. 81

Table 7: Sample of Guided Journal Response Analysis. 84

Table 8: College Preparation Terminology from First Journal Administration. 90

Table 9: College Preparation Terminology from Third Journal Administration. 90

Table 10: ANOVA Test Data on MSLQ Scale Question from First
Administration. 92

Table 11: ANOVA Test Data on MSLQ Scale Question from Third
Administration. 93

viii

List of Figures

Figure 1: Model of Vygotsky’s zone of proximal development. 33

Figure 2: Abraham H. Maslow’s Hierarchy of Needs. 43

Figure 3: Relationship Between College Preparation Clusters. 87

ix

ABSTRACT
Data indicates that the college-going rates for first-generation college going
students, typically from underrepresented populations, lag far behind the rates of non-
underrepresented populations. While various types of academic outreach programs
designed to increase the college-going rates have been funded by state and federal
resources, college going rates of first-generation college going students still lag behind.
Using 9
th
graders from a Los Angeles high school, this study investigated the effects of
problem-based learning (PBL) on the delivery of college preparation information.
Thirty three 9
th
grade students from a Los Angeles area high school participated
in the study. Students were placed in three different delivery modes of college
preparation information; problem-based learning, outreach service, and college center
access. Through the student responses on the General Perceived Self-Efficacy Scale,
Motivated Strategies for Learning Questionnaire (MSLQ), and guided-journal
assignments, data was analyzed on problem-based learning’s influence on self-efficacy,
motivation, and knowledge, as they relate to college preparation.
Quantitative and qualitative analysis found that generally, problem-based
learning did lead to increases in motivation and self-efficacy in college preparation as
compared to outreach and college center services. College preparation knowledge
results indicate equal effectiveness amongst all three deliveries of college preparation.
As university admissions standards and requirements become more stringent and
competitive, secondary students need to prepare earlier. PBL represents a tool that can
positively influence the early college preparation of first-generation college students.

1

Chapter I
Introduction
The purpose of this dissertation is to investigate if problem-based learning
(PBL) can be an effective tool for increasing high school student motivation, self-
efficacy, and knowledge towards college preparation. A special focus is placed on the
effect of PBL on motivation, self-efficacy, and knowledge towards college preparation
among 9
th
grade students in a high school in the Los Angeles area.
According to Choy (1999), 97% of U.S. students who completed high school
reported an interest in continuing their education after high school by enrolling in a
postsecondary institution. Of these 97%, 71% focused specifically on reaching the
bachelor’s degree. For underrepresented students in postsecondary institutions,
particularly Latina/o and African American students, these percentages do not
translate into enrollment and persistence rates (Gonzalez & Szecsy, 2002, Harvey,
2001, and Swail 2003). Despite increases in college enrollment nationwide, Latina/o
and African American students still trail their White non-Latino college-age
counterparts in college enrollment percentage; known as the college participation rate
(Harvey & Anderson, 2005). From 1990 to 2002, the high school completion rates for
Latina/o (61.5%) and African American (77.2%) students continued to trail White
non-Latino students (87.1%) (Harvey & Anderson, 2005). With the nation-wide
White non-Latino college student participation rate at 45.5%, this is higher than both
Latina/o (34%) and African American (39.9) college participation rates between 1990
and 2002 (Harvey & Anderson, 2005).

2

The data for California does not fare much better. In 2006, Latina/o (47.5%)
and African American (7.8%) students comprised over half of the K-12 California
student population, with White non-Latino students at 30.3% (California Department
of Education, 2007). A year earlier in 2005, 36.5% of Latina/o students graduated
from high school, with White non-Latino and African American high school graduates
at 39.6 % and 7.5% respectively (Postsecondary Education Commission, 2007).
Among these same high school graduates, 24.9% of Latina/o and 5.4% of African
American students completed the A-G high school class requirements. The
percentage of White non-Latino students completing the A-G requirements was 46.1%
(Postsecondary Education Commission, 2007).
The A-G requirements are classes a California high school student needs to
complete in order to be eligible applying to any of the 23 California State University
(CSU) and the nine University of California (UC) undergraduate programs. These
requirements are comprised of the following categories of classes: (A) four years of
English, (B) three years of Mathematics, (C) two years of History/Social Science, (D)
two years of a Laboratory Science, (E) two years of a Language other than English,
(F) one year of Visual and Performing Arts, and (G) one year of a College Preparatory
Elective.
According to the National Center for Public Policy and Higher Education
(NCPPHE) (2005), if these trends continue in this direction, the number of students
who complete a college education in the United States could decline during the next
10 to 15 years. Closing the gap between the education levels of White non-Latino

3

students and Latina/o and African American students can help reverse this trend
(NCPPHE, 2005). So what is being done to close this gap?
According to Ann Coles, Senior Vice-President of college access programs for
the Education Resource Institute, there are approximately 3,000 college preparation
programs in the U.S. targeting underrepresented students (Hequet, 2007). The federal
government spends more than one billion annually on college preparation programs
like Upward Bound (Hequet, 2007). In California, $127 million was spent during
2002 on 19 different college preparation outreach programs (MGT, 2002). The
California budget for these 19 programs increased four-fold in response to the effects
of recent policies that prevented university admissions practices from using race,
gender, and ethnicity in admissions decisions (MGT, 2002). In fact, approximately
94.9% of comprehensive California public high schools provided at least one college
preparation outreach program. The majority - 56.4% - of these public high schools
provided between one and four outreach programs to their students (MGT, 2002).
Most of the outreach programs were also focused on low-performing schools and
students, and first-generation college-going high school students; students who are
typically from underrepresented populations like Latina/o and African American
(Washington, 1996).
McDonough and Antonio (1996) state that in order to improve access and
equity in postsecondary education, we need to better understand how institutions
influence the transition from secondary schools to postsecondary institutions and an
understanding of the college decision making process of the student.

4

Understanding how students make decisions about the college preparation
process is the most critical because of two reasons (McDonough & Antonio, 1996).
First, research has demonstrated that where a high school student has been accepted
for college is dependent mostly upon the student since most are accepted by their first
choice campus (Karen, 1988, Manski & Wise, 1983). Second, the only way to make
true change at the student level is by understanding the college preparation and college
choice process and identifying at what point to implement specific interventions
(McDonough & Antonio, 1996).
Purpose of the study
The intent of this quantitative and qualitative study is to analyze the effect
problem-based learning (PBL) has on college preparation self-efficacy, motivation and
knowledge of 9
th
grade high school students. The General Perceived Self-Efficacy
Scale (Schwarzer & Jerusalem, 1995) was administered before and after the PBL
administration to measure the level of self-efficacy as it relates to college preparation.
The Motivated Strategies for Learning Questionnaire (MSLQ) was administered
before and after the PBL administration, measuring the levels of motivation for the 9
th

grade students as it relates to college preparation. Guided-journal responses to pre-
established questions were also collected before, during, and after the PBL
administration. The journal exercise allowed for in-depth comparisons of student self-
efficacy, motivation, and knowledge at different stages of the PBL process. The
purpose of using both quantitative and qualitative measures is to triangulate the data
and provide a rich description of the levels of influence PBL has on college
preparation, self-efficacy, motivation and knowledge among 9
th
grade students.

5

Significance of the study
High school college counselors have indicated that many of their Latina/o and
African American high school students often lack a basic understanding of their
postsecondary education opportunities and the college admissions process (Outcalt,
Tobolowsky, and McDonough, 2000). This lack of college choice knowledge can lead
high school students towards choosing the wrong postsecondary option. Students rely
heavily on the college preparation information available at their schools (Outcalt et al.,
2000), but often the information does not reach at-risk underrepresented populations
like Latina/os and African Americans (Carrasco, 1988; Merisotis, 1990).
According to Tierney (2005), the quantity of college preparation courses and
quality of academic rigor in the 9th grade is a good predictor of the kind of
postsecondary institution a high school student is likely to attend. The problem is for
underrepresented students in low-income areas who typically start to hear the “college
preparation message” in the junior and senior years of high school. This leads to an
already underserved population knowing even less about its postsecondary options and
more under-prepared to compete for coveted openings at colleges and universities.
The college preparation process is a “triangulated relationship composed of the
student, the admissions officer, and the guidance counselor” (Tierney, 2005, p. 130).
Admissions and outreach officers are more consumed than ever with enrollment
strategy, marketing and enrollment figures and goals (Newman, 2002; Penn, 1999;
Schurenberg; 1989). High school guidance counselors are consumed with non-
counseling tasks such as class scheduling, test administrations, and disciplinary issues
(Delaney, 1991; Kirchner & Setchfield, 2005; Thomas & Hutchinson, 1992). Within

6

these dynamics, the high school student, especially the ninth grade student, is left in a
situation where college preparation knowledge is scarce and assistance understanding
the knowledge is even scarcer.
Research has shown how problem-based learning can have a positive impact
on knowledge acquisition, on how a learner transfers that knowledge to action, on
problem solving skills, on attitudes and on opinions towards different curriculums, and
self-directed learning (Berkson, 1993; Colliver, 2000; Davies, 2000). Other studies
have also questioned the positive results reported because of unclear procedures on
how PBL was administered (Kelson and Distlehorst, 2000). There is also a lack of
research on the influence PBL may have on the beliefs students have about their
abilities; self-efficacy (Dunlap, 2005).
This study investigates PBL as a possible tool to empower students to be their
own best advocate on the path towards becoming a competitive college applicant. Can
PBL equip students to become active consumers of college preparation information?
Can PBL make a positive impact in the college preparation of first-generation college
going 9
th
grade students?
The Potential of Problem-Based Learning
As described by Vernon and Blake (1993), PBL is a method of teaching and
problem solving that emphasizes the use of case studies, small discussion teams,
independent study alongside team collaboration, deductive reasoning, and teacher
facilitation of group process, rather than teachers providing the information. Problem-
based learning centers on the belief that learning is most effective when the process of
learning is more important than directing the learning of a student (Yeo, 2005). The

7

knowledge a student acquires through learning needs to be tied to a specific purpose or
reason. This is the opposite of learning environments where the learning is more
centered on what the teacher delivers, evident in the more sermonic type lectures
given in conventional classrooms (Walker, Bridges and Chan, 1996). Problem-based
learning stands on the notion that most students will learn better if they are learning
information they need (Burch, 2000). This need comes when the learner encounters a
problem to be solved, a problem relevant to the learner.
Since 1969, PBL has changed the way some universities - Harvard, University
of Hawaii, McMaster University, and the University of Southern California - train
their professional students in the health sciences (Wilkerson and Gijselaers, 1996).
Most of the research evidence on PBL originates from research conducted in medical
schools and in gifted education (Hmelo-Silver, 2004).
This study will apply the strengths of PBL - developing flexible knowledge,
stronger problem-solving skills, and increased self-directed learning - to the
application of college preparation. Changes in self-efficacy, motivation and
knowledge of 9th grade high school students will be analyzed in terms of their
relationship to PBL exposure. These areas of inquiry between PBL and college
preparation will provide much needed insight into how high school students can
become their own best advocate in preparing for competitive college admissions.
In the state of California, the ratio of school/college counselors to high school
students is one school/college counselor for every 528 high school students (CDE,
2007). The American School Counselor Association recommends a ratio of one
counselor for every 250 (American School Counselor Association, n.d.). Even if the

8

recommended ratio was reached, an average of 32% of a high school counselor’s time
is spent directly on counseling high school students on their postsecondary
preparation; 25% for a public high school counselor (Hawkins and Clinedist, 2006).
Even though significant numbers of high school students identify college guidance
counselors as important in the college preparation process (Alva, 1991; McDonough,
1997), the quality of the college counseling can often be severely deficient of the most
current and accurate information on college preparation requirements (Carrasco, 1988;
Hutchinson & Bottorff, 1986).
A significant amount of the remaining time for a counselor is spent in handling
other issues not related to college preparation. These other issues include prevention
of high school dropouts, teenage drug abuse, suicide, pregnancy, sexuality and
personal issues; evidence of the public high school’s reduced attention to the college
advisement function of the high school counselor (McDonough, Korn, & Yamasaki,
1997).
From the postsecondary side, the number of college admissions counselors has
risen markedly, yet their function has been transformed. From being a resource to
help high school students transition to a postsecondary institution, college admissions
counselors represent now more of a marketer and recruiter for the enrollment
management bottom line (McDonough, Korn, & Yamasaki, 1997). University
outreach programs, like Project Advancement Via Individual Determination (AVID)
and the University of California’s Early Academic Outreach Program, target
underrepresented students yet often exclude the same underrepresented students who
do not meet certain criteria (Loza, 2003; McDonough, Korn, & Yamasaki, 1997).

9

These underrepresented students are often in the most need of the college preparation
services because they do not qualify for these same kind of outreach services (Loza,
2003; McDonough et.al., 1997).
With strained college counseling resources from the high school side and
limited access to important outreach programs from the postsecondary side, the high
school student is caught in the middle of a college preparation chasm. Can problem-
based learning empower high school students to become their own best advocate in
preparing for competitive college admissions? To further analyze the potential
benefits of problem-based learning and it’s application towards college preparation,
the following questions will be investigated.
Research Questions
1. Does a student’s self-efficacy towards college preparation increase
through participation in a college preparation program that utilizes a
pedagogical technique based on the principles of problem-based learning?
2. Does a student’s knowledge of college preparation increase as a result of
participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning?
3. Does a student’s motivation for preparing for college increase as result of
participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning?
Methodology Overview
This will be a quantitative and qualitative study conducted over a seven-week
period. The Motivated Strategies for learning Questionnaire (MSLQ) (Pintrich, Smith,

10

Garcia, & McKeachie, 1993) and the General Self-Efficacy (GES) Scale (Schwarzer
& Jerusalem, 1995) are the quantitative measures. The qualitative measures will be
captured through the administration of three guided-journal submissions. The
population is 9th grade students, primarily Latina/o students, in a public charter high
school in the Los Angeles county area. Administrators and staff at the public charter
high school will help in accessing students for the selection of experimental and
control groups. The experimental group will consist of 11 9th grade students in a PBL
learning environment. Two control groups will each contain 11 9th grade students,
but with no exposure to PBL. One of the control groups will deliver college
preparation through access to the high school college center, hence called the College
Center group. The other control group will deliver the college preparation information
via a series of university outreach presentations. This group will be called the
Outreach group. Like the PBL group, both control groups will be tested on the impact
they have on self-efficacy, motivation and knowledge towards college preparation.
Students will take the MSLQ and GSE Scale before and after the seven-week
exposure to the problem-based learning environment. Students will also submit
guided, non-graded journal submissions in the first workshop, the middle workshop,
and last workshop in each of the three groups. Changes in student self-efficacy,
motivation, and knowledge towards college preparation will be detected through data
gathered from the MSLQ, GSE Scale and guided-journal responses.
Limitations
The number of students in this study will be limited by the number,
availability, and demographic of students who want to participate in the study. Due to

11

the amount of time required to complete the PBL environment, attrition of student
participants in both the experimental and control groups may or may not become an
issue. Lack of financial resources will not allow for financial incentives to attract
students to participate in the study. Incentives such as free pizza, time credit towards
the mandatory school requirement for community service hours, and extra access to a
college preparation guidance counselor will serve as the incentives for student
participation.

12

Chapter II
Review of the Literature
In this literature review, I will examine three areas and their relation to
problem-based learning. First, a group of issues will be presented to make a case for
why PBL needs to be investigated as a tool for strengthening high school college
preparation. Second, PBL and the psychological theories that support it will be
visited. Third, research on motivation and self-efficacy and their impact on learning,
then bringing the literature review to a close with a visit to the challenges of PBL.
Access to and Quality of College Preparation Information
High school students, parents, and even high school educators, are often
confused as to how a high school student should prepare for college (Venezia & Kirst,
2005). High school students often have assumptions that can lead them to making
wrong college preparation choices (Venezia & Kirst, 2005). Some of these wrong
choices include thinking high school graduation requirements are sufficient for college
eligibility, community colleges not being a viable option for four-year institution
transition, the senior year in high school not being important, and grades and rigor of
classes only start to matter during the tenth grade year and on.
Research has shown that a student’s expectation of his/her acceptance in a
college is a major factor on the student’s enrollment in college (Cabrera & La Nasa,
2000; Hearn, 1987). In addition, high school guidance counselors play an important
role in supporting high school student’s decision process about which postsecondary
institution to attend (Center for Education Policy Analysis, 2002; Falsey & Heynes,
1984; Lee & Ekstrom, 1987; McDonough, 1997; Stanton-Salazar, 2000). High school

13

guidance counselors also provide their students with access to crucial college
preparation information related to financial aid, placement tests, and college
preparation skills that can significantly influence the college attendance expectation
and drive (Fallon, 1997).
Fueling the confusion are high school inequities that have been shown to lead
to a student’s success or failure in school. Examples of these inequities are the
percentage of English language learners at a school, the percentage of students who
are eligible for free or reduced meals, the numbers of certified teachers at a school,
and the level of racial and ethnic isolation present at a school (Yun & Moreno, 2006).
Although these examples are out of the control of high school counselors, these
socioeconomic, cultural, and structural issues play a role in school success.
K-16 Student Demographics and Transitions
In the state of California, these inequities are highly concentrated in schools
where high numbers of African American and Latina/o students attend (Yun &
Moreno, 2006). This is a problem when half of the enrolled K-12 California student
population in 2005-2006 was African American and Latina/o, 47.58% being Latina/o
(California Department of Education [CDE], 2007). In the Los Angeles Unified
School District (LAUSD), 73.2% of enrolled K-12 students were Latino and 11.4%
were African American (CDE, 2007). Add to these figures the current California ratio
of school/college counselors to high school students; one school/college counselor for
every 528 high school students (CDE, 2007). The American School Counselor
Association recommends a ratio of one counselor for every 250 (American School
Counselor Association, n.d.).

14

With the Latina/o and African American student populations comprising over
80% of the LAUSD K-12 student population, the need to strengthen college awareness
and college preparation for these two populations is not difficult to defend. According
to Gerald and Haycock (2006), fulfilling the college preparation needs for low-income
families and children of color is important because these are the populations most in
need of the information. In the end, the strength of the United States democracy and
economy depends on educating all children for a postsecondary education, which
leads to future employability (Gerald & Haycock, 2006). The need to strengthen
college awareness among Latina/o and African American students can be seen by
looking at the data of K-12 student ethnic population transitions to the CSU and UC.
The need can also be demonstrated by looking at research showing the benefits of
having an ethnically and culturally diverse undergraduate student population. One
benefit highlighted later in this chapter is how an undergraduate’s learning experience
can be strengthened by community involvement as a by-product of student exposure to
various cultures within the undergraduate population at a particular institution.
In terms of the data reflecting the numbers of Latina/o and African American
students in K-12 and then transitioning to public postsecondary institutions, the
numbers are striking. Half of the enrolled K-12 California student population in 2005-
2006 was African American and Latino, 47.58% being Latina/o and 7.84% being
African American (CDE, 2007). For White non-Latino, this group comprised 30.34%
of enrolled K-12 California students. The California State University (CSU) system’s
total undergraduate enrollment for Fall 2006 was 344,445 (CSU, 2007). The total
number of Latina/o undergraduates enrolled in the CSU during the same time period

15

was 81,304, or 23% of the total CSU undergraduate population (CSU, 2007). The
total number of African-American undergraduates enrolled in the CSU during Fall
2006 was 21,154, representing 6% of the total CSU undergraduate population (CSU,
2007). In the same Fall 2006, the number of White non-Latino enrolled
undergraduates was 125,264, representing 42.7 of the CSU undergraduate student
population. Data on Latina/o and African American undergraduates from the
University of California (UC) does not fair much better.
The UC system’s total undergraduate enrollment for Fall 2005 was 159,066
(University of California [UC], 2005). The total number of Latina/o undergraduates
enrolled in the UC during the same time period was 22,221, representing 14% of the
total UC undergraduate population (UC, 2005). The total number of African-
American undergraduates enrolled in the UC during Fall 2005 was 4,780, representing
3% of the total UC undergraduate population (UC, 2005). For Fall 2005, the number
of White non-Latino enrolled undergraduates was 55,499, representing 35% of the UC
undergraduate student population.
When comparing the percentage of Latina/o and African American K-12
students in California with the percentage of Latina/o and African American
undergraduates in the CSU and UC systems, the percentages for both groups are lower
for both systems. When comparing the percentage of White non-Latino K-12 students
in California with the percentage of White non-Latino undergraduates in the CSU and
UC, the percentages for this group are higher for both systems. What possible effect
does this have on the undergraduate learning environment in California’s public
postsecondary institutions?

16

Equity and Excellence
How do these figures translate to the quality of undergraduate education in the
CSU and UC systems? The benefits of ethnic diversity in universities and colleges
include enhanced learning, preparation for living in a diverse and global society,
willingness to interact with diverse societies after graduation, and strengthening
“social stability” in American culture (Crosby, Iyer, Clayton & Downing, 2003). Two
additional benefits of exposure to ethnic and cultural diversity are learning outcomes
and democracy outcomes (Gurin, Dey, Gurin, & Hurtado, 2003).
According to Gurin et.al. (2003), interaction with ethnic and cultural diversity
in the undergraduate experience leads to enhanced learning outcomes. These
outcomes are identified as enhanced intellectual engagement, a desire to think more
critically and actively about social issues, and improvements in academic skills (Gurin
et.al., 2003). The diversity experience has also been shown to impact problem solving
skills (Chang, 1999, and Hurtado, 2001) and increased involvement in learning with
groups and collaborations with other students (Terenzini, Cabrera, Colbeck, Bjorkland
& Parente, 2001). An awareness of others’ points of view and developing solutions to
legal problems has also been identified as a learning outcome (Orfield and Whitla,
2001).
Interaction with diversity in the undergraduate experience also leads to
stronger democracy outcomes (Gurin et al., 2003). These outcomes are identified as a
willingness to promote racial understanding, involvement in political activities,
increased community service, better sense of common values with fellow
undergraduate students from different racial and ethnic backgrounds, and increased

17

likelihood of involvement in community affairs after graduating from college
(Antonio, 2001, Gurin et.al., 2003). Increases in long-term living arrangements and
social relationships involving people from different racial and ethnic backgrounds
have also been described as a democracy outcome (Bowen & Bok, 1998; Gurin et.al.,
2003). If using the student demographic data reported earlier is any indication of the
level of learning outcomes and democracy outcomes that exist in California public
universities, then public university education overall is surely affected by the lack of
ethnic and cultural diversity; most notably in the University of California.
Increasing the numbers of Latina/o and African American students in public
four-year, post-secondary institutions is in the public’s best democratic and economic
interest (The Education Trust, 2006). The statistical data on discrepancies between the
proportions of Latina/o and African American in K-12 California schools and the CSU
and UC systems provides us with a glimpse on how far away we are from this public
interest. The research on ethnic and cultural diversity in the quality of an
undergraduate curriculum, demonstrates the importance of finding new methods to
bridge more Latina/o and African American students from secondary to postsecondary
institutions.
College Preparation Outreach and Programming
Methods used in increasing underrepresented and low-income students in
public four-year, post-secondary institutions often come in many forms. One of these
forms is the college preparation outreach program, which has three different categories
(MGT, 2000). The first category is the Informational Outreach Program, where the
focus is on providing information about how to prepare for college, financial aid

18

options, taking the right high school courses, and admissions deadlines. The second
category is the Student Academic Preparation Program, where a program works
closely with the student by focusing on improving academic skills. The third category
is the School Improvement Program, which provides curriculum support and other
services to teachers and staff to strengthen student academic performance.
Typically college preparation outreach programs help all students, and some
others have a special focus on underrepresented populations or first-generation
college-going and low-income students. Some examples of these programs are non-
profit organizations (i.e., Fulfillment Fund), government-sponsored programs (i.e.,
California Student Opportunity and Access Program – Cal SOAP – and Gaining Early
Access and Readiness for Undergraduate Programs – GEAR UP), literature (i.e.,
College: Making It Happen!), and university funded programs (i.e., CSU Outreach and
Recruitment, UC Early Academic Outreach Program, the University of Southern
California “I AM” program). These types of programs focus on serving the college-
preparation information needs for particular segments of K-12 students, again with
special emphasis on students who are underrepresented and/or come from low-income
families and who are first-generation college-going students.
Since 1970, with the inception of the Mathematics, Engineering, Science
Achievement (MESA) program, the California legislature has funded 19 different
college outreach programs to support the college preparation of low-income and
underrepresented K-12 students (MGT, 2002). These 19 programs are examples of
the many inroads that have been made in trying to increase the numbers of low-
income and underrepresented students in postsecondary education.

19

Tierney, Colar and Corwin (2003) provide us with nine components/questions
to consider, not require, in determining if a college preparation program, like the ones
mentioned above, is effective. First, does the program encourage students to take a
rigorous academic curriculum? Second, what is the level of college academic
counseling provided by the high school counselor? Third, are students participating in
college-related community- and school-based activities? Fourth, are culturally-
sensitive college-preparation tools provided? Fifth, does the program encourage
parental and community involvement in supporting the college-prep message away
from the high school campus? Sixth, does the program foster the development of
peer-support and –learning groups? Seven, are college preparation mentoring
opportunities available? Eight, does the program build on early and consistent K-12
college preparation messages. Lastly number nine, is the program being accountable
to the financial costs and purpose of the program? These are the nine factors to be
considered in determining if a college-preparation program has the best chance of
succeeding in strengthening college access to first-generation college-going students.
Another method used in increasing underrepresented and low-income students
in public four-year, post-secondary institutions is creation of college-going cultures at
school sites. Instead of having college preparation information provided to a student
on a seasonal basis or through participation in a college-preparation organization or
activity, the school becomes “the college-preparation message”. This is done by
adapting the infrastructure of the school site on the college preparation needs of its
students.

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One example of how a middle or high school can establish a college-going
culture are the nine principles put forward by McClafferty, McDonough and Nunez
(2000). These nine principles for creating a college-going culture represent a roadmap
for a secondary school that wants to be pro-active in preparing their students to
become competitive college applicants. The first principle, College Talk, focuses on
the school communicating to the student the information on the requirements to be
accepted to a college (McClafferty, McDonough and Nunez, 2000). The second
principle, Clear Expectations, emphasizes the recognition students, parents, and all
school staff should have in the role they play in preparing for college. The third
principle, Information and Resources, current and relevant information on college-
preparation needs to be readily available to the student and his/her family. The fourth
principle, Comprehensive Counseling Model, emphasizes that all high school
counselors are college guidance counselors, all ready to help students with any
questions about attending a college. The fifth principle, Testing and Curriculum,
stresses the importance of students being aware of placement exams needed to become
eligible for the baccalaureate-level college application process. The sixth and seventh
principles of Faculty Involvement and Family Involvement are related to the fourth
principle, instead it is now the school faculty and family members who need to work
together to become competent in basic college-preparation information. The eighth
principle, College Partnerships, secondary and post-secondary schools need to work
together in creating activities that strengthen the college-preparation message and
expectation for students. The ninth principle, Articulation, represents the consistent
expectation for attending a college that should exist throughout all grades in the K-12

21

pipeline. In this last principle, each grade level should support the grade level before
it with a consistent expectation and message to students about how they will be going
to college.
Despite all the resources dedicated towards preparing K-12 students for
college admissions, too many underrepresented and first-generation college-going
students still have limited access to information about their postsecondary options,
what classes to take to become eligible for university admissions, how to prepare for
the SAT and ACT, and how to pay for a college tuition (Venezia, Kirst, & Antonio,
2003). California public high schools are short on resources to effectively and
significantly help low-income underrepresented students attain information about the
requirements to attend college, application deadlines, and how to pay for college.
Compounding the dilemma is the focus of most university outreach programs
concerned with recruitment and enrollment management than college preparation.
Fortunately or unfortunately, this places the responsibility of acquiring and making
sense of college preparation materials squarely on the high school student (Tomas
Rivera Policy Institute, 2005).
In a recent report to the National Postsecondary Education Cooperative, Kuh,
Kinzie, Buckley, Bridges, & Hayek, (2006), identified some areas for research to help
our understanding of components that may influence student success before and
during college. The first area of research was to identify more effective methods for
encouraging different kinds of students (e.g., first-generation, low income, students of
color, men) to become more involved in postsecondary preparation programs. In the
case of programming, whether these programs have an academic or vocational focus,

22

who are their students and what impact do these programs have longitudinally on
student success? Regarding learning methods or pedagogical tools, what research has
been done on them concerning their application to college preparation and what can
we take from the results?
According to Luna De La Luna Rosa and Tierney (n.d.), it is recommended
that both college preparation information and financial aid information need to be
provided to high school students in the 9th grade. This allows students to become
aware of how college is both not only attainable but also possibly affordable.
Universities and colleges need to help strengthen this awareness to increase the pool of
eligible college applicants. Instead, colleges often battle in a never ending race for
enrolling students with high grad-point averages, high placement scores, advanced
placement scholar titles, what Tierney (2005) labels the ‘Talented Tenth’ (p. 144).
Tierney suggests more methods need to be created in order to expand this “Talented
Tenth” into a continuous growing high school pool of competitive university
applicants, including underrepresented students. This study responds to the
recommendation of Kuh et. al. and Luna De La Rosa and Tierney by investigating
how problem-based learning can be used in strengthening college preparation among
high school students. This study represents an investigation that may uncover a new
college preparation tool to be used in helping increase the applicant pool of
underrepresented competitive university applicants.
Problem-Based Learning
Problem-based learning (PBL) has been described as a learning process where
students from elementary school through graduate programs are presented with a

23

problem that challenges them to apply reasoning, questioning, researching, and critical
thinking – both individually and within groups – in order to find the solution to the
problem (Schallert, 2006). Problem-based learning has also been described as a
“cognitive apprenticeship” focusing on the knowledge of a particular topic through
using a real case example and the application of problem solving activities associated
with the knowledge in that case (Savery & Duffy, 1995); a kind of “ideology routed in
the experiential tradition” (Savin-Baden, 2000, p. 17). This is a key difference
between PBL and other problem-based approaches using cases because other
approaches will use the case example to highlight critical knowledge and learning
areas; thus emphasizing content (Savery & Duffy, 1995). Problem-based learning
takes the case example and uses it as a tool to engage the learner in problem solving
activities related to the case.
Problem-based learning is often confused with project-based learning,
problem-solving learning, and action learning (Major & Savin-Baden, 2004). Project-
based learning contains more structured problem-solving tasks that are established by
a tutor/facilitator who acts as a supervisor, with the role of the student being to
complete a project or being part of a team that develops a solution or strategy towards
problem solving (Major & Savin-Baden, 2004). Problem-solving learning is
facilitated through the introduction of a step-by-step logical problem solving
procedure that is provided by a lecturer (Major & Savin-Baden, 2004). The student in
problem-solving learning acquires knowledge through the pre-prescribed problem
solving activities. Action learning is characterized by group-led discussions and
reflection on actions by a tutor, with the student acting as their own advisor who

24

achieves their problem solving goals and helps other students reach their goals through
reflection and action (Major & Savin-Baden, 2004). Problem-based learning is
characterized by open-ended situations and challenge that are relevant to the stage of
inquiry a learner is at. The facilitator in PBL guides the learning by asking questions
and allowing the participant to own their own learning by identifying what is known
and not known; leading to what needs to be known in order to understand a particular
challenge (Major & Savin-Baden, 2004)
Problem-based learning has been implemented in different ways, yet key
features remain constant: a group facilitator guides the students through the PBL
exercise by using a real-case scenario to stimulate interest in a problem/question/issue;
students identify learning needs as a group by agreeing with what is known and not
known from the case presented; students then collect information and resources –
usually done away from the group - to address the learning needs needed to resolve the
problem/question/issue; the case is then revisited with newly acquired information and
resources; the group re-assesses what more needs to be done to solve the
problem/question/issue or decide the case is solved; finally the students are involved
in self- and peer-evaluations to provide an assessment of each individual and the group
performance as a whole during the problem-solving activity (Barrows, 1986; Berkson,
1993; Boud & Feletti, 1999; Colliver, 2000; Dochy, Segers, Van den Bossche, &
Gijbels, 2003; Vernon & Blake, 1993). This is very different from the traditional
teaching methods of teacher being the expert, the disseminator of information, one
who professes (Savin-Baden, 2000).

25

Problem-based learning has its origin in the growth of innovative teaching
pedagogy in the health sciences over 30 years ago in North America (Boud & Feletti,
1999). Due to a significant increase in the new medical information generated,
medical technology advancing at a rapid pace, and changing demands for the medical
practice, medical education had to evolve from its intensive and exhaustive lecture and
teaching programs in order to prepare students for these new challenges (Barrows &
Tamblyn, 1980; Boud & Feletti, 1999).
Problem-based learning first appeared in the medical education field with the
medical faculty at McMaster University in Canada during the mid-1960s. A slow and
gradual increase in the use of PBL in medical schools occurred during the 1970’s and
1980s, culminating into today’s use of PBL – whether in a greater or lesser extent - in
the curricula of most medical schools in the United States and in almost every country
around the world (Camp, 1996). Problem-based learning has now spread to such
fields as business, engineering, law, social work, forestry, police science, and other
professional fields (Camp 1996). The K-16 curricula has also felt the influence of
PBL (Camp, 1996)
Problem-based learning (PBL) has had a significant impact on how some
medical schools train their professional students in the health sciences (Wilkerson and
Gijselaers, 1996). Most of the research evidence on PBL originates from research
conducted in medical schools, and has branched into such areas as gifted education
(Hmelo-Silver, 2004) and general teacher pedagogy (Major and Palmer, 2006; Ernst,
Taylor, and Peterson, 2005; Ochoa and Robinson, 2005; Edwards and Hammer, 2006).
Problem-based learning has also been applied to elementary school education

26

(Zumbach, Kumpf and Koch, 2004; Pederson and Liu, 2002), middle school (Cho,
Hsieh, Liu, and Schallert, 2006; Bolinger, Memory, Warren, and Yoder, 2004; Brush,
Klein and Simons, 2004), and high school education (Gallagher, 2000; Butler, 1999;
Schneider, Krajcik, Marx, and Soloway, 2002).
From these studies, problem-based learning has been found to be a significant
tool in helping students or learners build collaboration relationships, listening skills
and time management. A considerable amount of additional research evidence
supports PBL as effective in helping students develop flexible knowledge, stronger
problem-solving skills, and increased self-directed learning (Hmelo-Silver, 2004).
Problem-Based Learning and Behavioral Theories
Even though some of the behavioral theories may run counter to problem-
based learning, PBL still demonstrates some behaviorist characteristics (Savin-Baden
& Major, 2004). Thorndike’s connectionism learning theory is an example of the
presence of behavioral theory as part of the foundation for problem-based learning
(Savin-Baden & Major, 2004).
Connectionism evolved from Edwin R. Guthrie’s theory of learning where
learning is understood as the ability to behave differently and permanently because of
previous behavior in a certain situation (i.e., practice makes perfect) (Gazda &
Corsini, 1980). Connectionism also has its roots in Burrhus F. Skinner’s theory of
learning where a stimulus elicits a response and is then reinforced through repeated
responses due to the stimulus (Skinner, 1931).
As an educational psychologist at Columbia University, Edward E.
Thorndike’s theory of connectionism took the stimulus-response framework typical of

27

behavioral theories and applied it to human cognition and learning (Walker, 1990).
Thorndike believed that learning was a by-product of the strengthening of
connections, or associations, between a response and the stimuli present at the time of
the response (Walker, 1996). The strengthening of the connections is tied to a
satisfier, which is anything animal or human will want to achieve or obtain without
avoidance (Thorndike, 1911). Over time, this satisfier reinforces the connections
between the stimulus and the response. Thorndike’s concept of connectionism
provides an understanding of the strengthening of learning through feedback, clear
goals, and practice through repetition, concepts that are very much part of problem-
based learning.
Another version of the stimuli-response conditioning is Clark Leonard Hull’s
drive-reduction theory, which has influenced a tremendous amount of research about
how we learn and how motivation is a factor in this learning (Walker, 1996). In drive-
reduction theory, the reinforcement process does not come from the satisfier, but
instead from the need to reduce a particular drive or an undesirable drive-stimuli
(Walker, 1996). The need in drive-reduction theory is an animal’s physiological
deficit of something that is needed for survival, such as water or food. This need then
leads to a drive to push an animal towards action leading to the reduction of the
undesirable stimuli. Reinforcement is achieved when fulfillment of the need reduces
the drive, thus culminating in a reduction of the undesirable stimuli.
The other side of drive-reduction theory is Sheffield’s (1954, 1960) drive-
induction theory. This theory postulates that reinforcement occurs when a stimulus
elicits arousal induction rather than reduction.

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For example, a hungry animal noticing the presence of food will usually
become noticeably agitated and excited. All the events and situations leading up to the
stimuli, in this case the food, become secondary reinforcers and build on the increase
in excitement; culminating in the attainment of the stimuli (Walker, 1996). Therefore
the excitement an animal feels is a reinforcing agent until the stimuli is reached.
Zajonc (1965) provides a different interpretation for drive theory by applying it
to the study of social facilitation. A drive theoretical approach to social facilitation
states that the presence of others can enhance the drive of a learner. As the learner
begins to master the desired response in the midst of others, the reinforcement from
others within the social setting can increase the drive level of the learner (Weiner,
1992). However the opposite can happen as well. If the learner encounters a difficult
task while in a social setting, the drive level can be reduced significantly because the
incorrect responses resulting from the difficulty become augmented by the presence of
the social setting (Weiner, 1992).
Even though theories like drive-reduction and drive-induction provided an
archetype for the experimental study of motivation (Weiner, 1992), one of the
problems with these behavioral theories is it’s mechanistic view that learning cannot
be observed unless there are overt behavioral changes to be measured (Savin-Baden &
Major, 2004). This viewpoint then focuses on the outcome of the learning rather than
the cyclical nature of learning that PBL promotes. According to Savin-Baden &
Major (2004), behavioral theories have provided theoretical foundations for
understanding the effectiveness of PBL, yet in the end proved to be too simplistic.
Where behaviorists focus on the acquisitions of skills and knowledge, problem-based

29

learning focuses more on the various ways on “how learning occurs”; whether
individually or socially.
Problem-Based Learning and Cognitive Theories
While behavioral theories focused on observable, physically describable
behaviors and provided mathematical models in order to predict behavior, cognitive
theories provide an important lens for understanding the problem-based learning by
focusing more on the mental processes of learning (Savin-Baden & Major, 2004).
Focusing on the understanding of how one learns is the essence of a cognitive theorist;
as well as a central tenet of problem-based learning. One tool cognitive theorists use
to understand learning is through a learner’s cognitive structuring or schemas,
categories of information that organize current and new learning experiences and
perceptions. Using Michael Wertheimer’s (1985) definition of schema, a schema is an
intricate knowledge structure embodying three key components: (1) the goals that can
be achieved through the completion of specific steps and operations contained in the
schema, (2) the pre-determined conditions necessary for a schema to successfully
exist, and (3) the knowledge structures and processes necessary to bring about the
schema’s goals to fruition. As new or modified information is learned, these schemas
change and are modified in order to provide new understandings or create new
information and relationships (Gallimore, Tharp, & John-Steiner, 1992; Stillings,
Feinstein, Garfield, Rissland, Rosenbaum, Weisler, & Baker-Ward, 1987).
Cognitive schemas provide insight into the development of a learner’s capacity
to add new information on top of pre-existing information, which can lead to the
development of new skills that may enhance learning. Just the same, problem-based

30

learning shares the view of a student entering a new learning environment or task with
pre-existing biases, knowledge and schemas (Savin-Baden & Major, 2004). Problem-
based learning uses this prior knowledge to identify where the learner is and utilize
this pre-existing knowledge and schema to identify what information needs to be
acquired in order to make the new learning environment or task meaningful and
understood.
Interestingly, cognitive theories tend to be more abstract than behavioral
theories in that the cognitive research is harder to measure or evaluate scientifically as
compared to behavioral research. The same can be said about problem-based learning,
where it can be more challenging to scientifically evaluate the impact of problem-
based learning, as compared to instruction focusing on memorization, fact-driven, or
acquisition of a skill (Savin-Baden & Major, 2004).
Edward C. Tolman’s cognitive mapping is one example of cognitive theory
supporting problem-based learning. Rather than focusing on the stimulus-response
connections, like those in behavioral theory, Tolman (1948) postulates that the learner
acquires information through the exposure of stimuli and then establishes schema sets
which create cognitive maps to make sense of a particular environment. As additional
information is acquired through the exposure of stimuli, the learner becomes more
selective with accepting or rejecting the newly acquired information based on the
information’s fit with the cognitive map created by the learner (Tolman, 1948). The
strength of this cognitive map is dictated by the goal of the learner and how often the
learner uses the map as a result of the strength of the goal. Therefore learning is
always with purpose and focus because it is attached to a goal (Savin-Baden & Major,

31

2004). Problem-based learning follows the same logic, where learners focus on a goal
and identify their own cognitive map, identify its shortcomings, and acquire new
information to address these shortcomings, therefore changing and strengthening the
cognitive map.
Max Wertheimer (1959) provided his cognitive-based perspective on thinking
and problem solving by focusing on the overall process of how to solve a problem.
Wertheimer proposed that the course of thinking embodies six characteristics: (1) the
thinking process is focused and productive, (2) the central processes of thinking
involve grouping, centering, and reorganization of schemas, (3) the thinking
components and operations are related to a whole or to a structure, (4) the phases of
the learning are related to the whole or to the structure, (5) the thinking processes
demonstrate a fluent and consistent development, and (6) the end result leads to truths
that change and strengthen cognitive structure and schema.
Wertheimer (1959) further argues that thinking and problem-solving flows
from the development of a situation (S1) where knowledge gaps and inconsistencies
exist, to a situation (S2) where these gaps and inconsistencies have been addressed and
are closed. The gaps and inconsistencies provide the stimulus for the learner to gather
information as it relates to the overall whole or structure of the problem. This is the
essence of problem-based learning, where gaps in knowledge provide the learning
opportunities to explore and gather information in order to solve a problem.
Cognitive Theories: The Zone of Proximal Development and Scaffolding
The soviet psychologist Lev Vygotsky (1978) provides us with an opportunity
to see the relationship between social development and problem-based learning.

32

Vygotsky theorized that everything learned during a child’s development is learned
first at a social level, and then afterwards at the individual level. Therefore, the
knowledge and competencies crucial to problem solving and learning (e.g.,
coordinating, planning, goal attainment strategies, etc.) are first developed through
interactions with others in a social environment, and then later become incorporated
into the learner’s repertoire of skills and techniques through independent activities
(Rogoff & Wertsch, 1984; Wertsch, Minick, & Arns, 1984). Essentially, the
foundation for learning in a child or a learner is through relationships, partnerships and
even group collaborations, helping make sense and meaning of the outside world.
Vygotsky’s zone of proximal development sheds light on the higher order
learning that takes place in the social level when a child or learner encounters
something for the first time. Vygotsky’s (1984) zone of proximal development (ZPD)
is defined as the distance between what a child or learner actually knows and
understands (what a learner can do through independent problem solving – zone of
actual development (ZAD)), and the child’s or learner’s potential for higher level of
knowing and understanding (what a learner can do with the problem-solving guidance
of someone who is more knowledgeable about a particular field of knowledge –
(ZPD)), as shown in Figure 1. Simply put, the zone of proximal development is the
area between what a learner already knows and the boundary of where he/she is
capable of learning more, with the assistance of a guide or teacher (Tudge, 1992).

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Figure 1. Model of Vygotsky’s zone of proximal development.

Interestingly, once a learner has moved beyond the zone of actual development
and reaches the outer boundary of the zone of proximal development, the outer
boundary becomes the new boundary for the ZAD. If the learner so chooses, the
process starts again with the aid of a mentor, moving beyond the ZAD to reach the
new outer boundary of the ZPD (Harland, 2003).
According to Vygotsky’s zone of proximal development, the starting point for
instruction is the current level of knowledge of the learner, the same as in problem-
based learning. Problem-based learning follows the same logic as the zone of
proximal development, with an experienced facilitator guiding the learning and social
collaborations amongst the learners. In the problem-based learning environment, the
zone of proximal development expands through the identification of knowledge gaps
and the group collaboration focusing on closing the knowledge gaps. This culminates
Zone of Actual
Development
Zone of Proximal
Development

34

in new a understanding based on the acquisition of new knowledge, with the guidance
of a PBL facilitator.
The concept of scaffolding, first introduced by Vygotsky and Luria (van der
Veer & Valsiner, 1991) and then made more mainstream by Bruner (1978), has been
used to describe the inner workings of problem-based learning. Bruner used the term
“scaffolding” as a correlation to a mother’s verbal cues in trying to communicate with
and foster language skills in their children. Bruner (1978) stated that a mother’s
scaffolding activities encompass five distinct characteristics: (1) making a task easy to
understand, (2) capturing the child’s attention and focus, (3) providing models for
comprehension, (4) expanding the lesson of the immediate situation to a larger lesson
or principle, and (5) providing support so the child does not revert back to old
behaviors.
Wood, Bruner and Ross (1978) also used the term “scaffolding” in the field of
educational psychology, referring to how someone with more experienced knowledge
helps another who is less experienced in that same knowledge. Wood, Bruner and
Ross (1978) argues for the importance of six characteristics that need to be present in
order for a tutor’s actions to be effective: (1) capturing the attention of the
learner/student, (2) keeping the task understandable through implementation of small
steps, (3) maintaining focus on goals, (4) identifying important learning milestones,
(5) managing possible frustration and other emotions from the learner/student, and (6)
modeling problem solving and finding the solution.
The concepts of zone of proximal development and scaffolding are two of the
most important concepts in cognitive psychology and socio-cultural theory. The

35

mechanics of problem-based learning, specifically the relationship between the
tutor/facilitator and the learner, can be seen in the concept of scaffolding within the
zone of proximal development. The challenge of the facilitator in the problem-based
learning environment is to guide the learner(s) through a discovery process where
identification of current boundaries in knowledge is identified in order to expand to
new boundaries of knowledge.
Problem-Based Learning and other cognitive theories
How a learner approaches learning is also a hallmark of cognitive psychology
(Savin-Baden & Major, 2004). This area of interest originated from the research
conducted by Marton and Saljo (1976a, 1976b), where they identified two kinds of
learners: the learner who focuses on the memorization of knowledge (surface-level
processing) and the learner who focuses on attaching meaning to the knowledge
(deep-level processing).
Pask and Scott (1972) supplemented these findings by Marton and Saljo with
their identification of the holist and serialist learning approaches. Pask & Scott
studied 16 college students and observed how each of them carried out a specific task
and then taught back what they learned. From this study, Pask and Scott identified a
holist as a learner who first tries to understand the whole through interrelationships
and then approaches the details to finalize an understanding of the whole. They also
identified a serialist as a learner who approaches an understanding of the whole by
first going step-by-step through details, upon which a complete picture emerges of the
whole (Pask & Scott, 1972).

36

Afterwards, Pask (1976) argued there were learning style preferences that
dictated how a learner would approach solving a problem, even if the solution to the
problem required a learning strategy the learner did not prefer. Thus, if an
environment favors a holist approach (comprehensive learning) to solving the
problem, a learner will still prefer to use a serialist approach (operational learning) to
solve the problem if that is what the learner favors. Students who are able to utilize
either approach appropriate to the environment would be displaying a versatile style of
learning (Pask, 1976). This ideal versatile style is a level every learner should aspire
to reach for, or else a learner will grow cemented in a way of approaching a problem
to be solved.
Entwistle, Hanley & Hounsell (1979) built upon the original two learning
approaches – surface-level and deep-level approaches - through a study that
encompassed 767 students from nine different departments and among three British
universities. By using a factor analysis instrument, the Lancaster Inventory of Study
Strategies, that accounted for a variety of approaches students employed towards
studying, Entwistle et. al. (1979) were able to identify a third learning approach; the
strategic approach. While the deep-level/holist approach (i.e., learning for
comprehension, learning for intrinsic values, links learning to real life, comprehensive
learning not focused on a class syllabus, views education as an opportunity to question
values) and surface-level/serialist approach (i.e., learning is focused on factual details
and rote learning methods, motivated by anxiety or fear or failure, learning dictated by
the class syllabus, views education as an opportunity to obtain necessary
qualifications) represented opposite dimensions of a student’s approach towards

37

formal education, the strategic approach has it’s main characteristics in organized
study practices, time-management skills, behavior focused on impressing the teacher,
and a positive mental approach towards studying. The strategic approach also
contains elements of the deep-level/holist approach, such as a student who builds
relationships with fellow classmates or teachers in order to master class material,
among other proactive behaviors.
Interestingly, these learning approaches fit very closely with the findings of
three main orientations of studying by Biggs (1978, 1979). These three orientations
are intentions that seem to be attached to deep personal motives of the learner,
resulting in the learner’s predisposition of a learning approach. A personal meaning
orientation was found to be associated with values of personal development, intrinsic
motives, and learning strategies used to link new information with existing
information. A reproducing orientation was associated with values of vocational
preparation through education, extrinsic motivation linked to need for required
qualifications from a field, and learning strategies linked to activities that were
required by a syllabus. An achieving orientation was tied to values of opportunities to
compete and demonstrate excellence in the educational arena, a motivation to compete
at the highest level and succeed, and learning strategies associated with effective time-
management, and meeting deadlines; winning “the game” in education.
Problem-based learning embodies each of these learning approaches and styles
(Savin-Baden & Major, 2004). An individual in the problem-based learning
environment may first start with surface-level processing and then move towards
deep-surface level processing as knowledge gaps are filled and confidence in the

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subject material is gained. Strategic learning can also be displayed during the filling
of knowledge gaps in the middle of the problem-based learning environment.
Problem-Based Learning and cognitive theories: The developmental theories
The cognitive developmental theories provide us with a lens into how
cognition can be appreciated as an active process (Savin-Baden & Major, 2004). The
first of these theories is Piaget’s cognitive development theory (Piaget, 1929).
According to Piaget (1929), a human being evolves through four distinct stage
of knowledge in order to reach a more accurate understanding of the world; (1) the
sensorimotor stage where children, from birth to age two, experience the world
through sense and movement, (2) the preoperational stage where children, ages two to
seven, begin to understand more through symbols and increased acquisition of motor
skills, (3) the concrete operational stage, from ages seven to 12, where children begin
to think logically about events witnessed, and (4) the formal operational stage where
adolescents, after age 12, can deduce and think abstractly about information. Piaget’s
cognitive development theory was one of the first that identified the development of
learning as a developmental process occurring over time (Savin-Baden & Major,
2004).
Building upon these four stages is William Perry’s (1970, 1988) nine positions
of intellectual and moral development, from qualitative research he conducted with
college students. According to Perry, students move through nine positions of
intellectual and moral development, classified together in four different categories.
The first category is called Dualism – comprised of the Basic Duality Position and
Full Duality Position – and is characterized by the student moving from learning the

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right solution to a problem towards learning the right solution and then ignoring other
solutions to a problem. Believing there is a right and wrong way of seeing things, no
alternatives. The student then moves on to the second group called Multiplicity –
comprised of Early Multiplicity and Late Multiplicity positions -, where students
move from identifying that there are solutions to problems we do know and other
solutions we don’t know towards a new identification of everyone having a right to an
opinion of a solution or that that problems are unsolvable. Students still try to retain
their dualistic viewpoint but begin to notice a diversity of opinions from others and
other plausible explanations their right-versus-wrong perception cannot provide.
From this awareness comes the third group, Relativism. This group is comprised of
the Contextual Relativism Position and Pre-Commitment Position where dualism now
becomes the exception and everything can be explained according to how it relates to
a person or situation. It is at this point where a student truly becomes aware of the
various opinions and explanation for what the world presents, allowing the student to
come closer to what they feel is the correct viewpoint or value. The fourth group,
Commitment, is comprised of the Commitment, Challenges to Commitment, and Post-
Commitment positions. It is in this group where the students know and commit to
what they want and consider the necessary measures needed to be taken in order to
make what they want actually happen.
The final group of Commitment in Perry’s nine positions can be seen in
Ausubel’s Assimilation Theory of Meaningful Learning (Savin-Baden & Major,
2004). According to this theory (Ausubel, 1968; Ausubel, Novak, & Hanesian, 1978),
learning has to be related to meaning, and that meaning is based on and supported by

40

what the learner already knows. This process of acquiring new knowledge by using
previously acquired knowledge strengthens the overall knowledge of the learner, as
well as the connections between the old and new knowledge. The final by-product of
this process is a stronger ability to recall and use the new information, resulting in a
learning process considered to be more meaningful. Three components are necessary
in order for meaningful learning to occur; prior knowledge related to a particular
subject, the new material/knowledge about the subject, and the learner’s decision to
use meaningful learning by connecting the old with the new material/knowledge.
The Theory of Meaningful Learning ties in very well with the Gestaltists (Max
Wertheimer, Wolfgang Kohler, and Kurt Koffka) who emphasize the importance of
the whole, or organization, in the learning process (Shanks, 1995). According to
Gestalt Theory, when a learner begins to see “the whole”, a cognitive process takes
place where the learner pieces together and comprehends the parts, resulting in an
awareness of “a whole”. When the learner wants to retrieve information, this is
accomplished by a holistic reactivation of the traces of memory from the new
information to the old; not just remembering one piece of information (Shanks, 1995).
Wertheimer (1959) was particularly interested in Gestalt Theory’s application to
problem-solving. Wertheimer argued that the essence of solving a problem is to
envision the whole problem. The spirit of this argument is held in Wertheimer’s Law
of Pragnanz (1912), which focuses on the simplicity of thinking, or a learning or
mental realization where the learner identifies the most stable, streamlined, or ordered
way of seeing a concept or problem because of recognition of “the whole” (Kubovy,
2001).

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Problem-based learning has its foundation in all the cognitive theories
presented. According to Norman and Schmidt (1992), problem-based learning can
lead to the increased retention of knowledge, facilitate the transfer of understanding
from old concepts to new material, increase the learner’s intrinsic interest in a subject
matter, and strengthen the learner’s appreciation of self-directed learning. All these
problem-based learning findings are supported by cognitive theory.
Problem-Based Learning and Humanist Theories.
Humanist psychological theory provides a different lens upon which to view
problem-based learning; the development and cultivation of the self, to find one’s
place in life, and the search for personal meaning (Nevill, 1977). As Donald E.
Polkinghorne (2001) also states, the major contribution humanists gave to psychology
“was reintroducing the self into the conversation of psychology” (p.81).
Humanists such Abraham Maslow and Carl Rogers believe human beings are
born with inner potentials – talents, needs, ideas, physical gifts – that will appear in
various stages of a persons lifetime if allowed to grow (Poppen, Wandersman, &
Wandersman, 1976). Specifically about the potential for learning, Rogers identified
two different kinds of learning. First is cognitive learning, where a learner has to
acquire knowledge that can be considered academic; vocabulary lists, multiplication
tables, scientific facts, and other material that has no relevance to the personal
meaning of the learner (Rogers, 1983). Second is experiential learning, where the
learning does have relevance to the personal meaning of the learner, thus addressing
the needs and wants of what the learner needs to know in order to function in his/her
reality. Key elements of experiential learning are (1) the quality of the “whole person”

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involvement in the learning, (2) the level of self-initiative the learner has for the
knowledge, (3) the pervasiveness of the learning experience in the behavior, attitudes,
thinking and outlook of the learner, and (4) the learner’s evaluation of the relevancy
and personal meaning of the learning and how it fills the once unsatisfied niche
(Rogers, 1983).
Rogers & Freiberg (1994) also discuss the teacher’s role in the learning
process. They identified a teacher as a facilitator who feeds the student’s curiosity to
learn. The best way to satisfy the students’ appetite to learn is to teach them how to
learn. The true teacher has no time to be an authoritarian or to profess. A constructive
process begins when the teacher chooses to trust the competency of his/her students.
An example is the teacher understanding what students feel during the learning
process, as well as he/she choosing to be “real” with their students.
Problem-based learning operates much the same way, with the learner being
exposed to new knowledge, then identifying the gap in understanding between what
he/she knows and what more needs to be understood (i.e., knowledge gap), and then
acquiring the necessary knowledge to bridge the knowledge gap (Birch, 1986). The
PBL facilitator strengthens this growth by guiding the learning rather than providing
the answers to the questions. Rather than preparing lectures to disseminate
information, the PBL facilitator role is more limited to the asking of questions to help
students consider learning areas that may need addressing. The PBL facilitator also
assists students in their evaluation of their growth in the problem-based learning
environment. Instead of promoting the memorization of knowledge, the PBL
facilitator promotes meta-cognition in learning.

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Maslow provides us with a framework to see learning on a continuum of
physiological needs through self-actualization, as seen in Figure 2.

Figure 2. Abraham H. Maslow’s Hierarchy of Needs.

According to Maslow (1970), a person’s need for self-actualization rests upon
the satisfaction of the needs preceding it; starting with the biological and physiological
needs through to the esteem needs. A significant part of the self-actualization need is
learning. In order for someone to become what he/she want to become (e.g., lawyer,
teacher, business owner, dentist, etc.), he/she needs to learn certain skills and
knowledge. As a learner, knowledge and skills are acquired in order to become self-
actualized.
Biological and Physiological needs – nutrition, shelter, sleep, etc.

Safety needs – freedom from fear, anxiety and chaos

Belongingness and Love needs – relationships and affection
Esteem needs – high evaluation of self
Self-actualization – desire for self-fulfillment

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Problem-based learning can be seen in Maslow’s self-actualization need,
where a learning environment is provided for someone to self-actualize themselves
towards a learning goal. Whether the learning goal is a profession or skill, the goal is
an important part of the person’s need to become whole or competent in the chosen
skill or profession.
Problem-based learning and Multiple Perspectives on Learning
Branching from the theories labeled as behavioral, cognitive, or humanist,
come other theories of learning that embody some or all of these theories of learning
(Savin-Baden & Major, 2004). The theories discussed here, in a sense, more closely
resemble the multiple characteristics of problem-based learning; the importance of
learning, the role of the facilitator, and the importance of experience in the learning
process.
Constructivism
Problem-based learning has been described as a constructivist-based teaching
model that strengthens thinking and problem-solving skills (Edens, 2000). Although
constructivism has a long history as a theory of perception and memory (Bartlett,
1932; Eysenck & Keane, 1995; Gregory, 1981; Neisser, 1967), its central tenet as a
theory of learning is that human knowledge is acquired through a process of active
learning. Knowledge is acquisition rather than absorption, and invention rather than
discovery. Knowledge must have personal relevance, be socially constructed, and
support learning that helps makes sense of the world, and the use of challenging
problems for the learner to solve (Fox, 2001).

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From the teacher’s perspective, constructivists view this role quite differently
from the typical “expert” who professes information from lectures and textbooks to fill
the empty vessel; the student’s open mind. On the contrary, the constructivist teacher
facilitates the learning by creating the environment where a learner has the opportunity
to grow his/her own meaningful knowledge (Trotter, 1995). These constructivist
principles of the student as the active learner, the teacher as facilitator, and meaningful
learning and understanding that comes from interactions with the environment, are
also characteristics of problem-based learning. Problem-based learning provides the
learner with an environment – both in knowledge and peer interactions - to be active in
their learning by identifying knowledge gaps with the help of a facilitator.
Theory of Information Processing
The Theory of Information Processing posits that a person’s memory and
learning is comprised of such processes as attention, selective perception (how a
learner screens out non-relevant information in order to access stored information),
short-term memory storage, rehearsal, long-term memory storage, and retrieval
(Gagne & Dick, 1983). Both what happens inside and outside of the learner – within
the learning environment – are contained within these processes.
From an instructor’s perspective, a set of ordered events are constructed in the
learning environment in order to support the learner’s progress (Gagne, 1977). These
events occur in the learning environment in the following order: (1) gaining the
attention of the learner, (2) introducing the learner to the objective of the learning
environment, (3) recall of preliminary information, (4) introduction of the learning
material, (5), facilitating the learning of the learner, (6) encouraging progress in

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learning, (7) analyzing the performance of the learner, (8) providing constructive
feedback, and (9) supporting the learner’s retention and retrieval of the new
information.
Problem-based learning shares some of the same aspects of information
processing models. From the learner’s perspective, selective perception, rehearsal of
the new learning, long-term memory storage of new information, and retrieval
capabilities from long-term memory storage are all integral components of successful
problem-based learning. For the instructor, the use of preliminary information,
facilitation rather than delivery of the learning, and supporting the retention of the new
learning are common characteristics shared with information process learning models.
Kolb (1976) provides a different layer of information processing through an
inventory of learning styles; a four-step learning process. First, a learner needs a
concrete experience that allows for direct experience with the learning experience.
This direct experience leads to the second step, where the learner engages in reflective
observation on the direct experience and analyzes the information from different
perspectives. This leads to the third step, the learner reaching an opportunity for
abstract conceptualization where what is learned is digested into current knowledge in
order to create generalizations and theories that help make meaning. This newly
digested information is then placed into action in the active experimentation process,
the fourth step. In this step, the learner uses these new generalizations and theories in
order to test them in new learning environments. For each new learning process, the
cycle repeats.

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Kolb provides a lens onto these four steps that groups them into two
fundamental elements (Claxton & Murrell, 1987). First, the learner grasps or
comprehends the information. Second, the learner transforms the learning experience
through active experimentation.
The four-step learning process leads to four different kinds of learners (Kolb,
1976). Divergers are learners who like to grasp learning through direct experience
and then use their imagination to manipulate and reflect on the experience.
Assimilators grasp the learning through bringing together various pieces of
information and then weaving them into an integrated idea or theory. Convergers are
the opposite of the divergers, as they grasp learning by interacting with abstract
concepts – not direct experience – and then actively engage in a learning process that
focuses on one answer. Accommodators are opposite of the assimilators because they
are risk takers by focusing on doing something in order to have new experiences.
These four types of learners are not meant to place an individual as only one kind of
learner. Research on learning styles has demonstrated that, over time, learners become
able to use most or all of these learning styles in order to adapt to different learning
environments (Lassan, 1984; Mentkowski & Strait, 1983)
Kolb’s learning processes can be seen in the problem-based learning
environment. Students directly interacting with the learning, reflecting on the
learning, and then digesting the new information, all occur within problem-based
learning. Students can then take this newly acquired information and actively test it in
real life scenarios, which will lead to more questions requiring the learning processes
to repeat again. The four different learning styles can also be seen in action in a

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problem-based learning environment. Although the direct experience in a problem-
based learning environment is the interaction with group peers, a facilitator, and the
challenge needing solving, all four different learning styles would flourish in a PBL
environment.
Transformational Learning
One of the main contributions to transformational theory comes from Jack
Mezirow’s (1981, 1994) idea of learners having a two dimensional structure to make
meaning from a learning experience; meaning perspectives and meaning scheme.
Meaning perspectives are the learning assumptions and the predispositions a learner
has from their societal and familial experience. The second dimension is the meaning
scheme, where a learner’s beliefs, faith, feeling and biases affect the interpretation of
what is being learned. For example, a meaning scheme can be seen by what a learner
feels about going to college, the importance of religion, or other topics the learner may
consider sensitive. Mezirow (1981, 1994) argues that, at first, a learner will resist
anything that does not fit with these two dimensions. At the same time, however, a
learner has an urge to understand the meaning of a learning experience, especially if it
is foreign and challenges their meaning perspectives and schemes. It is at this point
where transformational meaning structures influence the learning.
Mezirow (1981, 1994) states that it is at a problem-solving stage where a
learners meaning perspectives and schemes are challenged, forcing the learner to
reflect on previously held assumptions, beliefs, and feelings about the foreign concept.
The experience of reflecting on what a problem is and how to solve it allows the

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learner the opportunity to grow and change, or expand, their meaning perspective and
schemes.
Problem-based learning shares the power of reflection through the introduction
of the problem needing to be solved. All participants in the PBL environment enter
with their assumptions and beliefs of what is the cause of the problem, soon
discovering their assumptions and beliefs do not provide a full explanation of the
problem. This leads to the learner re-assessing his/her knowledge. Meaning
perspectives and meaning schemes are challenged and reflection comes into play,
leading to the opportunity for change in a learner’s meaning perspectives and schemes.
Another contribution to transformational theory that adds to the foundation of
problem-based learning is Paulo Freire’s (1972) concept of conscientization. At its
most fundamental level, conscientization is understood as the learning process by
which a learner becomes aware of the reasons why he/she is oppressed (Blackburn,
2000). It is a learning process where the learner becomes aware of the environment
he/she is in and how it shapes his/her reality. From this awareness comes the
transformational opportunity to act upon this reality by learning about the environment
and learning how to change it. The change that comes from the learning experience is
a by-product of the same action Mezirow highlights in the power of problem solving;
reflection of the learner. However, Friere’s conscientization takes the reflection
process a step further by emphasizing the action that comes about because of the
reflection (Blackburn, 2000). The action ultimately leads to further reflection, which
then leads to more action, and the chain reaction continues until the learner’s need for
reflection and action reaches a point where the learner can reach a new state of being,

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thinking, behaving, and believing. Thus the two main ingredients critical to the
occurrence of conscientization are how reflection leads to action and action leads to
more reflection.
Although Freire’s conscientization was focused on the sociology of oppressed
peoples and how knowledge can influence power (Westwood, 1991), his concept of a
symbiotic, synergetic relationship between action and reflection is a powerful yet
simple principle that is equally shared with problem-based learning. In the problem-
based learning environment, the learner has the same opportunity to reflect on what is
not known. Once the learning gap has been identified, a learner moves from reflection
to action in order to acquire knowledge to close the knowledge gap. Just like
problem-based learning, this cycle of reflection repeats until all necessary knowledge
gaps are filled and a conclusion is reached.
Andragogy
According to Knowles (1990), andragogy represents a unified set of
educational assumptions that help explain key characteristics of adult learning, as well
as complementing the ideological model of youth learning; pedagogy. Knowles’ first
assumption of androgogy is that an adult learner needs to know the why about learning
something before starting the learning process (Knowles, 1990). Part of the reason is
when the why about the learning is present, a learner will invest energy into the
process of learning in order to reap the benefits of the learning outcomes (Tough,
1979). The second assumption is that an adult learner has a self-concept of having
ownership and responsibility for the decision he/she makes. Along with this self-
concept comes the psychological need to be recognized by others as someone who is

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competent in making the right decisions for a productive life. Third, adults approach
an education with an increased repertoire of life skills and experiences as compared to
younger students. Fourth, adult learners are tuned in to learning what they need to
know in order to make more informed decisions related to their reality. The key piece
here is the timing of what a learner learns as it relates to what stage of developmental
skills they currently possess. For example, a 9
th
grade student who is interested in
becoming a cardiologist is not ready to learn about cardiology, but is ready to start
preparing for college admissions in order to be a competitive candidate for a university
that has an appropriate undergraduate program for someone who wants to become a
cardiologist. Fifth, adult learners approach learning on a life-centered scale. The
adult learner will be motivated to learn something if what is being learned will help
the learner solve a problem or challenge they are currently encountering. The sixth
and last assumption Knowles identifies is how inner motivation (increased self-
esteem) is more powerful than external motivation (more popularity, material awards)
among adult learners.
Both young and adult learners can fluctuate from androgogy to pedagogoy,
depending on what is being learned. For example, if an adult learner wants to enroll in
a physics class but was never exposed to the principles of physics nor has any real-life
need (e.g., professional development) to study physics, the adult learner would
probably have to depend more on the teacher to move forward in the learning. If a
young learner wants to learn how to prepare for college admissions and has a need to
learn this information because of a real-life need (e.g., a student wanting to be
accepted to a university after high school graduation), the young learner would

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probably depend less on the teacher as they will have more of an inner motivation to
move forward in the learning.
Problem-based learning shares many of the characteristics of andragogy. In
the PBL environment, the why of the learning, the sense of ownership of what is being
learned, the focus on learning that is relevant to current life-decisions, and how inner
motivation becomes the driving engine behind the learning, all these characteristics
exist. Although nothing is mentioned about the facilitators/teachers role, a PBL
facilitator would want to see these characteristics displayed in a problem-based
learning environment.
Social-Interaction Models
Curry (1983) states that learning styles can be organized into four distinct
layers; the first layer being the most stable and then moving to the “upper” layers that
are more fluid and interchangeable. The first layer is how a learner’s personality
dictates learning style. One of the most researched areas in this line of learning style
is the field of dependence-independence dimensions, where learners who are heavily
influenced by the surrounding environment are considered environment-dependent
and learners who are not influenced by the surrounding environment are considered
environment-independent (Witkin, 1976). The second layer is the Information-
Processing model, described earlier in the literature review (Theory of Information
Processing). The third and fourth layers are Social-Interaction, focusing on how
learners tend to interact in a classroom, and Instructional-Preference, focusing on a
learner’s preference for certain teaching methods.

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The Social-Interaction model provides another lens for us to see what kind of
learner can be present in a problem-based learning environment. Based on Reichmann
and Grasha’s (1974) Student Learning Styles Scale, there are six learning styles that
can be present in a classroom. The independent students favor thinking for
themselves. Listening to others is often done, but these learners trust in their own
ability to have the answer to a problem and will determine what they need to learn.
Dependent students only learn what they have to learn, and thus depend heavily on
what the instructor wants in order to have structure for their learning. The
collaborative students need to interact with others in order to learn effectively. The
classroom for the collaborative student becomes a tool in itself for efficient learning
through cooperative learning. Competitive students are focused on the reward and
regard others in the classroom as the challengers. The classroom is the playground
and the objective is to win. Participant students tend to occupy the middle ground in
the classroom. They want to learn, enjoy the classroom environment, but will only do
what is required in order to perform well in the classroom. Finally, the avoidant
student is not interested in any learning objective in the classroom.
In another Social-Interaction model, Eison (1980) provides styles of learning
tied to whether a student’s attitude toward learning is more concerned with grading or
learning. Eison postulated that students were either (1) more concerned with learning
important and relevant ideas in the classroom or (2) more concerned with doing the
required class work in order to receive a desired grade or certification. These two
categories were then enhanced to form four classes of learning orientations (Milton,
Polio, & Eison, 1986): High Learning Orientation/High Grade Orientation, learners

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who are motivated to learn and receive high letter grades; High Learning
Orientation/Low Grade Orientation, learners who approach education for personal
enrichment; Low Learning Orientation/High Grade Orientation, these are learners
who’s only interest in class is to receive a high letter grade; and Low Learning
Orientation/Low Grade Orientation, learners who are not concerned with either
learning or receiving high letter grades. Which orientation a learner adopts may be
related to the learner’s initial level of motivation. According to Chickering and
Havighurst (1981), one level of motivation is instrumental, where the learner is solely
focused on the tangible end result. For example, a student who only completes
required coursework and attain the necessary letter grades in order to graduate and be
recognized with honors. The second level of motivation is developmental, a leaner
who favors the experience of learning rather than a tangible goal; the journey being
more important than the destination.
Certainly in the PBL environment, all six of Reichmann and Grasha’s learning
styles - independent, dependent, collaborative, competitive, participant, avoidant - can
exist. Because problem-based learning focuses on self-directed learning and using
real-life problems to solve, the learning styles of Reichmann and Grasha can all find
an outlet for learning growth. Because the concerns and interests of a secondary
school learner can vary with age (Hendry, Glendinning, & Shucksmith, 1996), the
influence of parental-home environment and socioeconomic level (Kassar, Ryan, Zax,
& Sameroff, 1995), and societal influences (Ovadia, 2003), there is no simple formula
or method for teaching or guiding the learning of students. As a result, teachers must

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use a variety of learning methods to meet the needs of various learning styles;
problem-based learning is one of those methods.
The same with Eison’s learning orientations, all four can exist in a problem-
based learning environment. Whether the student is motivated to learn or not, PBL
provides a learning environment that meets the student at the level of learning interest
they are at with the hopes of increasing motivation for learning.
Problem-Based Learning and Motivation
According to Barrows and Kelson (1995), problem-based learning was
designed to help students build a wide and malleable foundation of knowledge,
problem-solving skills, self-initiated life skills, collaboration and teamwork skills, and
an intrinsic motivation for learning. Intrinsic motivation exists in a learner when
he/she works on challenge that is tied to their interest or passion (Hmelo-Silver, 2004).
When students believe what they are learning is important and has relevance to their
own lives, students become motivated to learn (Ferrari & Mahalingham, 1998;
Leontiev, 1978). The closer a problem or challenge to be solved is to the learner’s
need to solve something tangible in his/her life, the more motivated a learner will be
about the learning process to solve the problem (Bandura, 1997). Also, when students
believe they are in control of their learning outcomes, their motivation for learning
increases (Bandura, 1997; Dweck, 1991).
Research on the motivational effects of problem-based learning has revealed
that group discussions can positively influence a learner’s intrinsic interest and
motivation towards the problem needing to be solved in the PBL environment. In a
1998 study on the effects of group learning in problem-based learning on motivation

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and cognitive outcomes, Dolmans, Wolfhagen, & van der Vleuten (1998) found
motivation to be a central factor in positively influencing group productivity, group
collaborations, and thoroughness of group work. Das Carlo, Swadi and Mpofu (2003)
conducted additional research on the same topic as Dolmans et. al., and also found
motivation for learning to be a characteristic among the students in tutorial groups that
were considered highly productive.
There is promising research that shows problem-based learning leading to
higher levels of motivation for learning among graduate school applicants (Agbor-
Baiyee, Gordon, & Harper, 2000), graduate school students (Barrows & Tamblyn,
1976), professional programs (Barrows, 1996); high school students (Sungar &
Tekkya, 2006), middle school students (Pederson, 2003), and elementary school
students (Cobb, Wodd, Yackel, & Perlwitz, 1992). However, overall there is little
research that has focused on how problem-based learning enhances student motivation
(Hmelo-Silver, 2004). The greatest dearth of PBL-motivation research has been in the
population of K-12 students.
The research that is available on problem-based learning and motivation has
shown PBL to be an effective tool in increasing motivation to learn. This study’s
focus on problem-based learning and its application to the college preparation of
ninth-grade Latina/o and African-American students will add to needed research on
PBL and its influence on motivation on K-12 populations.
Problem-Based Learning and Self-Efficacy
Bandura (1997) defines self-efficacy as “beliefs in one’s own capabilities to
organize and execute the courses of action required to produce given attainment”

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(p.3). Self-efficacy is one clear indicator of a learner’s confidence in his/her ability to
carry out necessary actions in order to solve challenges and problems. Self-efficacy
can heavily influence a learner’s willingness to engage in a learning task, and the
amount of time and effort placed in solving a problem (Kinzie, Delcourt, & Powers,
1994; Schunk, 1995). Therefore, if a learner experiences a high level of confidence
because of progress achieved in solving a problem or challenge, the learner will
believe he/she is capable of having a high degree of success in solving similar
problems; which strengthens self-efficacy and reinvigorates learning (Schunk, 2001).
The relationship between the learning environment and self-efficacy is one
where one influences the other. In a study by Licht & Kistner (1986), a teacher’s
perception (the learning environment) of a disabled student’s low self-efficacy and
skills (self-efficacy) can prompt the teacher to provide easier tasks to accomplish.
This can lead to increased self-efficacy for the disabled student, because he/she can
now complete the task. As self-efficacy rises, the teacher’s perception of the disabled
student’s capabilities will change and task difficulty can become more challenging.
Learning vicariously through others is another example of the influence of the
learning environment on self-efficacy. Aside from a learner taking an active role in
the learning process, the learner can also enhance his/her learning by observing the
learning activities and consequences of others (Schunk, 2001). An example of this is
when a student realizes that preparing for college is important after noticing how older
siblings of peers have difficulty finding employment because they don’t have a college
education. Even though vicarious learning does have an impact on self-efficacy, it is
not as strong as active participation in a learning process.

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Expectations about learning outcomes are another important influence on self-
efficacy. If a learner feels efficacious enough about a particular learning task and is
confident in the positive result of the learning outcome, more effort will be placed on
the learning activity. More value is then placed on this learning activity, mastery is
built upon, and self-efficacy increases (Wigfield, 1994).
Self-efficacy and its influence on academic performance has been linked to the
strength of a student’s commitment and motivation for academic achievement (Schunk
& Miller, 2002). Across various disciplines with children and adolescents, research
has shown significant correlations between self-efficacy and academic achievement
(Lent, Brown, & Larkin, 1986; Pajares, 1996; Schunk, 1995). Specifically in high
school students, those who had high self-efficacy for problem-solving activities also
had higher academic persistence measures than students with low self-efficacy for
problem-soling (Bouffard-Bouchard, Parent, & Parivee, 1991).
In order to increase self-efficacy in the learning environment, students need to
be in an environment that allows them to feel a strengthening of task performance and
accomplishment. The implementation of such critical factors as learning goals,
learning-process goals, performance feedback, and performance modeling is needed in
a learning environment that strengthens self-efficacy. Problem-based learning shares
many of these attributes.
Challenges in Problem-Based Learning
Some research has shown that problem-based learning does not significantly
improve content-free problem-solving skills and may possibly reduce learning
(Norman and Schmidt, 1992). Literature on the cognitive benefits of problem-based

59

learning has demonstrated mixed findings (Hmelo, Gotterer, Bransford, 1994; Hsu,
1999). Studies on PBL effectiveness have also shown how PBL can sometimes be
less effective than traditional modes of instruction. One study’s results showed
medical students at PBL schools scoring lower on basic science exams and the
students viewing themselves as less prepared in the basic sciences as compared to
fellow students at traditional medical schools not employing PBL (Albanese and
Mitchell, 1993). Another study demonstrated how students learning through
traditional teaching methods scored higher on tests of medical knowledge as compared
to students learning through a PBL mode of instruction (Schmidt, Dauphinee, and
Patel, 1987). Some research also points to the problem-based learning curriculum not
guaranteeing true development of self-assessment skills (Langendyk, 2006).
Based on two important meta-analyses on the effectiveness of problem-based
learning (Albanese & Mitchell, 1993; Vernon & Blake, 1993), Bridges and Hallinger
(1997) concluded that seven out of 10 learning measures favored the problem-based
learning curriculum when compared to non-PBL curriculums. However, it has also
been reported that the PBL curriculum is not significantly different than traditional
modes of teaching and learning (Farrow and Norman, 2003).
Problem-based learning is a unique and innovative teaching method that
focuses on the question or problem being the driving force behind the learning
process. Because of its uniqueness and innovation, it carries along challenges when
compared to traditional models of teaching, learning, and assessment. As such,
alternative modes of assessment could provide a clearer understanding of how PBL
can be used as supplement for or replacement of traditional methods of learning and

60

teaching in different cases (Major & Palmer, 2001). To more accurately measure the
impact of alternative learning styles like the problem-based learning curriculum,
assessment tools should consider measuring the different variable involved in the
learning activity; attitudes, values, knowledge, and learning preferences (Evans,
Forney and Guido-Dibrito, 1998).
Discussion of Literature Review
This review of the literature has revealed psychological principles that support
the structure and purpose of problem-based learning. Building on the behavioral
psychology theories of connectionism, drive-reduction and drive-induction, cognitive
psychology theories provided a mental view of learning.
The cognitive approach of Vygotsky’s (1984) zone of proximal development
provided us with a perspective on how a learner is always capable of expanding
his/her learning. Reaching the edge of the zone of proximal development represents
the establishment of a new zone of actual development, only to start the growth
process again and reach towards a new zone of proximal development.
Supplementing this learner perspective is the tutor/facilitator perspective from the
concept of scaffolding from Wood, Bruner, and Ross (1978). By identifying what a
tutor/facilitator needs to do in order to be effective, we have an agent that can aid the
learning process by pulling the zone of proximal development. By paying attention to
the needs of the learner, establishing learning milestones, and being a mentor,
scaffolding becomes the symbiotic partner of the zone of proximal development.
Humanist theories provide a layer of meaning and philosophy to the purpose of
learning. Maslow’s hierarchy of needs offers us an understanding of how students

61

have an innate desire to realize their potential through the satisfaction of needs; from
biological to mental/spiritual. Problem-based learning provides learners with an
opportunity to reach their potential by working on challenges relative to their reality.
Complimenting this hierarchy of needs is Rogers and Frieberg’s (1994) view of the
teacher’s role in the learning process. The teacher focuses on giving the tools on how
to answer questions, rather than providing the answers. Like scaffolding to the zone
of proximal development, the humanist response is for a teacher to guide the learner
towards an opportunity to satisfy his/her need for self-esteem and self actualization.
Problem-based learning can lead to increased levels of motivation for learning.
With a positive and productive learning environment comes strength in self-efficacy
for the learner. I will investigate this dynamic in the application of PBL to college
preparation of ninth grade Latina/o and African American students. With the rising
numbers of Latina/o and African American students in the California K-12 pipeline,
but decreasing numbers in postsecondary enrollment, problem-based learning may be
another tool to use in the effort to reverse this trend. To turn the “Talented Tenth”
(Tierney, 2005, p.144) to access for all, students need to be empowered with tools that
will enable them to become their own best guidance counselor. Outreach programs
have provided the scaffolding for college preparation. Now problem-based learning
can expand the zone of proximal development for college preparation.

62

Chapter III
Methodology
In this chapter, I will discuss the details and logistics for how this PBL
quantitative/qualitative study was conducted. Information on the school setting,
experimental and control groups, and testing measures will be provided in this section.
Research Questions
1. Does a student’s self-efficacy towards college preparation increase
through participation in a college preparation program that utilizes a
pedagogical technique based on the principles of problem-based learning?
2. Does a student’s knowledge of college preparation increase as a result of
participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning?
3. Does a student’s motivation for preparing for college increase as result of
participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning?
Participants
Demographic data
This study was conducted in a large suburban public charter high school in the
Los Angeles area which we will refer to as High School X. The total number of ninth
through 12
th
grade students at this high school in the Fall of 2007 was 363, with 95%
of the student population being of Latino/Hispanic descent.
One-hundred fifty eight students are in the 9
th
grade class, followed by 50
students in the 10
th
grade, 63 in the 11
th
grade and 92 in the 12
th
grade. In the ninth

63

grade, 123 students (78% of the 9
th
grade class) are on the free- and reduced-lunch
program. For the remaining grades, thirty nine 10
th
grade students (78% of the 10
th

grade class), 52 11
th
grade students (83% of the 11
th
grade) and 73 12
th
grade students
(79% of the 12
th
grade) are on the free- and reduced-lunch program.
For English as a second language students (ESL), 23 9
th
graders (14% of the 9
th

grade class), seven 10
th
graders (14% of the 10
th
grade class), 12 11
th
graders (19% of
the 11
th
graders), and eight 12
th
graders (8% of the 12
th
graders) are considered ESL
students.
The parents of the students in High School X comprised the following
distribution educational levels.

Table 1. Educational Level Distribution of High School X Parents.

Assignment of subjects
Students were placed in one of three groups; an experimental group and two
control groups. Students in the experimental group were in the PBL college
preparation workshops for seven sessions. Student in the two other control groups
were not in the series of seven PBL workshops. Instead, control group students were
in one control group, labeled the College Center group, where they met with a

No High
School (HS)
HS
Graduate
Some
College
College
Graduate
Grad
School Declined
9th Grade Parents 42 parents 32 39 6 3 36
10th Grade Parents 10 parents 15 11 8 4 2
11th Grade Parents 11 parents 32 15 1 1 3
12th Grade Parents 15 parents 49 13 5 0 10

64

guidance counselor and used the school college center on an as needed basis during
the same six-week period as the PBL college preparation workshops. Students
assigned to the other control group, labeled the Outreach group, had seven workshops
on college preparation lead by an Outreach/Admissions officer from a local
postsecondary institution, also during the same six-week period as the PBL college
preparation workshops.
Eleven students were in each of the groups. The gender ratio within the
experimental group and the two control groups was 54% female to 46% male. The
students for all three groups were chosen from only the ninth grade at High School X.
Because these were ninth grade students, the age range for the students in each group
was approximately 12 to 13 years of age.
Grade point average, performance on placement exams, teacher evaluations, or
other criteria were not used in determining whether a student would participate in this
problem-based learning study. To reach the target group of at least 10 students in each
the experimental group and two control groups, the administration at High School X
and the founder of High School X were instrumental in beginning the promotion and
recruitment process for this study. Two meetings were held with these High School X
partners to plan the communication with the students and parents of all 9
th
graders at
High School X and encourage them to attend a meeting on High School X’s campus.
This meeting was open to all the parents and students from the 9
th
grade and was
conducted in both Spanish and English. One-hundred and fifty two students and their
parents, the entire 9
th
grade class of High School X were invited to this one meeting on
a weekday evening. A total of 33 students came to the meeting with both or one of

65

their parents. All the 9
th
grade students and parents who came to the meeting were
given the purpose of the study on a hardcopy handout, what the students would be
involved in terms of college preparation services, and assuring parents that no matter
whether their son or daughter was in the study or not, they would still receive the same
level of college preparation from High School X. Also, no matter which group the
student was assigned to in the experiment, experimental or control, we assured the
parents that all students in the experiment would receive some kind of college
preparation service. The Principal of High School X was also present in order to
answer any questions from the parents and students about such topics as the school’s
role in this study, what college preparation material and services are currently being
offered by the high school, and assurances that the parents would be notified of the
results of the study. After the question and answer session of this meeting was
finished, student consent and parental consent forms were passed out for those
students and parents who were interested in participating in the study. In the end, 33
students and their parents agreed to participate in the study. Within this 33, 18 were
female students and the remaining 15 were male students.
School District Setting for High School X
Over half of the enrolled K-12 California student population in 2005-2006 was
African American and Latina/o, 47.5% being Latina/o and 7.8% being African
American (California Department of Education [CDE], 2007). In the Los Angeles
Unified School District (LAUSD), 73.2% of enrolled K-12 students were Latina/o and
11.4% were African American (CDE, 2007). Add to these figures the current
California ratio of school/college counselors to high school students; one

66

school/college counselor for every 528 high school students in the state of California
(CDE, 2007); the American School Counselor Association recommends a ratio of one
counselor for every 250 (American School Counselor Association, n.d.)
LAUSD is comprised of 435 elementary schools, 74 middle schools, and 61
senior high schools. In addition to the magnet centers, continuation schools,
community day schools, special education schools, and all other K-12 entities, the
total number of K-12 school sites is 873. In addition to the other schools and centers
in LAUSD and the independent K-12 charter schools and centers – 96 in total – the
grand total for schools and centers in LAUSD is 1,155.
Enrollment data for LAUSD schools and centers are distributed across 10
different categories; elementary schools, (315,208 students), middle schools
(145,781), senior high schools (174,138), continuation schools (4,066), alternative
education and work centers (3,251), special education schools (3,982), SPAN schools
(23,771), community day schools (943), opportunity schools and centers (2,360) and
independent charter schools (34,961). Total student enrollment for LAUSD rests at
708,461 (Los Angeles Unified School District [LAUSD], 2007).
In terms of LAUSD district employees, there are 36,440 regular teachers in K-
12, adult and early education. There are 5,468 certificated staff support, which
includes school psychologists, nurses and counselors; total school district employees
is 77,377.
The high school chosen for this study is located in the northern-area of Los
Angeles County. The racial demographic of this specific area is 62.4%
Latino/Hispanic, 9.6% White, 20.3% African-American, .3% native American, 5.4%

67

Asian-American, .1% Pacific Islander, .1% not reporting, and 1.8% Bi-racial
(California State University, Northridge [CSUN], 2008). During the middle of 2008,
the average household income in this area was $65,818, the median total debts was
$194,335, average household net worth was $522,759, and the median home sale price
was $475,000 (CSUN 2008). The median incomes for the area surrounding High
School X are as follows:

Median Income Under 25 $47,297
Median Income 25-34 $55,575
Median Income 35-44 $58,454
Median Income 45-54 $67,921
Median Income 55-64 $61,380
Median Income 65-74 $54,192
Median Income Over 75 $49,112

Table 2. Median Incomes of Area Surrounding High School X.

High School X has 363 students from grades 9-12, with the freshmen class
being the largest at 158 students. The percentage of Latina/o and African American
students in High School X is 95% and 2% respectively. The main feeder into High
School X is a local charter middle school. This local charter middle school has first
priority in filling the open spaces for the incoming 9
th
grade class at High School X. If
the number of 9th grade spaces is fewer than the number of applicants coming from
the charter middle school, then a lottery is held for the open spaces. Those charter
middle school applicants who are left over after the spaces have been filled will
comprise the waiting list for the 9
th
grade class. If there are still 9
th
grade spaces

68

available, then a second lottery is held for interested applicants from the general
public.
In terms of staff personnel at High School X, the number of teachers at High
School X is 20 full-time teachers and two part-time. All the teachers are either fully
credentialed or are completing an internship/credential program. The average class
size in High School X is approximately 15 students to every one teacher. Two full-
time college counselors are employed to service the entire high school; an
approximate 1 to 184 ratio.
Instrumentation
This is a mixed methods three-group study combining qualitative and
quantitative measures. According to Gillis (2001), a journaling exercise can allow
students to explore their learning styles, reflecting on their abilities, and digest new
experiences as it relates to how the students’ learning is unfolding. Thus, a guided
journal assignment (See Appendixes A, B, and C) was used to gather qualitative data
on PBL’s influence on student knowledge, motivation and self-efficacy as it relates to
college preparation.
To triangulate the data from the guided journal assignments, the General Self-
Efficacy (GSE) Scale (Schwarzer & Jerusalem, 1995) (See Appendix D) and the
Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia, &
McKeachie, 1993) (See Appendix E) were used to gather quantitative data on the
effect of PBL on motivation and self-efficacy as it relates to college preparation.
The questions from the MSLQ will measure four different dimensions of
motivation. First, intrinsic goal orientation will measure the students’ perception of

69

themselves as being involved in a learning process because it peaks the curiosity and
represents a challenge. Students with an intrinsic goal orientation will interpret their
participation in the learning process as the reward, not what is gained from the
participation. The second dimension of motivation measured is task value, which
represents how important, interesting, and useful a learning process is to students. The
third is control of learning beliefs, which concerns a student’s belief that the positive
outcome from a learning process is dependent on the amount of effort he/she exerts in
the learning process. The fourth motivation dimension measured is self-efficacy for
learning and performance, which measures a student’s expectancy for success and
his/her self-efficacy in the learning process.
The MSLQ for this study was comprised of 21 questions. Questions 1, 9, 14,
and 16 measured Intrinsic Goal Orientation. Questions 3, 6, 10, 15, 18, and 19
measured Task Value. Questions 2, 5, 11, and 17 measured Control of Learning
Beliefs. Questions 4, 7, 8, 12, 13, 20, and 21 measured Self-Efficacy for learning and
Performance. The MSLQ scale has been shown to demonstrate internal consistencies
between robust Cronbach’s alpha scores ranging from .52 to .93 (Pintrich, Smith,
Garcia, and McKeachle, 1991)
The GSE for this study was comprised of 10 questions. Each of the these
questions measured Self-Efficacy, no sub-categories exist like in the MSLQ. The
GSE scale shows an internal consistency between Cronbach’s alpha scores of .75 and
.90 (Schwarzer, 1997). According to Schwarzer (1997, Method section, ¶1), “The
scale is not only parsimonious and reliable, it has also proven valid in terms of
convergent and discriminant validity. For example, it correlates positively with self-

70

esteem and optimism, and negatively with anxiety, depression and physical
symptoms”. Students answered the questions on the scale from the perspective of
preparing for college.
Procedure/Data Collection
Data was collected in the following manner. First, a thorough review of the
literature was conducted in order to build a foundation of the psychological theories
that support the process and outcomes of problem-based learning.
Second, the school administrators at High School X provided access to data
and resources in order to gather demographic data on the entire High School X
population. The high school’s access to the contact information of all 9
th
graders at
their school was used to reach the 33 students who agreed to participate in the study.
Using a numbering sequence of “1, 2, 3”, students were listed alphabetically and then
numbered with a “1”, “2”, or a “3” starting with the first student on the list. Students
assigned the number “1” were placed in the “College Center” control group. Students
assigned the number “2” were placed in the “Outreach Presentation” control group.
Students assigned the number “3” were placed in the “Problem-Based Learning”
experimental group.
Once the students were placed in their groups, they were not identified by
name on the recording instruments and were assigned a code unique to the student and
the group they were assigned to. Instead of using their names, the students would
write down these codes on the instruments used to collect data for the sake of privacy.
Students in the “College Center” control group were assigned alphabet letters (i.e., A,
B, C, etc.). The students in the “Outreach Presentation” control group were assigned

71

numbers (1, 2, 3, etc.). The students in the “PBL” group were assigned numbers
spelled in Spanish (Uno, Dos, Tres, etc.).
Experimental Group
The experimental group met with a PBL facilitator in each of the seven
sessions. Due to budgetary issues, the writer of this dissertation was trained to be a
certified problem-based learning facilitator in order to be the PBL facilitator for this
study.
From November 13, 2007 till December 5, 2007, the students met seven times
after school at 4pm in a classroom on their high school campus. The PBL workshop
lasted 50 minutes, from 4pm till 4:50pm. Before every meeting, the students had to
sign an attendance sheet to verify participation. In the first class meeting, the students
were introduced to the central challenge or question, what did they have to do as 9
th

graders to make sure they were competitive university applicants by the time they
reach the 12
th
grade? Once the PBL exercise ended after 50 minutes, the MSLQ and
GSE Scale were administered to the students. After these two quantitative scales were
completed, a guided journal exercise was distributed to the students for completion
before they left. The 50-minute workshop plus the completion of the three
instruments took approximately 72 to 80 minutes.
A time-series approach was used for the administration of the instruments.
Problem-based learning sessions one, four, and seven, ended with the administrations
of the MSLQ, GSE Scale and guided journal exercise, allowing for comparisons in
student knowledge, motivation and self-efficacy at three different points during the

72

PBL workshop series. The schedule for the PBL group between November 13, 2007
and December 5, 2007 was as follows:
• First workshop: Fifty minutes will be spent on PBL and 15-30 minutes will be
spent on completing three instruments after the presentation.
• Second workshop: PBL workshop, approximately 50 minutes.
• Third workshop: PBL workshop, approximately 50 minutes.
• Fourth workshop: Fifty minutes will be spent on PBL and 15-30 minutes will
be spent on completing three instruments after the presentation.
• Fifth workshop: PBL workshop, approximately 50 minutes.
• Sixth workshop: PBL workshop, approximately 50 minutes.
• Seventh workshop: Fifty minutes will be spent on PBL and 15-30 minutes will
be spent on completing three instruments after the presentation.
As an incentive to have students present during the first, fourth and seventh
workshops, free pizza was delivered after the 50 minutes of PBL, while they were
completing the data instruments.
College Center Control Group
The control group met with a guidance counselor three times during the
November 13, 2007 till December 5, 2007 period. The three meetings were spaced
out as evenly as possible and were used to answer any college preparation related
questions from the students by the high school counselor and to administer the MSLQ,
GSE Scale, and the guided journal exercise. The first meeting consisted of a 20-30
minute introduction by the guidance counselor to the resources of the college guidance

73

center at High School X. The second and third meetings consisted of the guidance
counselor being available to answer any college preparation questions and to
administer the three data instruments. Students were informed in the first meeting to
use the high school’s college guidance center on an as needed basis in answering their
college preparation questions. Like the PBL group, free pizza was used as an
incentive to have students present during the three meetings where the “College
Center” students were asked to come to the College Center, come with any questions
and then complete the three instruments. Attendance sheets were also administered
before each of the three sessions.
Outreach Group
The students in the Outreach Group had the same schedule as the PBL group,
meeting on the same days and times. An Admissions/Outreach counselor from a local
post-secondary institution was in charge of providing college preparation workshops
in each of the seven meetings.
From November 13, 2007 till December 5, 2007, the students met seven times
after school at 4pm in a classroom on their high school campus. The Outreach
workshop lasted 50 minutes, from 4pm till 4:50pm. Before every meeting, the
students had to also sign an attendance sheet to verify participation. In the first class
meeting, the students were introduced to a presentation on preparing for college. The
outreach representative in charge of these workshops was given free reign as to how
he wanted to organize the material in the seven workshops and what material to
present and how it is presented. Once these workshops ended after 50 minutes, the
MSLQ and GSE Scale were administered to the students. After these two quantitative

74

scales were completed, a guided journal exercise was distributed to the students for
completion before they left. The 50-minute workshop plus the completion of the three
instruments took approximately 72 to 80 minutes, just like the PBL group.
The same time-series approach was used for the administration of the
instruments. Problem-based learning sessions one, four, and seven, ended with the
administrations of the MSLQ, GSE Scale and guided journal exercise, allowing for
comparisons in student knowledge, motivation and self-efficacy at three different
points during the PBL workshop series. The schedule for the Outreach group was as
follows:
• First workshop: Fifty minutes will be spent on college preparation and 15-30
minutes will be spent on completing three instruments after the presentation.
• Second workshop: College preparation workshop, approximately 50 minutes.
• Third workshop: College preparation workshop, approximately 50 minutes.
• Fourth workshop: Fifty minutes will be spent on college preparation and 15-30
minutes will be spent on completing three instruments after the presentation.
• Fifth workshop: College preparation workshop, approximately 50 minutes.
• Sixth workshop: College preparation workshop, approximately 50 minutes.
• Seventh workshop: Fifty minutes will be spent on college preparation and 15-
30 minutes will be spent on completing three instruments after the
presentation.

75

The same incentive of free pizza for the students present during the first, fourth and
seventh workshops, was also used. The free pizza was delivered after the 50 minutes
of the college preparation information.
Data Analysis
Quantitative data analysis will consist of a test for abnormalities from pre- and
post- paired sample T-test results from administrations of the MSLQ and the GSE
Scale. Comparisons between the pre- and post- administration of both diagnostic
exams will be analyzed. Mann-Whitney test for independent samples will also be
used, alpha a priori significance level set at .05 for both the T-test and Mann-Whitney.
Frequency distribution of responses with descriptive statistics will be used to interpret
and discuss the data. The software, Statistical Package for the Social Sciences (SPSS),
will be used to analyze the data.
Qualitative data analysis will consist of having the data from the three guided
journal exercises transcribed onto a Microsoft Excel document within two weeks after
students complete a guided journal assignment. The qualitative method used to
analyze the data will be Grounded Theory. Comparisons between the experimental
and control groups, as well as between the first and last administrations, will be
analyzed for changes in college preparation knowledge.

76

Chapter IV
Findings
The focus of this study was to investigate if problem-based learning has any
influence on a 9th grade high school student's knowledge about college preparation,
motivation towards college preparation and self-confidence about college preparation.
The three research questions in Chapter III can be summed up in one question, does
problem-based learning increase a 9th grade student’s knowledge, motivation, and
self-confidence for preparing for college? The research questions for this study are:

1. Does a student’s self-efficacy towards college preparation increase
through participation in a college preparation program that utilizes a
pedagogical technique based on the principles of problem-based learning?
2. Does a student’s knowledge of college preparation increase as a result of
participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning?
3. Does a student’s motivation for preparing for college increase as result of
participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning?

The Statistical Package for the Social Sciences (SPSS) version 15.0 was used
to analyze the quantitative data gathered in the study. As will be summarized in the
following, participation in a PBL-based college preparation program PBL did

77

demonstrate differences but not significant changes in self-efficacy , knowledge, nor
motivation towards college preparation in High School X.
Descriptive Statistics for the Subjects
Ninety percent of the subjects were self-identified “Hispanic/Latino
American”, with the remaining 10% declining to answer. Fifty three percent of the
subjects were female and 46.7% were male. For the highest level of father’s
education, 60% of the subjects stated that high school was the highest level attained by
their father, 20% being elementary and middle school as the highest, 16.7% reaching
the Bachelor’s degree, and 3.3% having had no schooling. For the highest level of
mother’s education, 63.3% of the subjects stated that high school was the highest level
attained by their mother, 13.3% being elementary and middle school as the highest,
13.3% reaching the Bachelor’s degree, 6.7% reaching the graduate level, and 3.3%
having had no schooling.
For income level in their family, subjects identified their families as the
following:

Under $10,000 10%
Between $21,000 to $30,000 35%
Between $31,000 to $40,000 25%
Between $41,000 to $50,000 25%
Between $81,000 to $90,000 5%

Table 3. High School X Family/Subject Income Level

78

Research Question #1: The GSE Data
Does a student’s self-efficacy towards college preparation increase
through participation in a college preparation program that utilizes a pedagogical
technique based on the principles of problem-based learning? Analysis was done on
the first administration and the third administration of the GSE for the three groups
and then between the first and third administrations of the GSE within the College
Center, Outreach, and PBL groups.
Data from the first administration of GSE
Levene’s Test was conducted for each GSE question to test the assumption of
equality of variances between each of the three groups. The results are described in
the table below.

Levene
Statistic df1 df2 Sig.
GSE Question 1 0.231 2 28 0.795
GSE Question 2 1.277 2 28 0.295
GSE Question 3 4.302 2 28 0.023
GSE Question 4 2.229 2 28 0.126
GSE Question 5 0.267 2 28 0.768
GSE Question 6 2.581 2 28 0.094
GSE Question 7 1.392 2 28 0.265
GSE Question 8 3.722 2 28 0.037
GSE Question 9 0.243 2 28 0.786
GSE Question 10 0.419 2 28 0.662

Table 4. Levene Test Data on GSE Scale Questions from First Administration.

79

GSE question #3, “It is easy for me to stick to my aims and accomplish my
goals”, and GSE question #8, “When I am confused with a problem, I can usually find
several solutions”, demonstrated significant differences in variances between the three
groups. The probability level deemed significant was adjusted accordingly for this
variable.
A one-way Independent ANOVA was conducted for each GSE question to see
if there were differences in means between the College Center, Outreach, and PBL
group as they relate to each GSE question.

80

Sum of
Squares df
Mean
Squares F Sig.
GSE Question 1 Between Groups
Within Groups
Total
.191
13.809
14
2
28
30
.095
.493
0
.194
0
0
.825
0
0
GSE Question 2 Between Groups
Within Groups
Total
3.326
12.545
15.871
2
28
30
1.663
.448
0
3.711
0
0
.037
0
0
GSE Question 3 Between Groups
Within Groups
Total
2.075
11.409
13.484
2
28
30
1.037
.407
0
2.546
0
0
.096
0
0
GSE Question 4 Between Groups
Within Groups
Total
.484
19
19.484
2
28
30
.242
.679
0
.357
0
0
.703
0
0
GSE Question 5 Between Groups
Within Groups
Total
.435
21.436
21.871
2
28
30
.217
.766
0
.284
0
0
.755
0
0
GSE Question 6 Between Groups
Within Groups
Total
.838
22.582
23.419
2
28
30
.419
.806
0
.519
0
0
.601
0
0
GSE Question 7 Between Groups
Within Groups
Total
1.318
32.682
34
2
28
30
.659
1.167
0
.565
0
0
.575
0
0
GSE Question 8 Between Groups
Within Groups
Total
1.059
17.909
18.968
2
28
30
.529
.640
0
.828
0
0
.448
0
0
GSE Question 9 Between Groups
Within Groups
Total
.899
29.036
29.935
2
28
30
.450
1.037
0
.434
0
0
.653
0
0
GSE Question 10 Between Groups
Within Groups
Total
.483
12.936
13.419
2
28
30
.241
.462
0
.523
0
0
.599
0
0

Table 5. ANOVA Test Data on GSE Scale Questions from First Administration.

The College Center, Outreach and PBL groups displayed significant
differences in means with GSE question #2, “If someone opposes me, I can find the
means and ways to get what I want.”, F(2, 28) = 3.711, p < .05. The largest difference
between means existed between the PBL and Outreach groups (Dunnett T3 p = .009).

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Data from the third administration of GSE
A one-way Independent ANOVA was conducted for each GSE question to
uncover differences in means between the College Center, Outreach, and PBL groups
as they relate to each GSE question.

Sum of
Squares df
Mean
Squares F Sig.
GSE Question 1 Between Groups
Within Groups
Total
.889
8.075
8.964
2
25
27
.445
.323
0
1.377
0
0
.271
0
0
GSE Question 2 Between Groups
Within Groups
Total
4.939
9.775
14.714
2
25
27
2.470
.391
0
6.316
0
0
.006
0
0
GSE Question 3 Between Groups
Within Groups
Total
.579
6.100
6.679
2
25
27
.289
.244
0
1.186
0
0
.322
0
0
GSE Question 4 Between Groups
Within Groups
Total
.214
10.500
10.714
2
25
27
.107
.420
0
.255
0
0
.777
0
0
GSE Question 5 Between Groups
Within Groups
Total
2.375
8.875
11.250
2
25
27
1.188
.355
0
3.345
0
0
.052
0
0
GSE Question 6 Between Groups
Within Groups
Total
2.500
12.500
15.000
2
25
27
1.250
.500
0
2.500
0
0
.102
0
0
GSE Question 7 Between Groups
Within Groups
Total
.000
16.000
16.000
2
25
27
.000
.640
0
.000
0
0
1.000
0
0
GSE Question 8 Between Groups
Within Groups
Total
1.314
10.400
11.714
2
25
27
.657
.416
0
1.580
0
0
.226
0
0
GSE Question 9 Between Groups
Within Groups
Total
5.207
12.900
18.107
2
25
27
2.604
.516
0
5.046
0
0
.014
0
0
GSE Question 10 Between Groups
Within Groups
Total
.700
10.300
11.000
2
25
27
.350
.412
0
.850
0
0
.440
0
0

Table 6. ANOVA Test Data on GSE Scale Questions from Third Administration.

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The College Center, Outreach and PBL groups displayed significant
differences in means in GSE question #2, “If someone opposes me, I can find the
means and ways to get what I want.”, F(2, 25) = 6.316, p < .05, and question #9, “ If I
am in trouble, I can usually think of a solution, F(2, 25) = 5.046, p < .05. For question
#2, the largest difference of means existed between the PBL and College Center
groups (Scheffe p = .024). For question #9, the largest difference of means existed
between the Outreach and College Center groups (Scheffe p = .033).
Levene’s Test was again conducted for each GSE question to test the
assumption of equality of variances between each of the three groups in third
administration of the GSE. GSE question #3, “It is easy for me to stick to my aims
and accomplish my goals”, F(2, 25) = 4.520, p < .05, and GSE question #10, “I can
usually handle whatever comes my way”, F(2, 25) = 4.277, p < .05, demonstrated
significant differences in variances between the three groups. However, like the post
hoc results from the first administration of the GSE, Dunnett’s did not reveal any
significant variances between any two groups in each of questions #3 and #10.
Analysis for differences in self-efficacy between first and third administration of the
GSE.
Mean differences in all GSE questions did not display significant differences
for the College Center group between the first and third administrations of the GSE
scale. However, there was a difference in means with the Outreach group scoring
higher between first and third administrations in question #1, “I can always manage to
solve difficult problems if I try hard enough.”, (M = 3.7, SD = .483), t(19) = -2.629, p

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= .017. The PBL Group also demonstrated a difference in mean scores but this time in
question #2, (M = 3.8750, SD = .35355), t(15.705) = -2.310, p = .035.
Research Question #2: Journaling and Grounded Theory
Does a student’s knowledge of college preparation increase as a result of
participation in a college preparation program that utilizes a pedagogical technique
based on the principles of problem-based learning? The guided journal findings were
analyzed using Grounded Theory, a method of qualitative analysis that develops a
study-centered theory that is based on data systematically gathered and analyzed
(Glaser & Strauss, 1967; Strauss and Corbin 1994). The journal excerpts in this
section are samples of the student responses in the guided journal assignments. To
ensure the authenticity and voice of the participant, no grammatical corrections were
made to the responses presented here.
Open Coding
The first step in Grounded Theory is open coding, where data is first
conceptualized and categorized through labeling individual concepts and themes
arising from the journal entries. The journal entries from the PBL, Outreach, and
College Center groups were placed in separate Excel database sheets. For each group,
the Excel sheet would assign one row of data to each participant in that group. The
participant for each row is identified by using the same code name assigned to each
participant in each group during the study. For the PBL group, numbers one through
11 in Spanish were the codes used for its 11 participants. Each number was assigned a
row to accommodate the data for that one participant. Each column in the Excel sheet
would contain a question from the guided journal assignment, thus there were 19

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columns comprised of the six questions from the first journal assignment (Session 1),
seven questions from the second journal assignment (Session 2), and the final six
questions from the third journal assignment (Session 3). Student responses would be
placed in the empty cell intersecting the student-row and the question-column. Data
was then read longitudinally from left to right, thus reading and analyzing student
responses from the first journal entries first, the second journal entries second, and the
third journal entries third. A sample of the Excel database sheet is provided below.

SESSION 1 SESSION 1
Code Name
How do you currently feel
about your ability to prepare
for college admissions?
How well do you think you would do if you
started preparing for college today? What skills
and knowledge do you have to help you prepare
for college? What skills and knowledge do you
feel you still need to prepare for college?
UNO
I feel good its preparing me for
college and what Im up against
I would do pretty good. I know what kind of grades
I would need what kind of stuff I'm going
DOS
I think I'll do good Not so good
TRES
Good because I can get to
understand what is needed to go
to college
I think I'd do good. To learn as much as I can have.
The needs to go to college

Table 7. Sample of Guided Journal Response Analysis.

For the Outreach group, numbers one through 11 in English were the codes
used for its 11 participants. Finally, for the College Center group, letters “A” through
“K” were the codes used for its 11 participants. The data for both of these groups
were organized in the same manner as the PBL group.

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From the open coding process, four main themes or clusters – as they relate to
college preparation - were identified; support/influence, knowledge, confidence and
comfort. The support/influence cluster incorporates statements from the subjects
relating to comments concerning any type of support the students felt or had towards
preparing for college. As an example of the support/influence cluster, when asked
“What has influenced your ability (positively or negatively) to prepare for college?”,
one PBL participant response was “Positive, my brother goes.” Another response
from a PBL participant was “What influenced me was my family and money.” From
the College Center group, one participant responded to the same question with
“Something that has influenced me positive to prepare for college has been that my
brother graduated. Something influencing me negatively is the way some people
judge me for wanting to attend college.” From the Outreach group, one participant
responded with “My older sister and my cousins. They have positively influenced me
to prepare for college. The fact that they are all successful and still working hard. My
sister is a senior and now getting close to going.”
The knowledge cluster embodies statements from the subjects relating to what
they know about how to prepare for college. As an example of this cluster, when
asked “How well do you think you would do if you started preparing for college
today? What skills and knowledge do you have to help you prepare for college?
What skills and knowledge do you feel you still need to prepare for college?”, one
PBL participant response was “I would do pretty good. I know what kind of grades I
would need what kind of stuff I am going.” Another PBL response was “I think I
would do really well. The things we have to do for example the A-G requirements,

86

the GPA & scholarships and financial aid.” From the College Center group, one
response to the same question was “I don't really know much but researching what I
need will really help. I know that a lot of money is involved. I need to figure out
what classes I really want to take.” From the Outreach group, a subject responded to
the question with “If I started preparing for college today I don’t think I would do so
well because I feel extremely overwhelmed. The skills and knowledge I have is
patience and positive attitude. The skills I need is to know how to manage my time
wisely.” Another response from the Outreach group was, “I think I would do OK if I
prepared today. I do very well in English, History and Science.”
The confidence cluster is the category of statements relating to a subject’s
confidence as it relates to preparing for college. When asked “Are you confident you
can do all that is required to became a college applicant? Why or why not?”, one of
the PBL subjects responded with “Yes, because I've been passing my classes.”
Another PBL subject response was “Yes I'm confident w/the requirements.” From the
College Center group, one subject responded to the same question with “No I'm not
confident that I can do all that is required to become a college applicant because I feel
that I'm not ready to go to college yet.” Another subject from the College Center
group responded with “I am very confident because anyone can achieve whatever the
aim for.” From the Outreach group, one student responded with “I am confident that I
can accomplish all that is required. This is because my mind is set and it’s not too
hard to work towards a goal if you want it enough.”

87

The comfort cluster represents responses from subjects that provide insight
into what the student’s feel about their feelings and comfort towards their competence
in preparing for college.
Axial Coding
The second step in Grounded Theory is axial coding, where the clusters in the
open coding stage are analyzed to identify a central phenomenon or model established
through causal relationships between the clusters (i.e., interplay between the clusters
that influence the phenomenon). The goal is to make connections between the clusters
and explain the relationships. The model identified during this axial coding stage is
the following.

Figure 3. Relationship Between College Preparation Clusters.

Support/Influence
Confidence
Knowledge
Comfort

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The data revealed different sources of support and influence as it relates to
college preparation. From the College Center group, when asked “What has
influenced your ability (positively or negatively) to prepare for college?”, some of the
responses to this question that pointed to these support systems were, “My older sister
and my cousins. They have positively influenced me to prepare for college. The fact
that they are all successful and still working hard. My sister is a senior and now
getting close to going.”, “My family and my older cousin have influenced me
positively.”, and “Something that has influenced me to prepare for college is my sister
Jazmin because she says that if she could do it so could I. Also all my family has told
me to think big and that is what I am doing.” From the Outreach group, some of the
support/influence statements from the same question were, “My family and my older
cousin have influenced me positively.” and “School and teachers.” From the PBL
group, relevant statements included, “Positive, my brother goes.”, “What influenced
me was my family and money.” and “My parents because they want me to go to
college in my family.” The sources of support and influence evident from these
statements are parents, siblings, extended family, and school personnel. Each of these
sources of support and influence made an impact in the subject’s confidence,
knowledge, and comfort towards preparing for college.
Selective coding
The third and final step in Grounded Theory is selective coding, which builds
upon the foundation created by the open and axial coding. This stage in the analysis is
where the central theme or category is chosen in order to validate the relationship and
partnerships between the clusters. The central theme for the relationship between the

89

clusters was the presence of “college preparation awareness”; an awareness of various
pieces of knowledge necessary for the participant to actively and successfully start and
continue a process leading to eligibility in the college admissions process.
College preparation knowledge data list
Separate from the grounded theory process, analysis was conducted on the
number of college preparation related steps, processes, tasks that were mentioned by
each of the three groups in the first administration and second administration of the
guided journal assignments. In the first administration of the guided journal
assignments, all terminology related to college preparation were written down from
each of the participant responses in each group. Most of the original words used in the
responses were listed in the analysis, with the exception of three common themes.
“Family support” encompassed all terms from journal responses that mentioned
“father”, “brother”, “cousin”, and other family related terms indicating receiving or
not receiving support from them. “School support” was the label used for words from
the journal entries that mentioned terms such as “teacher”, “counselor” and other
school related titles that may have provided college preparation support. Lastly,
“Financial Aid” embodied such words from the journal responses as “scholarships”,
“loans” and other financial aid options. The table below lists the college preparation
related terms from the first administration responses within each group.

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First Guided Journal Administration Data
Outreach College Center PBL
1. Tuition 1. Sports 1. Sports
2. Academic
Subjects
2. Academic
Subjects
2. Academic
Subjects
3. Activities
3. Academic
Progress
3. A-G
Requirements
4. Volunteer
4. Standardized
Testing
4. Community
Service
5. Study Skills 5. Financial Aid 5. Financial Aid
6. Family Support 6. College Courses 6. Leadership
7. School Support 7. GPA 7. GPA
8. Family Support
8. Problem-
Solving
9. School Support 9. Activities

10. Family
Support

11. School
Support

Table 8. College Preparation Terminology from First Journal Administration.

College preparation terminology from the third administration of the guided
journals were also analyzed for any words that were different from words used in the
first administration. These results are listed in the next table.

Third Guided Journal Administration Data
Outreach College Center PBL
College Courses Legal Status College Application
Grades Internet

How to register for
college

Table 9. College Preparation Terminology from Third Journal Administration.

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The number of college preparation knowledge terms written by the Outreach
participants numbered nine. The number of college preparation knowledge terms
written by the College Center participants numbered 10. For the PBL group,
participant responses of college preparation knowledge terms numbered 14.
Research Question #3: The MSLQ Data
Does a student’s motivation for preparing for college increase as result of
participation in a college preparation program that utilizes a pedagogical technique
based on the principles of problem-based learning?
In total, 18 girls and 15 boys participated in the study. Boys in the study (M =
21.7, SD = 3.58) tended to have higher mean scores than the girls (M = 21.62, SD =
3.86) in Intrinsic Goal Orientation. In Task Value, boys (M = 36.02, SD = 4.26) again
scored higher than girls (M = 35.5, SD = 5.50). In Control of Learning Beliefs, boys
(M = 23.75, SD = 2.69) scored higher than girls (M = 21.23, SD = 4.37). In Self-
Efficacy for Learning and Performance, boys (M = 41.26, SD = 4.95) again scored
higher than girls (M = 40.19, SD = 6.20).
To address the third research question, we will revisit each of the four MSLQ
dimensions used for this study and how the College Center Group, the Outreach
Group, and the PBL Group compared to each other in each dimension. A One-way
Independent ANOVA was conducted for the first administration of the MSLQ.
Data from the first administration of MSLQ
A one-way Independent ANOVA was conducted for each of the four MSLQ
dimensions to see if there were differences in each of the group’s means as they relate
to each MSLQ dimension from the first administration.

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Sum of
Squares df
Mean
Squares F Sig.
Intrinsic Goal Orientation Between Groups
Within Groups
Total
80.958
358.909
439.867
2
27
29
40.479
13.293
0
3.045
0
0
.064
0
0
Task Value Between Groups
Within Groups
Total
225.521
421.445
646.967
2
27
29
112.761
15.609
0
7.224
0
0
.003
0
0
Control of Learning Beliefs Between Groups
Within Groups
Total
60.018
428.282
488.300
2
27
29
30.009
15.862
0
1.892
0
0
.170
0
0
Self Efficacy for Learning Between Groups
and Performance Within Groups
Total
137.200
809.600
946.800
2
27
29
68.600
29.985
0
2.288
0
0
.121
0
0

Table 10. ANOVA Test Data on MSLQ Scale Question from First Administration.

For the domains of Intrinsic Goal Orientation, F(2, 27) = 3.045, p > .05,
Control of Learning Beliefs, F(2, 27) = 1.892, p > .05, and Self-Efficacy for Learning
and Performance, F(2, 27) = 2.288, p > .05, the PBL, Outreach or College Center
approaches did not display any significant differences in their means. However, in
Task Value, F(2, 27) = 1.892, p < .05, the PBL, Outreach and College Center
approaches did display significant differences in their means. The largest difference
between means existed between the PBL and Outreach groups (Dunnett T3 p = .001).
Task Value, again, represents how important, interesting, and useful a learning process
is to students. The questions asked to measure Task Value were:
Question 3. I think I will be able to use what I learn in this course in other courses.
Question 6. It is important for me to learn the course material in this class.

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Question 10. I am very interested in the content area of this course.
Question 15. I think the course material in this class is useful for me to learn.
Question 18. I like the subject matter of this course.
Question 19. Understanding the subject matter of this course is very important to me.
Data from the third administration of MSLQ
A second one-way Independent ANOVA was conducted for each dimension to
see if there were differences in each of the group’s means as they relate to each MSLQ
dimension from the third administration of the MSLQ survey.

Sum of
Squares df
Mean
Squares F Sig.
Intrinsic Goal Orientation Between Groups
Within Groups
Total
22.006
244.957
266.963
2
24
26
11.003
10.207
0
1.078
0
0
.356
0
0
Task Value Between Groups
Within Groups
Total
100.654
600.775
701.429
2
25
27
50.327
24.031
0
2.094
0
0
.144
0
0
Control of Learning Beliefs Between Groups
Within Groups
Total
9.879
442.800
452.679
2
25
27
4.939
17.712
0
.279
0
0
.759
0
0
Self Efficacy for Learning Between Groups
and Performance Within Groups
Total
136.704
447.814
584.519
2
24
26
68.352
18.659
0
3.663
0
0
.041
0
0

Table 11. ANOVA Test Data on MSLQ Scale Question from Third Administration.

For the domains of Intrinsic Goal Orientation, F(2, 24) = 1.078, p > .05, Task
Value, F(2, 25) = 2.094, p > .05, and Control of Learning Beliefs, F(2, 25) = .279, p >

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.05, the PBL, Outreach or College Center approaches did not display any significant
differences in their means. However, in Self-Efficacy for Learning and Performance,
F(2, 24) = 3.663, p < .05, the PBL, Outreach and College Center approaches did
display significant differences in their means. The largest difference between means
existed between the PBL and College Center groups (Scheffe p = .07). Self-Efficacy
for Learning and Performance measures a student’s expectancy for success and
his/her self-efficacy in the learning process. The questions asked to measure Self-
Efficacy for Learning and Performance were:
Question 4. I’m certain I can understand the most difficult material presented in the
readings for this course..
Question 7. I’m confident I can understand the basic concepts taught in this course.
Question 8. I’m confident I can understand the most complex material presented by
the instructor in this course.
Question 12. I’m confident I can do an excellent job on the assignments and tests in
this course.
Question 13. I expect to well in this course.
Question 20. I’m certain I can master the skills being taught in this class.
Question 21. Considering the difficulty of this course, the teacher, and my skills, I
think I will do well in this class.
Analysis for dimension differences between first and third administration of the MSLQ
Equal variances were found within Intrinsic Goal Orientation, F(17, 14.827) =
1.155, p > .05, Task Value, F(17, 16.834) = .894, p > .05, Control of Learning Beliefs,
F(17, 13.190) = 1.363, p > .05, and Self-Efficacy for Learning and Performance, F(17,

95

16.799) = .077, p > .05, between the first and third MSLQ administrations for the
College Center group.
For the Outreach Group, Intrinsic Goal Orientation, F(19, 18.993) = .344, p >
.05, Task Value, F(19, 14.928) = 2.290, p > .05, Control of Learning Beliefs, F(19,
18.531) = .281, p > .05, and Self-Efficacy for Learning and Performance, F(19,
18.402) = .006, p > .05, demonstrated equal variances between the first and third
administrations. However, the mean number for the respondents in Self-Efficacy for
Learning and Performance in the third administration of the MSLQ was higher, (M =
44.8, SD = 3.39) than the same respondents in the first administration for same “self-
efficacy” dimension, (M = 41, SD = 3.13), t(19) = -2.670, p = .015.
The PBL Group also demonstrated equal variances in Intrinsic Goal
Orientation, F(19, 18.993) = .344, p > .05, Task Value, F(19, 14.928) = 2.290, p > .05,
Control of Learning Beliefs, F(19, 18.531) = .281, p > .05, and Self-Efficacy for
Learning and Performance, F(19, 18.402) = .006, p > .05, between the first and third
administrations of the MSLQ. However, the mean number for the respondents in
Intrinsic Goal Orientation, (M = 23.85, SD = 3.18), in the third administration of the
MSLQ was higher than the same respondents from the first administration in the same
domain, (M = 19, SD = 3.12), t(15) = -3.129, p = .007. The mean number for the
respondents in Task Value, (M = 38.62, SD = 2.44), in the third administration of the
MSLQ was higher than the same respondents from the first administration in the same
domain, (M = 32.1, SD = 3.57), t(16) = -4.395, p = .000. Also, the mean number for
the respondents in Self-Efficacy for Learning and Performance, (M = 45.57, SD =
2.14), in the third administration of the MSLQ was higher than the same respondents

96

from the first administration in the same domain, (M = 36.2, SD = 6.92), t(15) = -
3.437, p = .004.
Group Means among the four dimensions.
The PBL group responses were higher for Intrinsic Goal Orientation, (M =
23.85, SD = 3.18), Task Value, (M = 38.62, SD = 2.44), Control of Learning Beliefs,
(M = 23.75, SD = 4.09), and Self-Efficacy for Learning and Performance, (M = 45.57,
SD = 2.14), as compared to the College Center and Outreach groups. The PBL
differed most with the College Center group in all four dimensions, (M = 21.8, SD =
3.61), (M = 34.6, SD = 6.88), (M = 22.6, SD = 5.23), (M = 40.5, SD = 5.93)
respectively.

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Chapter V
Results
The intent of this study was to investigate whether problem-based learning
influenced 9
th
grader students in their self-efficacy, motivation, and knowledge
towards college preparation differently than an outreach-based or college center access
approach. Student responses on the General Self-Efficacy (GSE) Scale (Schwarzer &
Jerusalem, 1995) (See Appendix D), Motivated Strategies for Learning Questionnaire
(MSLQ) (See Appendix E), and a guided journal exercise were used to answer the
questions that formed the foundation of this study. Students who participated in this
study were members of the 9
th
grade class, class of 2011, from a high school in the
Los Angeles area. Ninety percent of the subjects were self-identified
“Hispanic/Latino American” and 10% declining to state their ethnicity. Fifty three
percent of the study subjects were female and 46.7% were male.
The high school in this study is referred to as High School X. Thirty three 9
th

grade students agreed to participate in the study. Using a numbering and alphabetized
sequence, 11 students were placed in each of the College Center and Outreach
Presentation control groups and in the Problem-Based Learning experimental group.
The PBL group met for seven workshops lasting 50 minutes each and longer
on three workshop dates when they had to take the diagnostic tests. The focus of the
PBL group was to introduced them to the central challenge or question, what did they
have to do as 9
th
graders to make sure they were competitive university applicants by
the time they reach the 12
th
grade? The Outreach group had the same schedule as the
PBL group, meeting on the same afternoon days and times. An Admissions/Outreach

98

counselor from a local post-secondary institution was in charge of providing college
preparation workshops in each of the seven meetings. The College Center group met
with a guidance counselor three times during the same duration as the PBL and
Outreach group. The three meetings were used to have the school counselor answer
the college preparation related questions from the students and to administer the
diagnostic tests.
Study participant involvement in this study was consistent. Of the 11 students
placed in each of the three study groups, one participant from the PBL group and two
from the Outreach group did not complete the first round of diagnostic tests. For the
second round of diagnostics tests, one from the College Center group, one from the
PBL group and three from the Outreach group did not complete the tests. For the final
round of diagnostics tests, one from the College Center group, three from the PBL
group and one from the Outreach group did not complete the tests.
In the subsequent sections; the research questions and results are presented and
discussed; a summary of findings is presented; implications of this study’s findings are
discussed; and recommendations for future research are provided.
Discussion of Research Question #1: Does a student’s self-efficacy towards college
preparation increase through participation in the problem-based learning
environment?
Student responses from the College Center, Outreach and PBL groups on the
GSE scale were analyzed to measure changes of self-efficacy as it relates to college
preparation within each of the groups.

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Measuring Self-Efficacy in the beginning of the study. Based on an analysis of
the first administration of the GSE, the three groups differed significantly in their
responses to GSE question #3, “It is easy for me to stick to my aims and accomplish
my goals”, and GSE question #8, “When I am confused with a problem, I can usually
find several solutions”. More specifically, The College Center, Outreach and PBL
groups displayed the most difference among themselves in GSE question #2, “If
someone opposes me, I can find the means and ways to get what I want.” The largest
difference between two groups in this question was between the PBL and Outreach
groups.
Measuring Self-Efficacy at the end of the study. Further analysis was
conducted on the third administration of the GSE. This analysis demonstrated the
three groups differing in their responses on GSE question #3, “It is easy for me to stick
to my aims and accomplish my goals”, and GSE question #10, “I can usually handle
whatever comes my way”. Further analysis demonstrated the three groups differing
the most on GSE question #2, “If someone opposes me, I can find the means and ways
to get what I want.”, and question #9, “ If I am in trouble, I can usually think of a
solution.” The largest difference between two groups in question #2 existed between
the PBL and College Center groups. For question #9, the largest difference was
between the Outreach and College Center groups.
Pre and post measures of self-efficacy within each group. Specifically within
the College Center group, there was no difference between the variances or the means
between the first and third administrations of the GSE. The Outreach group did
demonstrate a difference in means with their participants scoring higher between first

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and third administrations in question #1, “I can always manage to solve difficult
problems if I try hard enough.” The PBL Group participant data presented the only
time where one of the groups differed in variances between the first and third
administrations of the GSE, evident in question #2. The PBL group also demonstrated
a difference of means in question #2 between first and third administrations.
What these results indicate is that the PBL and Outreach methods may be more
effective in increasing self-efficacy towards college preparation than college center
services only. PBL was just as effective as a university outreach presentation in
positively influencing self-efficacy as it relates to college preparation.
The implications for these findings point to PBL’s viability for being used as a
method of college preparation. A college counselor may not have the time to lead a
College-Prep PBL (CP-PBL)group, but interested high school students in the 11
th
or
12
th
grade can play a role in leading these CP-PBL sessions. Not only will the older
high school students have an opportunity to mentor your younger high school students
but also will have opportunities to demonstrate their leadership and volunteer
commitment; two qualities that are highly sought after in competitive university
admissions processes. The older high school students would of course have to be
supervised by the high school college counselor, but this is time well spent as more
college –prep peer-mentor relationships are created. In the end, the high school
college counselor receives some needed assistance in college preparation and the high
school PBL mentors have an opportunity to demonstrate their leadership and volunteer
skills.

101

Discussion of Research Question #2: Does a student’s knowledge of college
preparation increase as a result of participation in a problem-based learning
environment?
Student responses from the College Center, Outreach and PBL groups on the
guided journal exercises were analyzed to measure changes in student knowledge as it
relates to college preparation within each of the groups.
Using Grounded Theory, the open coding process revealed five main themes of
data as they relate to college preparation; support/influence, knowledge, confidence
and comfort. The axial coding process revealed the causal and contextual
relationships between these five themes. The support/influence theme seemed to
influence the knowledge, confidence, and comfort themes in increasing degree from
the beginning of the study to the end of the study. Because of the increased support of
college preparation knowledge from the College Center, Outreach and PBL
approaches, there were varying degrees of this increase. However the two groups
demonstrating a greater observable increase in knowledge and clarity in college
preparation were the College Center group and PBL group. The final stage of
selective coding identified the central category for the themes and relationship
between them as an awareness of how to prepare for college; a kind of awareness
necessary to assist the participant in becoming an eligible four-year university
applicant.
A separate quantitative analysis was conducted to measure college preparation
knowledge within each of the groups. Terms such “financial aid”, “grades”,
“leadership”, “A-G requirements”, “tuition” and other college prep related items were

102

counted in the first administration of the guided journal and then compared and added
to the terminology count in the third administration. All groups demonstrated
evidence of college preparation knowledge through the words used in the journal
responses, but the PBL contained the highest number of words related to college
preparation. Interestingly, the PBL group contained the only reference to problem-
solving in college preparation.
What these results indicate is the PBL, College Center and Outreach groups
shared similar characteristics in how varied levels of college preparation support can
influence a student’s confidence, comfort and knowledge towards college preparation.
College Preparation Awareness was evident in all three groups in the study.
In terms of college preparation knowledge, participants in the PBL group
tended to mention and talk more about various terms related to college preparation.
As stated earlier, the PBL group was the only group where more than one student
mentioned problem-solving in the same context as college preparation.
The implication for these findings rest, once again, in the application of PBL in
the secondary school setting. PBL proved to be just as effective as the College Center
group and Outreach group in strengthening college preparation knowledge. Especially
among first-generation students, PBL demonstrated how it can be a useful tool in
solidifying or increasing a student’s knowledge of college preparation.
Discussion of Research Question #3: Does a student’s motivation for preparing for
college increase as result of participation in a problem-based learning environment?
Measuring motivation in the beginning of the study. In the first administration
of the MSLQ, the PBL, Outreach or College Center groups did not display significant

103

differences within the domains of Intrinsic Goal Orientation, Control of Learning
Beliefs, and Self-Efficacy for Learning and Performance. However, the PBL,
Outreach and College Center groups did display significant differences in variance in
the domain of Task Value. Within this domain, the largest difference existed between
the PBL and Outreach groups.
ANOVA analysis presented the same trend in the College Center, Outreach
and PBL groups displaying no significant differences between themselves in the
domains of Intrinsic Goal Orientation, Control of Learning Beliefs, and Self-Efficacy
for Learning and Performance. Once again, the three groups displayed significant
differences in means in the domain of Task Value, with the largest difference being
between the PBL and Outreach groups.
Measuring motivation at the end of the study. In the third administration of the
MSLQ, the PBL, Outreach or College Center groups did not display significant
differences within the domains of Intrinsic Goal Orientation and Control of Learning
Beliefs. Self-Efficacy for Learning and Performance and Task Value data from the
PBL, Outreach and College Center groups did display significant differences in their
variances. However, additional post hoc analysis showed no significant differences
between the Outreach, College Center and PBL group motivation results.
ANOVA analysis showed PBL, Outreach or College Center groups
demonstrating no significant differences in their means within the domains of Intrinsic
Goal Orientation, Task Value, and Control of Learning Beliefs. However, the three
groups did display significant differences in Self-Efficacy for Learning and
Performance, with the largest difference between the PBL and College Center groups.

104

Differences in dimension scores between first and third administration of the
MSLQ. The College Center group responses between the first and third
administrations of the MSLQ showed no differences in variances or means in Intrinsic
Goal Orientation, Task Value, Control of Learning Beliefs, nor Self-Efficacy for
Learning and Performance.
The Outreach Group data showed no variance differences in Intrinsic Goal
Orientation, Task Value, Control of Learning Beliefs, and Self-Efficacy for Learning
and Performance between the first and third administrations. However, the Outreach
group did show an increase in mean differences from the first to the third
administration of the MSLQ in the domain of Self-Efficacy for Learning and
Performance.
The PBL Group data also demonstrated equal variances in Intrinsic Goal
Orientation, Task Value, Control of Learning Beliefs, and Self-Efficacy for Learning
and Performance, between the first and third administrations of the MSLQ. However,
the PBL group did show a difference in means within Intrinsic Goal Orientation, Task
Value, and Self-Efficacy for Learning and Performance, with the third administration
of the MSLQ being higher than the first administration. PBL showed a greater
increase in overall motivation as compared to the College Center and Outreach groups.
Group Means among the four dimensions.
The PBL group mean scores were higher in all dimensions of motivation -
Intrinsic Goal Orientation, Task Value, Control of Learning Beliefs, and Self-Efficacy
for Learning and Performance - , as compared to the College Center and Outreach
group mean scores. The PBL mean scores differed most with the College Center

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group in all four dimensions, with the Outreach group being second to the PBL in all
domains of motivation.
These results indicate that PBL was more effective than the outreach
presentation and the college center services in motivating students about preparing for
college. Much like the self-efficacy results, the implications for PBL in the college
preparation of secondary school students are in the many ways PBL can be applied
towards delivering college preparation services. Whether it is as a mentoring tool, a
leadership opportunity for students, a community service opportunity, or professional
development for the high school counselor, the possibilities are many.
Between the qualitative and quantitative data, one trend that became evident
was the overall positive influence PBL had in the motivation, self-efficacy and
knowledge towards college preparation among the 9
th
grade participants. A positive
influence that seemed slightly stronger than college preparation delivered through a
university outreach presentation or access to a college center.
Discussion
Research indicates that adult students and low-income, first-generation
college-going students tend to choose a postsecondary institution during the same time
they have to choose a postsecondary option or when they are returning to school
(National Postsecondary Education Cooperative (NPEC), 2007). Primarily based on
qualitative information, research indicates that an individual’s predisposition towards
postsecondary options is determined by personal preferences influenced by familial,
cultural and environmental factors (Bers and Galowich, 2002; Butner et. al., 2001; De
La Rosa, 2006; Hossler, Schmidt and Vesper, 1999; McDonough, 1997). Therefore,

106

students who are exposed early to college or postsecondary information from their
surroundings will also seek out information earlier for the college decision making
process. Without the familial, cultural and environmental influences, students will not
actively search out this postsecondary information.
Once students enter high school, they become increasingly aware of how they
compare to others on racial, religious, gender and academic criteria. Specifically with
the academic criteria, a student’s academic identity becomes a significant part of how
a student views him or herself in the school setting and becomes a central influence on
the student’s academic performance and motivation to achieve (Welch and Hodges,
1997). Interestingly, the motivation behind the academic identity is enhanced when a
student becomes aware of the relevance and importance of the academic information
to their current situation. Thus, a student’s academic identity is more likely to be
active and heightened during the junior and senior years of high school when the
transition from high school to postsecondary or occupational options comes closer. A
student’s academic identity during the middle school or 9
th
and 10
th
grade years would
still exist, but overall not at the heightened level of a student nearing high school
graduation.
Hossler’s Three-Stage Model of College Choice
The current body of literature on how and when college preparation related
information is sought, retrieved and acted upon by students who are preparing for
postsecondary options relies very heavily on the three-stage model of college choice
designed by Hossler (Hossler and Gallagher, 1987; Hossler, Schmidt and Vesper,
1999).

107

The first stage of Hossler’s three-stage model of college choice is the
Predisposition stage. Here, the student starts self reflecting on the idea of attending
college. This stage culminates in the student’s decision to attend college. Individual
and environmental factors such as exposure to university environments, parental
support, positive academic influences, sibling role models, college-prep related peer
pressure, education-attainment level of parents all have the strongest influence in a
student’s desire to move forward in the college preparation process. In fact, the
parent’s education-attainment level, parental support and student achievement are
variables recognized as the strongest predictors of a student’s college aspirations and
future enrollment in a postsecondary institution (Bers and Galowich, 2002; Hossler,
Schmidt, and Vesper, 1999).
In the Search stage, the students actively searched for and retrieved both
general information on preparing for postsecondary option and specific information on
particular postsecondary institutions. After analyzing the information, this stage ends
with the student choosing a select group of postsecondary options. The individual and
environmental factors still play a role in this stage but succumb to the postsecondary
institutions themselves as their information becomes less abstract and more tangible
through campus tours and interactions representatives.
The Choice stage, the final stage in Hossler’s three-stage model of college
choice, is characterized by the student and his or her family structure analyzing the
information and deciding whether a postsecondary institution is viable, which
institutions to consider and which institution provides the best match to a student’s
interest.

108

How does this three-stage model relate to first-generation college-going
students? Hossler’s model admittedly is based on patterns and themes of traditional-
aged students who exist in an academic culture designed to enter a postsecondary
option immediately after high school. The research on college-going aspiration
among first-generation college going students is very small yet growing (Cooper,
2006). This study on how PBL can be used in the college preparation of first-
generation college-going students will shed some light on another delivery of college
preparation and how it can affect the college aspirations of these students.
Data Revisited, Limitations of the Study, and Recommendations/Modifications to
the Study
Starting with the 8
th
grade and ending with the 12
th
grade, the consistency and
intensity of the college decision-making process changes markedly (NPEC, 2007).
Usually students in the 8
th
, 9
th
, and sometimes the 10
th
grade, often do not actively
seek information on postsecondary options. Also, students in these grades tend to not
actively seek or start discussions on how to prepare for these options (NPEC, 2007).
The relevance of postsecondary information to the academic identity of a 9
th
grade
student is likely not as strong as the relevance of the same information to the academic
identity of a 12
th
grade student. This is a possible explanation for the lack of overall
significant differences of the college preparation in the PBL group compared to the
College Center and Outreach groups.
There were differences, with PBL demonstrating higher scores in motivation
and slightly higher scores in self-efficacy. Yet, maybe the differences in self-efficacy,
motivation and knowledge as they relate to college preparation could have been

109

significantly higher if applied to students with stronger academic identity; namely11
th

and 12
th
graders. These two populations would probably be more receptive and active
in their participation in the College Center, Outreach, and PBL groups. However, this
would run counter to the near universal agreement of the importance of early
intervention (ie., middle school intervention) in building awareness of postsecondary
options, taking the correct college preparation courses, and providing college-
aspiration support (De La Rosa and Tierney, 2006; Mumper, 1998; Perna and Swail;
2001).
In light of the fact that there were few if any PBL studies done on college
preparation of middle school and high school students, future studies applying PBL to
college preparation should continue utilizing qualitative and quantitative methods.
One additional qualitative method that can provide greater insight into the effects of
PBL on college preparation would be the interview; interviews not only with the
students in the study but also the facilitators/teachers in each group.
Additional research should be conducted on the potential of PBL in the college
preparation of first-generation college potential 9
th
grade students, as this is the last
grade where students can make significant changes to their academic profile for
admittance to a four-year university. However, the middle school population is
another population in which to investigate the influence of PBL. As well, because
parents have a vested interest in seeing their children succeed in academics and
transitioning to a postsecondary institution, future studies should consider
investigating the usage of PBL in the college preparation training of middle school and
high school parents.

110

In terms of the time frame for the study, the seven sessions were adequate due
to the timeliness of the completion of this dissertation. Future studies should consider
at least a full semester of PBL curriculum applied to college preparation. The short
duration of the current study may not have allowed the influences of PBL to enter the
college preparation learning in the group. Allowing more time for the students to
comfortably investigate what they know and don’t know about college preparation
through PBL would be a method worth investigating in future research.
The manner by which the study was delivered should be revisited. Because the
Outreach and PBL groups met after school, student interest in this college preparation
service was sometimes low and distracted. One way the student’s time spent in each
of the three groups was rewarded by the school was by allowing the student’s time
spent in the study to be credited towards the yearly community service requirement for
all students at High School X. Future research on PBL and college preparation in
middle schools and high schools should work towards strengthening the
institutionalization of the study, such as providing the college preparation workshops
during the regular school schedule. One example of an institutionalized school option
for providing additional college preparation is to provide PBL as part of the morning
homeroom or as a separate class for credit/no credit. This would eliminate the
distraction of “staying after school” and be replaced with the college preparation as
part of the normal school routine.
If funds are available, a trained PBL-facilitator should be hired to conduct the
PBL workshops. The principal investigator for this study had to be trained as a PBL-
facilitator due to lack of funds to provide financial compensation. The outreach

111

representative from the local postsecondary institution and using school personnel
were appropriate resources for this study and are recommended for future studies.
High School X was unique in that it provided a college preparation
environment for all students. Teachers were trained on the latest learning techniques
to implement in their classrooms and administrators were always focused on providing
a college going culture. This school was chosen due to the accessibility of the
administration and their willingness to participate in the study. However, this benefit
was also a limitation to the study’s relevance to the typical public secondary school.
Future research should be conducted at school campuses where a college going culture
may not be as strong, where there are high rates of English language learners, and
where academic performance according to state-wide standards is low. This would
allow the results of the study to be more applicable to the larger public school
environment.
Implications for Practice
This researcher began with the viewpoint that PBL would prove to show how it
can be a viable tool in teaching college preparation to high school students, especially
9
th
graders. Because the 9
th
grade represents one of the last opportunities for a
secondary student to efficiently prepare for becoming a competitive university
applicant, the viewpoint was the 9
th
grade students would be more receptive to college
preparation information because of the unique opportunity to prepare early through a
unique learning approach. This viewpoint was almost correct. While the students in
the study did show higher levels of motivation and some differences in self-efficacy as
they relate to college preparation, the students in the College Center, Outreach and

112

PBL groups all demonstrated some improvement in learning about how to prepare for
college.
Each of the three deliveries of college preparation benefited the students in
some way. Much like college preparation programs like GEAR UP, AVID, and
Upward Bound, each method of college preparation delivery provided unique benefits
to the students. Problem-based learning is a viable method for delivering college
preparation training. Supplemented with other school and community resources like
any other college preparation intervention, PBL does show promise in providing
students with a unique opportunity to learn about how to prepare for college while also
learning problem-solving skills that can be applied to both academic preparation and
leadership preparation. In this time of competitive university admissions where non-
academic criteria is considered just as much as academic criteria, PBL provides an
opportunity to allow the student to not only discover what it means to prepare for
college but also what it means to be a life-long learner.
Problem-based learning provides an opportunity for full-time counselors to
provide professional development opportunities for high school students to become
PBL mentors for their fellow students. Upon training and supervision by the full-time
school counselor, interested high school students can take advantage of a unique
leadership opportunity by being trained as a PBL facilitator and leading PBL
workshops on college preparation. This would represent another opportunity to
conduct research on this method of delivery, shedding more light on the capabilities
and challenges of PBL in the delivery of college preparation services.

113

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APPENDICES
APPENDIX A
First Guided Journal Questions for High School X
Questionnaire: Problem-based learning and college preparation

Thank you for agreeing to answer the following questions. Please take the next 10-20
minutes to answer the following questions as completely as you can. Your name will
be kept confidential and your answers will be placed in a dissertation study that aims
to find out how problem-based learning influences college preparation.

Name:___________________________________________________

How do you currently feel about your ability to prepare for college admissions?

133

How well do you think you would do if you started preparing for college today? What
skills and knowledge do you have to help you prepare for college? What skills and
knowledge do you feel you still need to prepare for college?

Based on your current college preparation experience, what methods of college
preparation do you feel you can do?

134

Besides having or working for good grades, what other skills do you have to help you
become a competitive college applicant.

Are you confident you can do all that is required to become a college applicant? Why
or why not?

What has influenced your ability (positively or negatively) to prepare for college?

135

APPENDIX B
Second Guided Journal Questions for High School X
Questionnaire: Problem-based learning and college preparation

Thank you for agreeing to answer the following questions. Please take the next 10-20
minutes to answer the following questions as completely as you can. Your name will
be kept confidential and your answers will be placed in a dissertation study that aims
to find out how problem-based learning influences college preparation.

Name:_____________________________________________________
What did you learn about your ability to prepare for college during the last three
weeks? Did anything influence (positively or negatively) your ability to prepare for
college?

136

What questions or problems have been raised over the last three weeks that require
more study? How will you answer these questions or resolve these problems? (Don’t
just list your current questions and problems. Include how you intend to solve these
new problems. With each question or problem, identify the resources you expect to
use to solve it, the amount of time you expect it to take, and when you will do it.)

How do you currently feel about your ability to prepare to be a college applicant? Has
your ability to prepare for college changed since the beginning of this workshop? In
what ways?

137

What have you learned about your college preparation abilities over the last three
weeks that would make you feel confident if you started planning for college today?

What have you learned about your college preparation abilities over the last three
weeks that would make you feel uncomfortable if you started planning for college
today?

138

How has your knowledge of what to do in order to prepare for college admissions
changed over the past three weeks?

Compared to three weeks ago, how confident and motivated in dealing with the
demands of preparing for college admissions?

139

APPENDIX C
Third Guided Journal Questions for High School X
Questionnaire: Problem-based learning and college preparation

Thank you for agreeing to answer the following questions. This is the last set of
questions you will answer. Please take the next 10-20 minutes to answer the following
questions as completely as you can. Your name will be kept confidential and your
answers will be placed in a dissertation study that aims to find out how problem-based
learning influences college preparation.

Name:_____________________________________________________
How well do you think you would do if you started preparing for college admissions?
What have you learned about your abilities that would make you feel uncomfortable in
preparing for college admissions? What have you learned about your abilities that
would make you feel confident in preparing for college admissions?

140

How do you currently feel about your ability and motivation to prepare for college
admissions? Has your ability and motivation to prepare for college admissions
changed since the beginning of this workshop? Explain How.

What was your understanding and knowledge of college preparation before you started
this workshop? How has your understanding and knowledge about college preparation
changed during this workshop?

141

Given your experience thus far, what methods of college preparation do you feel
confident actually doing?

What has influenced your ability (positively or negatively) to prepare for college?

Are you confident that you can deal with the demands of college preparation? Why or
why not? (Write on back of this sheet for your answer to this question)

142

APPENDIX D
General Perceived Self-Efficacy Scale (Schwarzer & Jerusalem, 1995)

Name:____________________________________________________

Directions: Write your response to each question (see Response Format below) in the
space provided to the left of each question. Please be sure that all ten questions are
answered, and that your name is in the appropriate space provided above (your name
will be kept confidential). Thank you.

Response Choicest:
1 = Not at all true 2 = Hardly true 3 = Moderately true 4 = Exactly true

____ I can always manage to solve difficult problems if I try hard enough.

____ If someone opposes me, I can find the means and ways to get what I want.

____ It is easy for me to stick to my aims and accomplish my goals.

____ I am confident that I could deal efficiently with unexpected events.

____ Thanks to my resourcefulness, I know how to handle unforeseen situations.

____ I can solve most problems if I invest the necessary effort.

____ I can remain calm when facing difficulties because I can rely on my coping
abilities.

____ When I am confronted with a problem, I can usually find several solutions.

____ If I am having trouble, I can usually think of a solution.

____ I can usually handle whatever comes my way.

143

APPENDIX E
Motivated Strategies for Learning Questionnaire
Demographic Information

Name:_______________________________________________

What is your race/ethnic background? Please circle one.
a. African American e. Pacific Islander/Native Hawaiian
b. Asian American f. White non-Latino American
c. Hispanic/Latino American g. Other, please specify____________
d. Native American

Gender (circle one): Male Female

What is the highest level of education for your father? Please circle one.
a. Elementary and Middle School d. Graduate School (Masters or
Doctorate)
b. High School e. No Schooling
c. College (Bachelors Degree)

Class Level (circle one): Freshman Sophomore Junior Senior

144

The following questions ask about your motivation for and attitudes about this college
preparation class. Remember, there are no right or wrong answers, just answer as
accurately as possible. Use the number scales below to answer the questions. If you
think the statement is very true of you, circle 7; if a statement is not at all true of you,
circle 1. If the statement is more or less true of you, find the number between 1 and 7
that best describes you. Please place your name where indicated (your name will be
kept confidential).

1 2 3 4 5 6 7
not at all very true
true of me of me

1. In a class like this, I prefer course material that 1 2 3 4 5 6 7
really challenges me so I can learn new things

2. If I study in appropriate ways, then I will be 1 2 3 4 5 6 7
able to learn the material in this course.

3. I think I will be able to use what I learn in this 1 2 3 4 5 6 7
course in other courses.

4. I’m certain I can understand the most difficult 1 2 3 4 5 6 7
material presented in the readings for this course.

5. It is my own fault if I don’t learn the material 1 2 3 4 5 6 7
in this course.

6. It is important for me to learn the class 1 2 3 4 5 6 7
material in this class.

7. I’m confident I can understand the basic 1 2 3 4 5 6 7
concepts taught in this class.

8. I’m confident I can understand the most complex 1 2 3 4 5 6 7
Material presented by the instructor in this course.

145

9. In a class like this, I prefer course material that 1 2 3 4 5 6 7
arouses my curiosity, even if it is difficult to learn.

10. I am very interested in the content area of this 1 2 3 4 5 6 7
course.

11. If I try hard enough, then I will understand the 1 2 3 4 5 6 7
course material.

12. I’m confident I can do an excellent job on the 1 2 3 4 5 6 7
assignments in this course.

13. I expect to do well in this class. 1 2 3 4 5 6 7

14. The most satisfying thing for me in this course 1 2 3 4 5 6 7
is trying to understand the content as
thoroughly as possible.

15. I think the course material in this class is useful 1 2 3 4 5 6 7
for me to learn.

16. When I have the opportunity in this class, I 1 2 3 4 5 6 7
choose course assignments that I can learn from
even if they don’t guarantee a good grade.

17. If I don’t understand the course material, it 1 2 3 4 5 6 7
is because I didn’t try hard enough.

18. I like the subject matter of this course. 1 2 3 4 5 6 7

19. Understanding the subject matter of this course 1 2 3 4 5 6 7
is very important to me.

20. I’m certain I can master the skills being taught 1 2 3 4 5 6 7
in this class.

21. Considering the difficulty of this course, the 1 2 3 4 5 6 7
teacher, and my skills, I think I will do well
in this class.

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Asset Metadata

Creator Vazquez, Marcelo F. (author)

Core Title Problem-based learning and its influence on college preparation knowledge, motivation, & self-efficacy in high school students

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 08/27/2008

Defense Date 05/12/2008

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag college preparation,High school students,Latino high school students,OAI-PMH Harvest,PBL,problem-based learning

Place Name Los Angeles (city or populated place)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Keim, Robert G. (committee chair), De La Rosa, Mari Luna (committee member), Venegas, Kristan M. (committee member)

Creator Email mfvazque@usc.edu,mvazquez2@cslanet.calstatela.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m1582

Unique identifier UC1331292

Identifier etd-Vazquez-2213 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-106556 (legacy record id),usctheses-m1582 (legacy record id)

Legacy Identifier etd-Vazquez-2213.pdf

Dmrecord 106556

Document Type Dissertation

Rights Vazquez, Marcelo F.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu