University of Southern California Dissertations and Theses

What motivational factors influence community college students' tendency to seek help through math tutoring?

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What motivational factors influence community college students' tendency to seek help through math tutoring?

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Content WHAT MOTIVATIONAL FACTORS INFLUENCE COMMUNITY COLLEGE
STUDENTS’ TENDENCY TO SEEK HELP THROUGH MATH TUTORING?
by
Chung-Yin Teresa Lai
____________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION
August 2008
Copyright 2008 Chung-Yin Teresa Lai
ACKNOWLEDGMENTS
To my chairperson, Dr. Myron Dembo; my dissertation committee members Dr. Luz
Shin and Dr. Ginger Clark; my family and friends; and to all who participated in and
helped me organize the study, I extend my deepest gratitude for your support and time.
ii
TABLE OF CONTENTS
ACKNOWLEDGMENT ii
LIST OF TABLES v
ABSTRACT vi
CHAPTER 1. INTRODUCTION 1
Tutoring and Academic Achievement 6
Help Seeking and Academic Achievement 10
Motivational Factors and Help Seeking 10
Purpose of the Study 16
Importance of the Study 17
Problem Statement 18
Research Questions 18
Definition of Terms 19
Organization of Study 21
CHAPTER 2. REVIEW OF THE LITERATURE 23
Academic Support Systems 25
Help Seeking in Academic Settings 27
Goal Orientation Theory 28
Perceived Classroom Goal Orientation 39
Self-Efficacy 46
Task Value 56
Summary 61
CHAPTER 3. METHODOLOGY 67
Participants and Setting 68
Procedure 69
Instruments 72
Data Analysis 76
CHAPTER 4. RESULTS
Quantitative Findings 78
Qualitative Findings 91
Summary 97
CHAPTER 5. DISCUSSION 98
Relationship between Motivational Variables and Help Seeking 99
Relationship between Help Seeking and Achievement 102
Student Perceptions of Math Lab Services 103
Student Expectations of Math Lab Services 104
Barriers Related to Help-Seeking 105
Implications 106
Limitations 109
Conclusion 109
REFERENCES 110
APPENDICES
A. Recruitment Speech for Students 131
B. Informed Consent for Students 133
C. Recruitment Speech for Math Lab Tutors 138
D. Informed Consent for Math Lab Tutors 139
E. Student Survey 142
F. Focus Group Questions 146
LIST OF TABLES
1. Descriptive Statistics and Estimates of Internal-Consistency Reliability 79
2. Means, Standard Deviations, and Pearson Product Correlations for
Measured Variables 84
3. Regression Analyses Predicting Help-Seeking Behaviors from Attainment
Value and Math Self-Efficacy 87
4. Regression Analyses Predicting Help-Seeking Behaviors from Cumulative
GPA, Attainment Value, and Math Self-Efficacy 90
v
ABSTRACT
The purpose of the current study was to examine predictor variables that might
help explain the students’ lack of proficiency in mathematics at a community college.
Particularly, this study scrutinized the degree to which personal goal orientation,
classroom goal structure, task value, and math self-efficacy, influenced the extent of help
seeking behaviors via math tutoring, and how help seeking related to math achievement.
A sample of 304 students enrolled in 25 sections of a prerequisite math course at a
community college participated in the study. Statistical analyses revealed that students’
attainment value and math self-efficacy influenced help seeking behaviors. Together, the
attainment value and math self-efficacy accounted for approximately three percent of the
variance in help seeking. However, results showed no significant relationship between
help seeking and achievement.
vi
CHAPTER 1
INTRODUCTION
Academic achievement has always been the primary concern for educators and
remains one of the most pressing issues for our nation today. In particular, the lack of
math proficiency has reached a level of crisis. While the No Child Left Behind Act,
otherwise known as the NCLB, has driven high-stakes testing in mathematics and
educational reform in the K-12 domain, a gap in math performance persists. Data
analysis reveals that in 2005, 39% and 32% of the nations’ public school students
performed at basic and below basic levels respectively, in the math content area (National
Center of Education Statistics, 2005).
Despite the fact that a majority of students are unprepared in many of the
fundamental academic skills including mathematics, many graduate high school and
move on to attend college. College enrollment has increased by 38% from the 1990s to
2003 and continues to rise each year (NCES, 2005). As postsecondary enrollments
increase, the number of under-prepared students grows proportionately. As a result, 2-
year and 4-year institutions across the board are flooded with students who are not
prepared for college level coursework.
Specifically, open access policies have contributed to a rise in community college
enrollment – with an estimated 11.6 million students enrolled in community colleges
across the nation in the year 2000 (American Association of Community Colleges, 2000).
1
Not only do community colleges admit a huge proportion of students from the low
socioeconomic stratum, minority categories, they also enroll students who are much less
academically prepared and achieving than those of other postsecondary institutions (Lee
& Frank, 1990). According to the 2005 Community College Survey of Student
Engagement (CCSSE), more than half of the students who enroll in community colleges
are not prepared for college and are placed in remedial courses. Likewise, Hoachlander
et. al (2003) reported that 64% of students who began their studies at community colleges
in 1994 possessed insufficient skills for doing college level coursework.
California State Universities report that 45% of regularly admitted freshmen
arrived unprepared in mathematics as indicated by placement exams. The National
Education Longitudinal Study reveals that 30% of the students score at Level 1 and
below on the math proficiency, incapable of performing basic arithmetic operations
(NCES, 2001). With the large number of students identified as lacking basic math
proficiency, 76% of Title IV degree-granting institutions have been forced to offer
remedial math courses to ensure that students acquire the basic skills necessary to achieve
at the postsecondary level (NCES, 2003). According to a recent report on Remedial
Education at Higher Education Institutions, all of the community colleges surveyed
offered remedial education courses in basic skills areas, including math (NCES, 1995).
One consequence of this is that much of the resources are allocated to remedial education
rather than actual college level courses that should be the primary focus of community
2
colleges. Moreover, this profusion of remedial courses at the community college level, as
well as in four-year institutions, is indicative of the students’ deficiency in fundamental
skills and preparedness for college level coursework.
Although there is debate with regards to the cost and consequences of offering of
remedial education in postsecondary institutions, the presence of and need for remedial,
or developmental education is clear. Remedial education, as the term indicates, serves as
an opportunity for students to overcome basic deficiencies in reading, writing, or math,
and prepare them for college-level coursework. Remedial courses bear no college credit
but are designed to lead up to credited, college-level coursework. There are several
forms of remedial education including stand-alone classes for each area of deficiency,
support classes linked to other courses, self-paced sessions, and more. Research on the
effectiveness of remedial education reveals that under-prepared students who are enrolled
in remedial programs earn higher grade point averages and complete courses at higher
rates than those who do not enroll in remedial courses (Weissman, Bulakowski, &
Jumisko, 1997). Owing partly to the documented effectiveness of remedial programs, the
presence of remedial education across campuses has exponentially increased and become
a part of the community college mission (Raftery, 2005). Though institutions vary in the
composition of their remedial program, it is generally hoped that remedial courses will
enable students to acquire the skills to become academically successful.
Before enrolling in college-level coursework, most incoming community college
students are required to take a skill assessment (NCES, 2003). However, regardless of
3
whether students meet the basic proficiency, not all institutions mandate that their
students enroll in remedial courses (Jenkins & Boswell, 2002; Perin, 2005). In the annual
report The Condition of Education, the National Center for Education Statistics indicates
that 61% of the students who attended 2-year colleges took at least one remedial course;
and of those, approximately a quarter of them failed to complete the course (NCES,
2005). In the Los Angeles Community College District, alone, 40% of the students failed
to acquire proficiency in basic skills in the period 2004-2005 (LACCD, 2007). The
sample for the proposed study examines students from a local urban community college
in Southern California, which will be referred to as College X. Based on the current
investigation, half of the students who enrolled in the two lowest remedial math courses
offered at the college, failed to pass. This is congruent with the trends found across other
two-year institutions across the nation (NCES, 2004). As the figures reveal, even with
remedial education, community college students are not achieving basic math
proficiency.
Specifically, at College X, approximately 800 of the 1600 students who enrolled
in remedial math courses in Fall 2000 failed. In other words, nearly 50% of the students
received grades of D or F in the remedial math courses they took. Given that a large
proportion of remedial math enrollees fail to acquire basic math proficiency, the number
of students taking transferable, credited math courses is dismal at best. The shockingly
low rates of success not only impact the achievement quotas the college is attempting to
achieve, but also create a chain of problems ranging from high dropout, low degree
4
attainment, and in general, an unskilled workforce incapable of meeting the social and
economic demands of our increasingly global society.
In response to the high numbers of students failing remedial courses, many
educational institutions have increased the number and types of academic support
services including supplemental instruction, learning labs, and study skills programs.
Many community colleges have since created learning assistance centers to support
remedial education efforts (Perin, 2004). Learning assistance centers offer a wide range
of services including advisement, counseling, computer assisted learning, and academic
tutoring (Stern, 2001), which are designed to help students surmount learning
impediments and efficiently grasp content knowledge (Grubb et al., 1999). Perin’s
(2004) study investigating the effectiveness of these learning assistance centers in 15
community colleges across the country reveals that learning centers are indeed valuable
in boosting students’ preparedness, and in some cases effective in raising student GPA.
Most colleges and universities, in particular, have since offered subject specific
tutoring programs to help students acquire basic mathematical skills and eventually be
able to take college level coursework. In the period 1992-1993, approximately 76% of all
colleges and 87% of 2-year colleges provided academic support in the form of tutoring
programs (NCES, 1995). College X, likewise, set up a math tutorial lab to assist students
in attaining basic math proficiency. The math lab is open daily to students on a walk-in
basis. Under the supervision of the instructional specialist and sometimes a math faculty,
paid tutors who have passed the mathematics skills diagnostic test and interview are
5
available during regular hours to assist students with any math assignments or questions.
Students log in with their student identification number and simply approach any of the
tutors present to receive assistance. In general, it is hoped that tutoring will have positive
effects on students’ attainment of basic math skills and ultimately contribute to students’
overall learning at the postsecondary level.
Tutoring and Academic Achievement
Research has found that tutoring, a form of academic support whereby students
receive assistance from peers or others, positively impacts students’ academic
achievement (Cohen, 1982; Fuchs, Fuchs, & Karns, 2001; Hendriksen, Yang, Love, &
Hall, 2005; Kulik, Kulik, & Schwalb, 1983; Robinson, Schofield, & Steers-Wentzell,
2005; White, 2000; Xu, Hartman, Uribe, & Mencke, 2001). While there are various
underlying theories (behaviorist, social-linguistic, or gestalt) that guide the design of
tutoring strategies, the overall goal of tutoring programs is to provide one with a more
individualized, meaningful, and engaging experience that will encourage one to acquire
necessary skills and succeed academically (Powell, 1997). In other words, students who
participate in tutoring, regardless of form, significantly improve their grades. Cohen,
Kulik, and Kulik (1982) conducted a meta-analysis of 65 studies to explore the effects of
tutoring programs on students in primary and secondary schools. In particular, the study
assessed the impact of tutoring on student achievement. In 87% of the studies, students
who received tutoring outperformed students who did not receive the intervention.
Similarly, Kulik, Kulik, and Schwalb (1983), found in their meta-analysis of 60 studies
6
on college intervention programs, that high-risk students who participated in tutoring and
other academic intervention programs attained higher grade point averages than those
who did not participate in the programs. Most of the studies conducted since the two
meta-analyses confirm that tutoring yields positive results in students’ academic
performance, at secondary and postsecondary levels.
Math Tutoring
As the previous section described, research findings have substantiated the
positive effects of tutoring on students’ overall academic achievement (Cohen et al.,
1982; Kulik et al., 1983; Gribbons & Dixon, 2001). In particular, tutoring has a major
influence on students’ achievement in the domain of math (Allsopp, 1997; Gardner,
Cartledge, Seidl, Woolsey, Schley, & Utley, 2001; Greenfield & McNeil, 1987; Lopez,
2001; Mieux, 1993; Robinson, Schofield, & Steers-Wentzell, 2005; White, 2000; Xu,
Hartman, Uribe, & Mencke, 2001).
Mieux (1993) developed a before-school peer and cross-age tutoring program to
help students functioning below proficiency levels in mathematics. Students referred to
the tutoring program were given a pretest in mathematics and monitored for the duration
of the tutorial program. Observations and report card grades revealed that the students
not only demonstrated more frequent application of study skills, but also performed better
in their math classes. The tutorial sessions compelled students to actively engage in their
own learning and thereby strengthened students’ basic mathematical skills, as shown by
7
their improved math grades and higher post-test scores. In other words, the extra help
that the students received via math tutoring had positive effects on students’ mathematics
performance at the primary levels.
Gardner et al. (2001) likewise explored the impact of tutoring in the after-school
setting on math performance. Elementary children who were identified as performing
below grade level were placed in a weekly, peer-mediated intervention program that
consisted of timed practice rounds in basic math facts and multiplication. At the
conclusion of the academic year, all of the students in the after-school tutoring program
demonstrated considerable gains in mathematics (Gardner et al., 2001). The difference in
students’ pretest and posttest scores showed that students improved in their math
accuracy and speed.
The outcomes of the above mentioned studies have been corroborated by
comparable studies (Fuchs et al., 2001; Greenwood & Terry, 1993). Although the
majority of studies involving middle and high school students at risk of failing math have
demonstrated that peer tutoring lead to higher scores on standardized assessments as well
(Early, 1998; Lopez, 2001; White, 2000), there is an exception to the positive correlation
between math tutoring and math achievement (Allsopp, 1997). The exception occurs
when the skills being taught are higher order, rather than basic math skills. Rather than
studying the impact of tutoring on basic math competency, Allsopp (1997) investigated
the influence of tutoring on students’ Algebra performance. The results of the
investigation indicated that tutoring had no significant impact on students’ mathematics
8
achievement, confirming the researcher’s hypothesis that tutoring yields limited benefits
for higher order skills such as algebraic manipulations. This finding supports the fact that
some students do not achieve at a higher level of math skill competency despite seeking
tutorial assistance.
Despite the above finding that tutoring has no impact on higher order math skills,
positive effects of math tutoring on the mathematics achievement have been found at the
postsecondary level with respect to college students (Williams, 1978). Specifically,
Williams (1978) discovered, upon examining the relationship between college student
success in math and math tutoring, that students, who were placed in weekly tutorial
workshops and asked to engage in peer tutoring sessions, improved their math grades
markedly at the conclusion of the semester than those who did not receive additional
assistance. The parallel findings indicate that students who obtain help by means of
mathematics tutoring, regardless of size, type, or format of instruction, achieved at higher
levels than those who needed but neglected to seek assistance. Although it is likely that
students’ effort to seek math tutoring is coupled with other help seeking behaviors and
that math tutoring is not the sole cause of academic improvement, there is nevertheless a
positive correlation that exists between mathematics achievement and math tutoring.
Together, the findings further support the aforementioned meta-analyses that lay the
groundwork on the impact of tutoring on achievement.
9
Help Seeking and Academic Achievement
Research on academic help seeking has shown that help-seeking behaviors or
tendencies play a moderating role in academic achievement (Karabenick, 2003; Newman,
1998; Ryan & Pintrich, 1997; Wigfield & Eccles, 2002). In other words, students’ ability
or willingness to seek help in the academic setting is directly related to their academic
performance. This is particularly relevant to the community college setting because a
large proportion of community college students lack the ability to succeed independently
in the remedial classes in which they are enrolled. If the students do not have the basic
skills and do not seek help, the likelihood of their passing courses is slim. Students who
are placed in remedial math courses, especially, will not be able to progress towards their
degrees since math serves as a gatekeeper to advanced college level courses. Therefore,
help seeking is of utmost importance in closing the gap in mathematics achievement
among community college students and ensuring that these students in fact receive a
higher education.
Motivational Factors and Help Seeking
An abundance of research studies have investigated motivational factors
correlated and predictive of help seeking. The following section will briefly describe the
motivational constructs that have been identified as possible factors influencing students’
help-seeking behavior or tendencies.
10
Goal Orientation
Goal orientation represents the beliefs that influence the manner in which one
approaches tasks and the standard by which one judges self-competence (Ames, 1992).
In terms of the framework, goal orientation reflects an individual’s reason for engaging in
achievement related activities and how the individual defines success or failure.
Although there are a number of constructs that fall under goal orientation, most stem
from two main goal orientations termed mastery and performance goals. Mastery goal
orientation refers to a focus on learning for the sake of developing competence and skills,
while performance goal orientation refers to a focus on striving to demonstrate
competence relative to others. Within mastery goal orientation, there are two
subcategories: mastery approach and mastery avoidance. Accordingly, mastery approach
-oriented students focus on mastering tasks, thorough understanding, and self-
improvement, whereas mastery avoidance-oriented students focus on avoiding failure to
master or understand a given task (Pintrich & Schunk, 2002). Likewise, performance
goal orientation has two forms, performance approach and performance avoidance.
Students who uphold the performance approach goal orientation focus on being superior
and outperforming others; on the other hand, students who are performance avoidant
focus on avoiding inferiority or appearing incapable in front of others (Pintrich &
Schunk, 2002). Research has shown that these goal orientations influence help-seeking
behaviors and tendencies (Butler, 1998; Butler & Neuman, 1995; Kaplan & Midgley,
1999; Karabenick, 2003; Karabenick, 2004; Karabenick & Newman, 2006; Linnenbrink,
11
2005; Middleton & Midgley, 1997; Newman, 1998; Newman & Schwager, 1995; Ryan,
Gheen, & Midgley, 1998; Ryan, Pintrich, & Midgley, 2001). Mastery-oriented students
are likely to exhibit self-regulatory behaviors including seeking help to obtain task-
related information that resolve difficulties and further progress toward achievement
goals. On the other hand, students who are performance oriented are less likely to exhibit
adaptive help-seeking behaviors. This difference may be due to the students’ view of the
benefits or consequences associated with help seeking. Alexitch’s (2002) finding
obtained with college students generally supports this relationship between goal
orientation and academic help seeking found in studies of younger students. Despite the
scarcity of research on goal orientation and help seeking of community college students,
a correlation between the two variables undoubtedly exists. Since students who attend
community colleges are a product of the primary and secondary educational system, it is
likely that the goal orientation they adopted at an earlier age continued to influence their
behaviors in college. A closer examination of the literature on goal orientation and help-
seeking tendencies will yield information that can help us understand why community
college students do not seek help in the academic setting. The proposed study will shed
light on goal orientations and how they influence students’ decisions of whether or not to
obtain tutoring outside of class.
Perceived Classroom Goal Orientation
Research has shown that students’ perception of the classroom goal orientation or
achievement goal structure influences their help seeking behaviors as profoundly as if not
12
more than personal goal orientation (Arbreton, 1993; Midgley, 2002; Pintrich & Schunk,
2002; Ryan et al., 1998; Ryan, Gheen, & Midgley, 1998; Turner et. al, 2002). Because
students are socially interactive, it is reasonable that their perception of the classroom
environment as supporting mastery or performance goals plays an important role in their
help seeking behavior. In particular, students who perceive the classroom goal structure
as mastery oriented are likely to adopt a personal mastery orientation and seek assistance
when necessary, whereas students who perceive the classroom goal structure as
performance based are likely to shy away from asking questions in fear of
embarrassment. Whether the classroom goal structure is explicitly or implicitly
communicated, students will form a perception that will impact their help seeking
tendencies. This perception will likely carry over to situations outside the classroom in
the academic setting, such as tutoring programs. Research examining the relationship
between classroom goal structure and students’ help seeking behaviors, has revealed that
task-focused goal structures are associated with low levels of help avoidance and relative
ability goal structures are related to high levels of help avoidance, regardless of how
these goal structures came to influence student beliefs and behaviors (Ames, 1983;
Newman, 1991; Ryan & Pintrich, 1998; Ryan, Gheen, & Midgley, 1998). In other
words, in classrooms where emphasis is on successfully learning and completing a task
students were less likely to refrain from seeking assistance, while in classrooms where
the focus is on outperforming others students were more likely to avoid asking for help.
Similarly, Karabenik (2004) found an existing relationship between college students’
13
help seeking and their perceptions of classroom achievement goal structure. In the
proposed study, the influence of perceived achievement goal structure on academic help
seeking will be scrutinized. An in-depth understanding of the relationship between the
two variables will reveal why community college students do not seek help in face of
academic difficulties.
Self-Efficacy
Self-efficacy refers to one’s belief in his or her capabilities to organize and take
courses of action needed to achieve substantive outcomes (Bandura, 1997). Specifically,
academic self-efficacy refers to students’ beliefs in their ability to complete school
assignments successfully (Schunk, 1991). Literature on help seeking is replete with
evidence of a relationship between self-efficacy and help-seeking behaviors (Dweck,
1986; Dweck & Leggett, 1988; Elliot & Dweck, 1988; Newman, 1990; Ryan, Gheen, &
Midgley, 1998; Ryan & Pintrich, 1997; Silver, Smith, & Greene, 2004). Students who
have high self-efficacy are likely to ask for assistance when encountering difficulty,
while students who have low self-efficacy are likely to avoid seeking help in fear of
revealing their lack of ability. Although some studies have reported that students with
high self-efficacy sometimes also refrain from seeking help, there is a consensus that self-
efficacy plays a significant role in students’ academic help seeking behaviors regardless
of its direction of impact. Literature on self-efficacy and help seeking of community
college students is sparse. However, by looking at how self-efficacy beliefs influence
students’ willingness to seek academic assistance at the primary and secondary levels,
14
one will better understand how community college students, who are the product of
primary and secondary institutions, view their own capabilities. This could help in
finding ways to counter their reluctance to seek help. Specifically, an examination of
math self-efficacy in the following chapter will yield valuable information with regards to
students’ mathematics achievement and help seeking tendencies.
Expectancy Value
According to the current expectancy-value model, which is derived from Lewin
and Atkinson’s (1957) synthesis of achievement motivation, the main predictors of
achievement behavior are expectancy and task value. Eccles and Wigfield’s (2000)
social cognitive model purports that achievement behaviors including choice, cognitive
engagement, and actual performance, effort, and persistence, are all products of cognitive
and motivational beliefs that are impacted by the social environment. Specifically, the
expectancy construct refers to students’ beliefs about their probability of success and the
task value construct deals with the four incentive values (attainment value, intrinsic
value, utility value, and cost belief) students espouse. The first of these, attainment
value, refers to the importance individuals place on a task. Intrinsic value refers to the
enjoyment one reaps from the task. Utility value is defined as one’s judgment of the
usefulness of the task. Finally, cost value is identified as the tradeoffs associated with
engaging in a particular task. Together these constructs influence an individual’s
decision-making and task engagement. Research has shown that as students grow older,
their attainment task values decline (Eccles & Midgley, 1989; Wigfield & Eccles, 1992;
15
Wigfield, 1994) and their self-perceptions of ability decrease as well (Rosenholtz &
Simpson, 1984; Reuman, 1989). Overall, older students demonstrate lower self-
perceptions of competence, exhibit less interest and place less importance on academic
subjects. In addition, data has revealed gender differences in the two constructs, intrinsic
and attainment value (Wigfield & Eccles, 2002). In a recent study, Eccles, Vida, and
Barber (2004) found that students’ academic value was a strong predictor of their
enrollment decisions and college plans. For instance, students who held high expectancy
and task value beliefs about mathematics were more likely to enroll in college-bound
math course sequences during high school and have higher educational aspirations than
those with low expectancy and task value beliefs. Moreover, high expectancies of
success were found to be associated with more help seeking behaviors. However,
research on the direct influence of task value on help seeking tendencies is sparse. This
gap in research prompts the need for an advanced investigation of the motivational
construct of task value.
Purpose of Study
Disturbingly, current research indicates that students who need help seek it least
(Alexitch, 2002; Karabenick & Knapp, 1988; Ryan, Gheen, & Midgley, 1998).
Specifically, students struggling in classes are less likely to ask for assistance than those
who are performing satisfactorily. The purpose of this study was to contribute
knowledge and understanding to the topic of why students do not seek help in academic
settings. The study narrowed in on factors influencing help seeking by employing a
16
framework grounded in motivation theory. This study further distinguished itself from
previous research in that it focused on academic help seeking in mathematics, a domain
that carries considerable weight in students’ overall academic achievement and degree
attainment. A thorough exploration of help seeking and the motivational factors
influencing help seeking, such as goal orientation, perceived classroom goal orientation,
self-efficacy, and task value, will enable us, as educators, to strengthen, modify, or come
up with effective academic tutoring programs that will help close the gap in math
achievement at the community college level.
Importance of Study
Given the large numbers of students attending community colleges and the
striking number of students achieving below desired levels, something must be done in
order to close the gap in math proficiency. Not only does a lack of math proficiency
reduce one’s chance of successfully passing a remedial course, it reduces one’s
probability of attaining a formal degree and limits one’s opportunity to fully participate in
the workforce. In order for the nation to meet the demands of the changing economy,
community colleges must provide students with adequate skills to enter the workplace
and compete in the job market. Whether the supply of workers will meet the demand and
expectations of the job market will depend on the remedial education provided by
community colleges across the nation. Helping community college students pass
remedial math courses and achieve beyond the minimum has inevitably become one of
the core goals of higher education. Educators need to examine the motivational factors
17
that influence students’ help-seeking behaviors, as well as the relationship among the
factors, to understand the critical questions as to why low mathematics achievement
exists despite the abundance of tutorial programs available. A comprehensive
investigation on the topic can yield valuable knowledge and provide insight as to how
help seeking behaviors can be promoted in the community college setting.
Problem Statement
In spite of the abundance and availability of math tutoring programs across the
nation, and at College X under investigation, a math achievement gap persists. Students
who need the additional assistance are not taking advantage of the math tutoring available
by seeking help outside of class. Tutoring, which involves assistance with schoolwork,
instruction, and the development of good study habits, has been found to be effective in
enhancing student learning in many settings (Hendriksen, Yang, Love, & Hall, 2005; Xu,
Hartman, Uribe, & Mencke; 2001). Regardless of the positive effects tutoring has on
math achievement, the problem of math underachievement cannot be resolved if students
who need assistance do not seek help.
Research Questions
The primary research questions for this study were: Do students’ personal goal
orientations, perceptions of the classroom goal structure, self-efficacy beliefs, and task
values influence their help seeking behaviors? Do students who seek help achieve at
higher levels than students who fail to seek help?
18
The secondary research questions were:
3) What are students’ perceptions of the math tutoring services provided and how
do these perceptions influence their help seeking behaviors?
4) What do students who seek math tutoring expect from the services?
5) What are the barriers related to students seeking help?
These research questions examined remedial education and tutoring programs,
which are an integral part of the community college system today. Answers to the
questions will provide an in depth understanding of the motivational constructs that
underlie students’ help-seeking behaviors, which will help community colleges
implement or modify existing programs to suit the needs of the students. Findings can
also be utilized to develop appropriate interventions that positively influence students’
goal orientation and self-efficacy, as well as adjust the achievement goal structures of
community college classrooms and tutoring labs, which together promote adaptive help-
seeking behaviors essential for academic success.
Definition of Terms
Help Seeking
Help seeking, a self-regulated learning strategy, refers to taking the initiative or
active role in seeking assistance when needed (Newman & Schwager, 1995). This
includes knowing what help to seek, when and where to seek help, and how to seek help.
Accordingly, Nelson-Le Gall (1985) defines help seeking as individuals seeking
assistance when they are unable to meet task demands independently.
19
Goal Orientation
Goal orientation refers to the beliefs that influence the manner in which
individuals approach or engage in tasks and the standard by which they define and judge
their competence (Dweck & Leggett, 1988). Individuals who exhibit a mastery approach
goal orientation are focused on acquiring new information, understanding, and mastering
skills to improve their competence, while those who maintain a mastery avoidance goal
orientation are focused on avoiding learning or having misunderstandings. In contrast,
those who maintain a performance approach goal orientation focus on demonstrating
competence relative to others, while individuals who adopt a performance avoidance
orientation are governed by their goals to mask incompetence.
Self-Efficacy
Self-Efficacy, a term once used interchangeably with self-concept, now distinctly
refers to one’s belief in his or her capabilities to organize and take courses of action
needed to achieve substantive outcomes (Bandura, 1997). More specifically, self-
efficacy is defined as, “…people’s belief in their capacity to exercise control over their
own functioning and over environmental demands” (Bandura, 1997, p. 368). Self-
efficacy beliefs are developed when individuals assess their competence based on past
experience and the relative difficulty of the task presented (Pietsch, Walker, & Chapman,
2003).
20
Achievement Goal Structure
Achievement goal structure refers to a classroom’s adoption of a mastery or
performance goal orientation. Academic settings in which the acquisition of skills and
thorough understanding of concepts are the primary focus are mastery oriented. On the
other hand, performance oriented classrooms invite competition and judgment of students
relative to others. Perceived achievement goal structure is defined as the goal orientation
of an academic setting from the perspective of the student.
Expectancy Value
The model assumes that individuals’ choices are influenced by their task value
beliefs. Task value refers to the various values (attainment, intrinsic, utility, cost) one
places on a given task. Together, these make up the determinants of choice.
Organization of the Study
Chapter 1 presented an overview of the current issues related to the persisting
mathematics achievement gap at the community college level. Academic help seeking
and tutoring were discussed as they relate to academic achievement. Motivational
variables identified as predictors of help seeking tendencies were then examined. Based
on the information available, it was established that a knowledge gap exists with regards
to motivational factors influencing academic help seeking and the mathematics
achievement of community college students. Together, the aforementioned led to the
development of the purpose of the investigation, the importance and implications of the
study, and the guiding research questions.
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Chapter 2 is a comprehensive literature review that examines academic help
seeking in detail, as well as the motivational constructs of personal goal orientation,
perceived achievement goal structure, self-efficacy, and task value, as they relate to
academic help seeking. Relevant studies were used in determining the correlations
between the variables.
Chapter 3 presents the methodology of the research investigation. Specifically,
the participants and setting, sampling procedures, instrumentation, and data analysis, are
described in detail.
Chapter 4 is the results of the study, including a descriptive analysis of the inter-
correlations among the variables, followed by a discussion of the findings.
Chapter 5 focuses on conclusions drawn from the study. Limitations as well as
implications and recommendations for practice at community colleges, are discussed at
the conclusion of the chapter.
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CHAPTER 2
REVIEW OF THE LITERATURE
The following review will examine previous research findings on the influence of
personal goal orientation, perceived classroom goal orientation, self-efficacy, task value,
and the moderating role of help seeking, on mathematics achievement. In particular, this
section will investigate personal goal orientation as it relates to help seeking. A review of
the relationship between perceived classroom goal orientation or classroom achievement
structure and help seeking, will be scrutinized. Also, the correlation between self-
efficacy and help seeking will be discussed. Subsequently, a focused examination of the
influence of task value on help seeking will be presented. Lastly, a detailed summary and
analysis of the research findings will be presented.
This literature review was conducted by obtaining articles from online databases,
including PsychInfo, ERIC, ProQuest, using the keywords and descriptors goal
orientation, help seeking, self efficacy, math self efficacy, task value, peer and cross-age
tutoring, math tutoring, and math achievement. Articles published prior to 1995 were
included under the circumstance that they were landmark studies or provided valuable
information for further understanding of the topic at hand. The majority of the articles
cited are from 1995 to 2006.
Although college students, primarily community college students, are intended to
be at the heart of this discussion, research conducted on the target group is available but
less abundant; therefore, studies that used primary and secondary school students were
23
included. The inclusion of these studies was done carefully, keeping in mind that they
yielded data that provided an in-depth understanding of help seeking and the aforesaid
motivational constructs, as well as their relevance to the community college student
population. It is also important to note that several researchers who conducted studies
with one student population did so with alternate student populations as well. Given that
most college students, including community college students, are a product of the
primary and secondary educational system, and that similar data have been collected
across different student populations, the studies that used non-college students are of
immediate relevance. Also, samples composed of individuals with disabilities were
excluded on the basis that motivational influences and help seeking related outcomes
would be different for such populations.
With respect to tutoring effects, even though this review focuses on the domain of
mathematics, studies on tutoring in other subjects are included when such research lent
insight on the effects of tutoring on student achievement. Additionally, because the
present study intends to verify the motivational variables impacting academic help
seeking behaviors through tutoring primarily, various types of tutoring interventions,
including peer tutoring, cross-age tutoring, group tutoring, are included.
Another characteristic of the literature review worth mentioning is the exclusions
of terms that describe the background of students involved in the studies. Since the study
aims to understand the motivational beliefs of community college students at large,
24
minority status, ethnic differences, and gender distinctions, are all excluded. All samples
are described according to levels of educational attainment, such as primary, secondary,
or college students.
The following literature review will present the findings of the accessed studies,
paying special attention to the congruities and discrepancies across the board. Findings
from primary and secondary populations will be presented in cases where they can be
generalized and are applicable to college students.
Academic Support Systems
In an effort to boost students’ academic achievement, community colleges have
implemented a range of support services to supplement regular classroom instruction.
Academic support systems implemented include skills workshops, counseling, and
tutoring programs. While the increased presence of counseling services and study skills
workshops has made an impact, tutoring labs have been the major and most immediate
sources of academic assistance provided by community colleges throughout the nation
(Hendriksen et. al, 2005; Perin, 2004). Research has revealed that, in general, tutoring
correlates positively with student’s grades (Cohen, Kulik, & Kulik, 1982; Fuchs et al.,
2001; Hendriksen et al., 2005; Kulik et al., 1983; White, 2000; Xu et al., 2001). In other
words, students who choose to participate in tutoring programs and receive academic
assistance in their schoolwork, improve their grades significantly. However, despite the
evidence supporting the impact of tutoring on achievement, many students fail to seek
assistance through such academic support systems. This may be, in part, due to the
25
effectiveness and attractiveness of the academic support programs available. As research
indicates, the support services available vary in their quality and receptiveness to student
needs, which thereby influence students’ help seeking behaviors (Finkelstein, 2002;
Perin, 2004; Hendriksen et al., 2005).
Upon examining successful academic support programs, most of which are
tutoring services, Finkelstein (2002) found that all programs successful in attracting
students possessed the following criteria: first, the staff listened to the students with
regards to their questions and concerns; secondly, they were proactive in design; third,
the services were directed by effective faculty; fourth, the staff helped students feel
recognized and a part of the learning process; fifth, they provided students with
opportunities to assist one another; sixth, they were regularly evaluated on their actual
impact on student performance; and lastly, they were open and creative in offering new
services. Together, these components constitute the effectiveness of academic support
programs available.
Recently, Hendriksen et al. (2005) examined the effectiveness of a tutoring
program in the community college setting by focusing on the program’s impact on
students’ attainment of academic goals. The program evaluations revealed that students
who received tutoring assistance completed remedial courses at higher rates than those
who did not receive tutoring from the center. Additionally, evaluations provided
evidence that students who received tutoring progressed from doing remedial coursework
26
to completing regular college coursework in higher numbers. Finally, students reported
that the tutoring program was receptive to their needs and helped them boost their grades.
Thus, as evidenced by the above studies, academic support programs can make an
immense contribution to students’ achievement provided that they are receptive and
effective. A well-designed academic support program has the potential to goad students
to take action in improving their grades and achieving their academic goals.
Help Seeking in Academic Settings
Help seeking, as dictated by the term, refers to the process of seeking or obtaining
assistance in times of need in an effort to better one’s learning or performance. In
particular, help seeking ranges from actively asking questions to voluntarily participating
in tutorial outside of class. Given that most students will encounter some form of
academic difficulty and need assistance some time in their academic career, help seeking
holds the potential of guiding students through their problems in the immediate and
future states. Studies in academic help seeking and tutoring have shown that help
seeking behaviors lead to positive outcomes, such as attitude and approach to school, self
efficacy, interest in tasks, and overall achievement (Allsopp, 1997; Gardner et al. 2001;
Robinson et al. 2005; Topping, Campbell, Douglas, & Smith, 2003). In particular,
Topping et al. (2003) found that cross-age tutoring using mathematical games contributed
to gains in tutees self-confidence in math, or more appropriately math self-efficacy, as
well as generated a higher level of interest and enthusiasm in the subject. This study,
along with others examining the role of help seeking, confirms the short-term and long-
27
term advantages of help seeking. While these advantages can be attributed to the general
process of help seeking, there are two distinct types of help seeking behavior: expedient
help seeking and instrumental help seeking. The first of the two, expedient help seeking,
which is also known as executive help seeking, refers to the act of acquiring aid for the
sake of avoiding work or exerting mental effort. The latter, on the other hand, refers to
the acquisition of aid that can be applied to related future tasks or are adaptive in
achieving a long-range objective. The potential benefits of help seeking point to the need
to further understand the motivational variables that influence the adoption of help
seeking behaviors.
Goal Orientation Theory
Goal orientation theories were developed to explain achievement behavior in
particular. Rather than scrutinizing the goal setting and content, this theory is concerned
with how students’ beliefs lead to their differential task approach and engagement.
Although there are variations of goal orientation, all focus on examining individuals’
purposes or goals for engaging in achievement behavior. In general there are two
contrasting dimensions of goal orientation: mastery and performance goal orientations
also referred to as task-focused and ability-focused orientations. The mastery or task-
focused goal orientation is defined as the inclination to engage in tasks for the purpose of
mastery, gaining an in depth understanding, and self-improvement (Dweck & Leggett,
1988). The performance or ability-focused orientation, in contrast, refers to an emphasis
on relative competence. Individuals who adopt a performance orientation make decisions
28
in accordance to and view themselves in terms of their relative standing amongst peers.
More recent research on goal orientation further makes a distinction within the mastery
and performance goal orientations: approach and avoidance forms. The mastery
approach orientation refers to a focus on learning and understanding, whereas mastery
avoidance orientation focuses on avoiding failure of mastery. Even though both mastery
orientations are concerned with learning, mastery avoidance oriented students set
extremely high standards to not fail. Similarly, although performance oriented
individuals judge themselves relative to others, performance approach oriented students
seek recognition for their ability, while performance avoidance oriented students avoid
being recognized at all to hide inferiority
Goal Orientation and Achievement
Goal orientation, unlike some constructs that focus simply on the degree of
motivation, looks at the goals and purposes that are perceived of achievement behavior
(Dweck & Leggett, 1988). Traditionally, the mastery and performance goals have
dominated the center of discussions as researchers have conceptualized the predictive
utility of task and performance goal orientations (Pintrich & Schunk, 2002). In theory,
goal orientation impacts students’ level of academic achievement since students are
driven by their desire to attain success or avoid failure. In several studies, researchers
found task goal orientations to be positively correlated with students’ school grade point
average (Dupeyrat & Marine, 2005; Lepper, Corpus, & Iyengar, 2005). In other studies,
the relationship between mastery orientations and achievement are unfounded (Meece,
29
Blumenfeld, & Hoyle, 1988; Harackiewicz, Barron, Carter, Letho, & Elliot, 1997;
Wolters, 2004). Likewise, both positive correlations (Barron & Harackiewicz, 2001;
Harackiewicz, Barron, Tauer, & Elliot, 2002) and negative correlations (Lepper, Corpus,
& Iyengar, 2005) between performance goal orientations and students’ GPA were found.
The different findings point to the possibility that other factors are mediating the
outcomes.
In a recent study, Lepper, Corpus, and Iyengar (2005) predicted that students who
are intrinsically motivated, or mastery oriented, would perform better academically than
students who are extrinsically motivated and oriented around performance approach and
avoidance goals. Using Harter’s Scale of Intrinsic vs. Extrinsic Motivational Orientation,
researchers assessed the motivation orientations of samples of elementary and middle
school students. Results of the study revealed that there was a significant positive
correlation between overall GPA and intrinsic motivation, as well as a significant
negative correlation between GPA and extrinsic motivation. This was consistent with
previous finding on the predictive utility of mastery and performance goal orientations on
achievement.
In the same year, Dupeyrat and Marine (2005) conducted a study on the effects of
goal orientation and achievement of a sample of adult learners returning to school. In
line with the results of the aforementioned study, researchers found that mastery goal
orientation led to increased use of deep learning strategies and impacted achievement
positively. However, taking into account the mediating role of effort, mastery
30
orientations had little impact on achievement. This points to the idea that students who
place an emphasis on understanding and skills utilize more learning strategies, but only
with considerable effort did they develop and acquire competence. Students upholding
performance orientations, on the other hand, exhibited both shallow and deep learning
strategies but neither predicted achievement.
In examining college students, however, Harackiewicz et al. (1997) found that
mastery goal orientations were not in any way related to actual academic performance,
whereas performance goal orientations were positively related to course outcomes and
overall grade point average in the following semesters. Instead, mastery goal orientations
were positively correlated with sustained interest in the course subject and performance
goal orientations were negatively or not associated with interest. Senko and
Harackiewicz’s (2005) study with another sample of college students provided further
support that performance goal orientations can lead to high achievement.
The clashing evidence prompted Harackiewicz, Barron, Tauer, and Elliot (2002)
to conduct a 4-year longitudinal study on the predictive utility of achievement goal
orientation on students’ college success. This study added to the existing knowledge in
that students were monitored over the entire course of their college career in terms of
their performance and sustained interest, thereby strengthening the predictive utility of
goal orientation with regards to academic achievement. Outcome measures of academic
success assessed in terms of overall GPA and continued interest as indicated by
31
subsequent enrollment in courses, showed that mastery goals were predictive of interest
and performance goals were directly related to achievement.
In yet another study, researchers looked at the influence of student’s goal
orientation on exam performance (Elliot, McGregor, & Gable, 1999). Like previous
studies, results revealed that students who held mastery goal orientations engaged in deep
information processing, demonstrated more cognitive effort, and utilized learning
strategies. On the other hand, the data on students who held performance goal
orientations was mixed. While performance-approach and performance-avoidance
oriented students both processed information at a superficial level, performance-approach
oriented students, like mastery oriented students, exhibited more cognitive effort and
persistence. However, performance-avoidance oriented students demonstrated little
effort and had lower achievement. These results indicate that regardless of whether an
individual adopts the mastery or performance-approach goal orientation, he will achieve
as long as there is sustained focus on the achievement goal or task.
The disparate findings on the relationship between goal orientation and
achievement point to the notion that mastery orientation is more motivating in terms of
persistence on a task than actual performance, which may explain why mastery oriented
students do not necessarily have higher achievement than those who are performance
oriented. Also, the qualitative differences in the secondary and college populations may
account for some of the differences found. College students who are motivated to
achieve high grades for the sake of attaining a good GPA will probably do all that is
32
necessary to ensure their academic success, whereas those who are intrinsically motivated
will focus their energies on understanding the entire learning process and neglect their
grades.
Goal Orientation and Math Achievement
In attempt to account for the disparities, Middleton and Midgley (1997) tapped
into the predictive nature of performance avoidance tendencies. In the experimental
study, the researchers narrowed in on the academic setting, focusing on middle school
students’ mathematic achievement. The results revealed that performance goal
orientations did not facilitate academic achievement; rather, they were positively
correlated with avoidance behaviors and test anxiety (Middleton & Midgley, 1997).
Students with lower GPAs were found to endorse performance approach and avoidance
goal orientations. This correlation confirms the idea that preoccupation with one’s
abilities relative to others takes students’ focus away from mastery of skills and thereby
hinders academic achievement.
Wolters’ (2004) study provided further evidence supporting the notion that
mastery orientation is not predictive of mathematics achievement. Although mastery
oriented students were less likely to procrastinate, more likely to take math courses in the
future, more likely to exhibit effort, and more likely be cognitively engaged, these
students did not achieve at higher levels. In other words, the students’ mastery
orientation was not predictive of math grades assigned at the end of the term.
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In recent years, it has become clear that both mastery and performance goals can yield
positive results in terms of academic achievement. It is clear that while mastery goals
induce students to engage deeply in their learning of concepts and thus lead to positive
outcomes, performance goals can also encourage students to engage in activities for
different reasons. Given that most research on goal orientation and achievement rely on
correlative methods, other factors need to be examined to ascertain what exactly accounts
for the relation between the two variables.
Help Seeking and Goal Orientation
In situations where there is a discrepancy between students’ abilities and task
related demands, it is logical that they would regulate their learning and request help as it
affects their academic achievement. However, research has shown that while some
students lack the ability to meet academic demands independently, they do not engage in
self-regulatory or help-seeking behaviors as a way of coping with difficulty and attaining
mastery (Dillon, 1982; Newman & Goldin, 1990; van der Meij, 1988). In order to
promote help seeking as a form of self-regulated learning, which directly influences
achievement, it is imperative that educators understand the motivational beliefs that
mediate students’ help seeking tendencies. Chiefly, examination of the effects of goal
orientation on self-regulation including help seeking behaviors and attitudes will point to
new directions for raising students’ academic achievement.
Earlier on, Ames and Archer (1988) conducted a study on the relation between
goal orientation and self-regulated learning. One hundred seventy-six middle and high
34
school students randomly chosen were asked to respond to a questionnaire about their
perception and adoption of goal orientation, as well as their use of effective learning
strategies such as planning study activities, monitoring attention, and sustaining
motivation. Students perceiving and adopting the mastery goal orientation of their
classroom environment reported more frequent use of learning strategies. Although
academically advanced, self-efficacious students are expected to exhibit a high degree of
self-regulated learning, the findings revealed that the effects of a mastery or performance
oriented classroom contexts modified their academic strength or self-perceptions of
ability, and that students’ self-regulatory and help seeking tendency was defined by the
goal orientation the students adopted.
In a later study, Butler and Neuman (1995) decided to examine the effects of task
and ego achievement goals on help-seeking behaviors and attitudes of 6
th
-grade students.
Task-involved orientation, in this case, is conceptually consistent with what Bandura
(1977) called intrinsic motivation, what Ames (1991) called mastery goal orientation,
whereby individuals strive to improve, learn, and understand tasks at hand. The research
found that students were more likely to seek help when task goals rather than ego goals
were more salient (Butler & Neuman, 1995). In other words, individuals more frequently
sought help when tasks were presented as opportunities for developing skills and
competence than when presented merely as an indicator of ability. Also, the study
revealed that students who held task goal orientations perceived help seeking as striving
35
for mastery, while students who held ego-focus orientations explained help-avoidance in
terms of masking incompetence.
To further scrutinize the influences of personal and contextual achievement goals
on students’ help seeking, Newman (1998) conducted a study where he observed
students’ mathematical problem solving process. Results revealed that students with a
learning or mastery goal orientation were more likely than those with a performance goal
orientation to request process-related information (Newman, 1998). That is, a positive
relation was found to exist between the frequency of help seeking and learning goal
condition, whereas a negative relation was revealed in the performance goal condition.
Additionally, when students with strong performance goal orientations were placed in
learning goal contexts, they demonstrated more process-related help seeking than they
had done in performance goal contexts. This study revealed that not only that goal
orientation influences help-seeking behavior but also that the learning environment
played a role in goal adoption, which translated to help seeking.
Karabenick (2003) conducted a study on help seeking in large college classes.
Specifically, goal orientation and the associated help seeking behaviors were examined.
Findings of the study were consistent with previous studies on primary and secondary
populations (Arbreton, 1998; Ryan & Pintrich, 1998) establishing that help seeking could
be differentiated by approach and avoidance patterns. As predicted, mastery goal
oriented students were more likely to demonstrate help seeking behaviors than
performance-oriented students. In accordance with the current goal orientation theory,
36
help avoidance behaviors likely stem from performance-oriented students’ attempt to
conceal signs of stupidity and dodge embarrassment.
Skaalvik and Skaalvik’s (2005) study on adult learners returning to high school
yielded results congruent with Karabenick’s (2003) findings on college students.
Performance orientations, including both performance avoidance and performance
approach orientations, predicted students’ perception of help seeking as threatening and
negative perceptions of help seeking were correlated with low levels of help seeking
behaviors. Linking the data, performance orientations were found to be significant
predictors of help seeking tendencies.
Butler (1998) added a layer of complexity to understand the role of personal goal
orientation in help seeking and considered the possibility that students fell into
subcategories under the umbrella of mastery and performance goal orientations. The
researcher proposed that there are three sub-orientations: autonomous, ability-focused,
and expedient. In particular, individuals who fall into the category of autonomous
mastery orientation would avoid seeking help in an attempt to strive for independent
mastery; individuals with an ability-focused or performance avoidance orientation, would
avoid asking for assistance to mask incompetence; and, individuals belonging to the
expedient orientation category would avoid seeking help with the perception that
assistance would not expedite the completion of tasks. As the author predicted, the sub-
orientations determined students’ help seeking behavior, with highest numbers of pupils
endorsing the ability-focused orientation as reason not to seek help. Contrary to popular
37
findings, mastery oriented individuals did not necessarily exhibit more help seeking
tendencies. Mastery oriented students who are autonomous refrained from seeking
assistance because they preferred to work out their problems independently. On the other
hand, mastery oriented students who see themselves as apprentices sought guidance
because asking for help was part of the learning process.
Bartholome, Stahl, Pieschl, and Bromme (2006) corroborated the above finding in
their study of a sample of college level students taking science courses. Even though the
researchers expected that mastery oriented students would show higher levels of help
seeking considering their motivation to learn and develop new skills relevant to the given
task, the data did not confirm their hypothesis. Again, this may be due to the fact that the
students’ high mastery orientation induced autonomy, which in turn reduced their
likelihood to seek help. In other words, students who are extremely focused on learning
may avoid seeking assistance in strive for independent achievement of a task.
Taken together, the results of the studies on the effects of goal orientation on
help-seeking and self-regulatory behavior provide support for the proposal that
differential goal approach or avoidance tendencies are associated with the absence of
academic help-seeking behaviors. The majority of the examined studies found positive
associations between mastery orientation and instrumental help seeking, as well as a
relation between performance orientation and high levels of help seeking avoidance.
Although there are instances where contextual aspects of tasks altered expected learning
38
behaviors, the majority of the research examined revealed that mastery goal orientations
encouraged help-seeking behaviors and performance goal orientations inhibited adaptive
help seeking.
Perceived Classroom Goal Orientation
In addition to the personal goal orientations discussed, there is the influence of
goal structure. Goal structures refer to the environmental cues that make organizational
goals salient (Ames, 1992). Learning environments, including its school policies,
classroom features, and instructional practices, all contribute to the dominant goal
structure. However, there is no concrete definition that describes exactly what goal
structure is. It could be a school’s mission to outperform neighboring schools or
teachers’ use of normative standards to evaluate students that foster a performance
oriented goal structure. It could also be a school’s mission to instill meaning in students’
learning or teachers’ emphasis on mastery of content over grade outcomes that cultivate a
goal structure that is mastery-oriented. In any case, goal structure is a salient feature that
cannot be ignored when discussing student learning and achievement.
Perceived Classroom Goal Orientation and Achievement
What is of interest in the current investigation is not the actual learning goal
structure itself, but rather students’ perception of the goal structure. While it is difficult
to ascertain the exact goal structure of a classroom, students’ undoubtedly form
perceptions about their learning environment, which impacts their beliefs and behaviors.
As evidenced by previous studies, students’ perceptions of classroom goal structure are
39
associated with their personal goal orientation (Anderman & Midgley, 1997; Church,
Elliot, & Gable, 2001; Young, 1997) and achievement (Church et al., 2001; Urdan &
Midgley, 2003).
In a recent study, Church et al. (2001) assessed the predictive role of class goal
structure on college students’ adoption of personal goal orientations and its indirect
impact on academic achievement. Adapting three categories (task engagement,
evaluation, and harsh evaluation) from Ames’ (1992) conceptual system TARGET,
which is used to differentiate goal structures according to classroom characteristics, the
researchers formed the following hypotheses. One, researchers predicted that students’
perception of the professor as being engaging in his lecture would promote the adoption
of mastery goal orientations. Results showed that students’ who perceived the goal
structure as falling under the categories of task engagement were likely to adopt mastery
goal orientations. Secondly, the researchers predicted that students’ perception of the
professor as emphasizing the importance of grades would lead to the adoption of
performance goal orientations, both approach and avoidance. Findings revealed that
those who viewed their class as being grade oriented were likely to exhibit performance
goal orientations. Lastly, the researchers hypothesized that students’ perception of the
goal structure as harsh and non-receiving would be
related to the adoption of performance avoidance goals. Data confirmed that students
who viewed their professors as being evaluative and insensitive did in fact adopt
performance avoidance goal orientations.
40
Urdan (2004) investigated the influence of the two subcategories of performance
goal structure on achievement of a sample of high school students. He predicted that
while a performance goal structure would foster an individual’s adoption of a
performance goal orientation, two pathways leading to either achievement or self-
handicapping would emerge. In particular, the researcher hypothesized that students
adopting performance approach goals would achieve academically, whereas students
adopting performance avoid goals would engage in self-handicapping that is detrimental
to their academic success. Path analysis confirmed the hypotheses. The results indicate
that the influence of perceived goal structure on motivation and performance varies from
person to person, as well as suggest that other factors may cause students to interpret the
goal structure in contrasting ways when adopting either the performance approach or
avoidance orientation.
In yet another study, Bong (2005) made the conjecture that students’ perception
of the goal structure would be linked to their personal goal orientation in general and
specific domains, and that the performance goal structure would make a more significant
impact at the general level. The association between perception of goal structure and
goal orientation was readily confirmed. Although perceived performance goal structure
was positively linked to personal performance orientation at the general level in the initial
period of data collection, supporting Urdan and Midgley’s (2003) study, it was linked to
only English achievement at the time of the third evaluation. Bong (2005) also tested
whether changes in students’ perception of the goal structure over the school year would
41
be coupled with changes in personal goal orientations. Previous research on middle
school student transition has shown that changes in perception are indeed accompanied
by changes in student goals (Anderman & Midgley, 1997; Urdan & Midgley, 2003). As
students transition to secondary school where grading is the basis of evaluation, it is then
likely that they will perceive the goal structure as more performance oriented than
mastery focused. Based on this assumption, the researcher hypothesized that a change in
perceived goal structure would be reflected even more prominently in changes in high
school students’ personal goal adoption. Findings reveal that despite perceived changes
in the class goal structure, the students’ goal orientations did not waver. This implies that
although students’ perception of school goal structure may change, their goal
orientations, which are part of their core motivational beliefs, are relatively stable upon
secondary schooling.
The above findings reveal that in general, students’ perception of goal structures
is related to their achievement outcomes. It has also been found that classroom goal
structures affect students’ adoption of personal goal orientations. However, the
understanding of the relation between goal structure and mathematics achievement is
tenuous. The following section reports the investigation of the two variables within the
specified domain of mathematics.
Perceived Classroom Goal Orientation and Math Achievement
Although many studies have investigated the relation between perceived goal
structure and personal goal orientation, few have looked at the two along with student
42
achievement outcomes. Of the studies that have examined the relation between goal
structure and achievement, some have found a positive correlation (Maehr, 1999;
Midgley & Urdan, 2001), while others have found no correlation at all (Anderman &
Midgley, 1997; Roeser, Midgley, & Urdan, 1996). In particular, Roeser et al. (1996)
found no relation between perceived goal structure and achievement when students’ past
achievement and personal goal orientation was accounted for. These findings suggested
that goal structure is more predictive of achievement when past achievement and
motivational variables are not factored in.
To corroborate the previous findings, Wolters (2004) looked at the perceived
classroom goal structure and personal goal orientation of a sample of middle school
students to ascertain its predictive utility in mathematics achievement. Results indicated
that students’ perception of the goal structure as mastery oriented generally led to their
adoption of mastery goals and decreased focus on performance avoidance goals.
However, when students entered classrooms with their existing personal goal
orientations, goal structure became less predictive of achievement as indicated by the
variance in grades. The findings support the notion that goal structure is predictive of
mathematics achievement when assuming that students enter the classroom environment
without having already adopted a personal goal orientation and when isolated from other
variables.
Urdan (2004) took a different stance, positing that although perceived goal
structure influences one’s adoption of a personal goal orientation, one’s goal orientation
43
likewise impacts one’s perception of the goal structure. Using multiple methods, the
researcher identified the goal structures of several high school classrooms. Despite being
subject to the same environmental conditions, students within the same classrooms
reported differences in their perception of the goal structure. Data analysis revealed that
these differences stemmed from the students’ personal goals and achievement.
Specifically, personal mastery goals were linked to perceptions of the classroom goal
structure as mastery focused and personal performance goal orientations were related to
perceptions of the presence of a performance oriented goal structure. This implies that the
personal beliefs that individuals bring to the classroom alter their perceptions of the
existing goal structure, which then reinforce individuals’ subjective convictions and lead
to further adoptions of goal orientations that either foster or inhibit achievement.
To further address the interaction among goal structure, personal goal orientation,
and achievement outcomes, Linnenbrink (2005) examined a sample of elementary school
students during a math unit. The researcher hypothesized that a perceived mastery goal
structure would relate to greater increases with respect to pretest and posttest scores than
other perceived goal structures. Instead, results of the study revealed that students who
perceived the goal structure to be performance approach oriented or a combination of
mastery and performance orientations, experienced greater gains in achievement test
scores. This relation between goal structure and achievement is parallel with
Harackiewicz et al.’s (2002) finding that college student achievement is related to
performance goal orientations rather than mastery orientations.
44
In sum, the research has shown that students’ perceptions of the classroom goal
structure, mastery or performance, have an influence on their academic achievement.
Together, these patterns suggest that there are potential benefits and disadvantages of
both goal structures and prompts the need to investigate the manner by which each goal
structure or perception of goal structure impacts academic achievement.
Help-Seeking and Perceived Classroom Goal Orientation
Since help seeking is an inherently social process, it is important to understand the
interactions that take place between individuals and their immediate environment.
Whether students will exhibit or inhibit help seeking behaviors will depend largely on
their perception of the environment in terms of its structure, demands, and receptivity.
Research examining goal structures has revealed that students’ perceptions of goal
structures are indeed correlated with cognitive and behavioral outcomes such as self-
handicapping and help seeking (Arbreton, 1993; Ryan, 1998; Turner, Midgley, Meyer,
Gheen, Anderman, Kang, & Patrick, 2002; Urdan, Midgley, & Anderman, 1998).
Despite the numerous investigations of perceived goal structure and help
seeking, researchers have not looked at the extent perceived goal structure explains help
seeking above that accounted for by goal orientation. Also, no systematic study has
investigated the effect of goal structure on college students’ help seeking tendencies in
large classes. Isolating the effects of goal structure from those tied with goal orientation,
Karabenick (2004) found that perceived goal structure directly and significantly predicted
students’ help seeking patterns. Differences in students’ perceived mastery goal structure
45
were related positively to help seeking approach patterns, and consistent with Ryan et
al.’s (1998) study, students’ perceptions of classrooms as performance oriented were
associated with help avoidance. Additionally, greater effects on help seeking tendencies
were found for perceptions of goal structure on performance avoidance than performance
approach patterns. This is logical since performance goal structures are expected to
foster performance avoidance, as in the case of help seeking.
Taken altogether, the results of the observed studies are consistent with findings
of the relations between goal orientations and help seeking. When other factors, such as
prior achievement and personal goal orientations are controlled for, a strong direct
correlation exists. Perceived mastery goal structure correlated with greater instrumental
help seeking, while perceived performance goal structure correlated with help avoidance
or expedient forms of help seeking.
Self-Efficacy
Self-efficacy, a concept originally introduced in the context of social cognitive
theory, has been incorporated in expectancy value theories and become an important
construct linked to human motivation and behavior. Social cognitive theory, which is
rooted in the view that individuals are change agents, asserts that people are both
products and reactants of social events. Key to this assertion is that individuals possess
beliefs that come to dominate their feelings and influence their behaviors. Among these
beliefs is the concept of self-efficacy. Bandura (1982) defines self-efficacy as “people’s
judgments of their capabilities to organize and execute courses of action required to attain
46
designated types of performances” (p.391). It is people’s beliefs about their capabilities
to perform and succeed at tasks that serve as the foundation of their engagement in
activities, rather than their actual potential. In other words, unless individuals believe
that they have the ability to govern the outcome of their actions, they will hesitate or
refrain from making any moves at all. Much empirical evidence has since supported the
relation between this construct and human behavior.
Self-Efficacy and Achievement
Expectancy-value models, central to discussions of student learning today, are
grounded in cognitive theories, which emphasize that motivation arises from individuals’
processing of beliefs. Intuitively, positive self-perceptions of ability should contribute to
cognitive engagement in tasks and yield positive academic results. Data collected on
students’ grades and standardized test scores across a series of studies revealed that
student expectancy for success, or self-efficacy, is a strong predictor of actual
performance (Eccles et al, 1989, Wigfield, 1994; Wigfield & Eccles, 1992).
In a recent study among high school students, researchers confirmed that
academic self-concept and self-efficacy were indeed related to academic performance, as
prior studies have shown (Pietsch, Walker, & Chapman, 2003). The more positive an
individual felt about his academic self in comparison to his peers the better he performed
in school, and the more competent an individual felt in accomplishing a specific task due
to previous success, the more he achieved. The results indicated that in the area of
mathematics, self-efficacy and competence related self-concept, are predictive of future
47
performance. Notably, high levels of self-efficacy and academic self-concept correlated
with high levels of achievement. While self-concept beliefs are formed on the basis of
one’s feelings about oneself, self-efficacy beliefs stem from one’s cognitive evaluation of
his competence (Pietsch, Walker, & Chapman, 2003). In other words, an individual’s
self-concept results from an affective appraisal of self, whereas self-efficacy results from
one’s questioning of his or her ability to accomplish or master certain tasks. Also, unlike
self-efficacy, researchers indicate that self-concept relies heavily on social comparisons
rather than previous experience (Pietsch, Walker, & Chapman, 2003). When individuals
evaluate themselves based on normative criteria regarding their relative standing with
their peers, they form a concept of their selves. On the other hand, self-efficacy beliefs
are developed when individuals assess their competence based on past experience and the
relative difficulty of the task presented (Pietsch, Walker, & Chapman, 2003).
As mentioned previously, although much research in this area has consistently
found a relation between self-efficacy and achievement, some studies have revealed that
while males and females differ in their self-efficacy, their actual achievement does not
vary significantly. In these cases, it may be that response biases play a role in the
differences in self-perceptions of ability (Eccles, Adler, & Meece, 1984; Pintrich &
Schunk, 2002). For example, it could be that girls take a more humble stance when
making self-judgments of competence. Another reason may be that cultural stereotypes
moderate an individual’s self-efficacy rating (Eccles, Wigfield, & Schiefeld, 1998).
According to this hypothesis, males who endorse the stereotype that males are better in
48
math and sports than females will tend to have higher self-efficacy in the two areas; on
the other hand, females who endorse the idea that girls are more linguistically capable
will hold higher self-efficacy in reading and writing.
Moreover, studies examining ethnic differences have yielded results that raise
questions about the link between self-efficacy and actual performance. Stevenson, Chen,
and Uttal (1990) found that self-efficacy perceptions were related to actual achievement
in Caucasian children but not African-American children. Similarly, Graham (1994)
found, in studying differences in competence perceptions between Caucasian and African
American children, that while self-efficacy beliefs of Caucasian children correlated with
their actual achievement, there was no link between the competence-related beliefs and
performance in African-American children.
The mixed findings point to the notion that these general self-efficacy perceptions
are not solely responsible for or accurately predictive of achievement. It is possible that
other variables are at play and that self-efficacy taken broadly is too ambiguous. The
next part of the literature review provides an in depth examination of self-efficacy to
better understand the source of discrepancies.
Math Self-Efficacy and Math Achievement
A distinctive aspect of self-efficacy research is its subject or context specific
assessment, as well as its task and problem specificity. Instead of examining an
individual’s general academic self-efficacy as it relates to performance, one would look
at self-efficacy perceptions within a particular domain, such as math. Accordingly, this
49
specific self-efficacy perception would be a better predictor of achievement in the area
than general academic self-efficacy because the subject specific self-efficacy is more
closely aligned with the subject performance outcome it theoretically predicts.
Additionally, assessing whether one feels efficacious in solving a particular problem or
completing a certain task would conceptually be a better predictor of successful solving
of the given problem or task than knowing whether one holds high self-efficacy in the
subject. Much research has demonstrated that academic self-concept or subject specific
self-efficacy indeed relate most strongly to achievement in the same subject (Joo, Bong,
& Choi, 2000; Marsh, 1992). For example, Pajares’ (2003) review of the literature on
writing self-efficacy beliefs and achievement in writing pointed consistently to the
positive relation between the two variables. Writing self-efficacy rather than general
self-efficacy predicts achievement in the writing domain. Likewise, research has
indicated that math self-efficacy relates most directly with math achievement.
In Bong’s (2002) study of the predictive utility of subject specific self-efficacy in
the English and mathematics performance of high school students, results indicated that
only English self-efficacy predicted English performance and only math self-efficacy
predicted math performance. Higher levels of English self-efficacy were associated with
higher levels of performance on the English placement test. By the same token, higher
levels of math self-efficacy were related positively to math placement test scores.
However, the predictive power of English and math self-efficacy in irrespective domains
was virtually nonexistent.
50
In a recent study, Stevens, Olivarez, Lan, and Tallent-Runnels (2004) evaluated
the impact of math self-efficacy on mathematics performance of a sample of 9
th
and 10
th
grade high school students taking algebra and geometry. Using a mathematics self-
efficacy instrument composed of Likert-type scale questions, the researchers asked
students to give their level of confidence or efficacy in correctly solving the problems.
Then, the researchers asked students to solve problems similar to the ones used to assess
their self-efficacy levels. Data gathered revealed that math self-efficacy did in fact
correlate positively with actual mathematics performance. These results were not only
significant for the total sample, but also for both the Caucasian and Hispanic subgroups.
A noteworthy part of the study is the correlation found between prior math achievement
and math self-efficacy, which is indicative of the reciprocal influence between the two
variables.
Pajares and Miller (1995) took another step in investigating the relationship
between math self-efficacy and performance of college students by introducing three
subcategories of math self-efficacy: efficacy in solving math problems, efficacy in
succeeding in math-related classes, and efficacy in performing math-related tasks.
Although data confirmed the positive relationship between all subtypes of math self-
efficacy and mathematics achievement, efficacy in solving math problems was most
predictive of math performance. This again implies that task-specific self-efficacy is a
stronger predictor of achievement than general self-efficacy.
51
Although other researchers have acknowledged the role of other motivational and
academic variables in predicting academic achievement, few have made attempts to
control for them in studying self-efficacy and achievement. Pajares and Graham (1999)
sought to fill in the gap by controlling for those variables and isolating mathematics self-
efficacy to ascertain whether it made an independent contribution to math performance.
Results showed that mathematics self-efficacy alone was indeed a good predictor of math
performance. In addition, researchers found that math self-efficacy decreased along with
a drop in math performance, over the course of the study that spanned 3 years. Whether
self-efficacy levels in fact decreased over time or were a result of students’ initial over-
calibration remains a question to be investigated.
Previous studies, such the ones described above, have all examined math self-
efficacy. While the construct of math self-efficacy and achievement in general
mathematics courses are the center of this discussion, it is important to include statistics
in the analysis because it requires, to some degree, the same skills needed for successfully
completing a traditional math course and in many college settings an alternative to taking
a traditional math class. It is also possible that math self-efficacy is correlated with
statistics self-efficacy and therefore predictive of achievement in statistics courses, or that
math self-efficacy is confined to traditional math achievement only, which further
confirms the belief that self-efficacy is more accurately predictive of subject, problem,
and task specific achievement.
52
Benson (1989) set out to assess the relationship between self-efficacy and
achievement in statistics. It was predicted that general self-efficacy and math self-
efficacy would be related to grades in a statistics course. However, the researcher found
no such relationship. Similarly, Bandalos, Yates, and Thorndike-Christ (1995) found no
relationship between math efficacy and statistics performance. Despite the disconfirming
evidence, Finney and Scraw (2003) developed measures to investigate the variables.
Rather than hypothesizing that general self-efficacy in statistics would be linked to
statistics performance, the researchers tapped into task specific self-efficacy in statistics.
The results of the study, conducted with a sample of college students taking statistics
courses, revealed that math self-efficacy in fact correlated with statistics self-efficacy and
task specific self-efficacy in statistic computations predicted statistics performance. This
implies that math self-efficacy can be generalized to domains that overlap in content and
applicable skills, such as statistics, as well as the notion that specificity governs the
predictive utility of self-efficacy in achievement.
The aforementioned research together point to an undeniable relationship between
self-efficacy and achievement. Studies revealed that subject and task specific self-
efficacies are most predictive of actual achievement. Researchers attribute such
relationships to the close alignment of the subject specific motivational belief and domain
specific aspect of evaluation. For instance, when students are asked to assess their level
of self-efficacy in math, their appraisals are more accurate than if asked to assess overall
self-efficacy in academics, which is too broadly defined.
53
Help Seeking and Self-Efficacy
While self-efficacy beliefs have been tied to students’ academic achievement,
these relations do not look at the self-perception prompted behaviors that lead to actual
performance. In order to understand how students’ motivational beliefs translate into
concrete indicators of academic achievement such as GPA and standardized test scores,
one must examine the interplay between academic self-efficacy beliefs and self-regulated
learning or help seeking.
Intuitively, as individuals develop, they will acquire a better understanding of
their own learning and know when to seek help. However, researchers have found that
adolescents refrain from academic help seeking despite their apparent need (Newman,
1990; Newman & Goldin, 1990; Ryan & Pintrich, 1997). To account for why students
avoid asking for help, Ryan, Gheen, and Midgley (1998) administered a survey to
elementary students across 10 middle schools in 3 districts to investigate the relation
between student academic self-efficacy and avoidance of help seeking. Specifically, they
proposed that students with lower self-efficacy would exhibit greater help avoidance, and
conversely, those with higher self-efficacy would demonstrate higher frequencies of help-
seeking behavior. Results of their survey revealed that student’s help-seeking avoidance
behavior was related to students’ academic self-efficacy (Ryan, Gheen, & Midgley,
1998). On an individual basis, those who were less efficacious, especially boys, avoided
seeking help. Also, despite varying degrees of help seeking across classroom contexts,
students with lower self-efficacy engaged in less help seeking.
54
In another study, Ryan and Pintrich (1997) investigated the role of motivational
influences on help-seeking behavior in math classrooms specifically. The researchers
proposed, based on prior findings, that academic self-efficacy or perceived cognitive
competence, would be positively correlated with adaptive help-seeking behavior and
negatively correlated with help-seeking avoidance. In particular, the study sought to
examine students’ self-efficacy belief of perceived social competence. Social
competence, unlike perceived academic competence, refers to one’s belief in his ability to
interact with others in the social environment, including forming relationships as well as
knowing how to approach others for help. Since help seeking involves both social and
cognitive engagement, they predicted that perceived social competence would influence
students’ tendency to seek academic help. In alignment with their hypotheses, students
who felt socially and cognitively efficacious were more likely to engage in adaptive help
seeking than those who perceived themselves as lacking in social and cognitive
competencies.
Butler (1998) put the theories of the relationship between self-efficacy and self-
regulated learning to test. Aligning the Strategic Content Learning (SCL) instructional
goals with the findings supporting the impact of individuals’ personal efficacy beliefs on
tendencies to self-regulate, Butler (1998) designed a curriculum to foster a range of
knowledge and self-efficacy beliefs that would further self-regulation. SCL instructors
provided students with support in analyzing tasks, evaluating existing knowledge and
skills, defining criteria for successful task performance, and other guidance, all
55
appropriate for boosting efficacy and further self-regulated learning behaviors. Analysis
of the results indicated that SCL instruction improved individuals’ task-specific efficacy,
knowledge about self-regulation, and demonstration of self-regulated learning strategies.
Based on the body of research, self-regulated learning and help seeking are a function of
self-efficacy and task specific self-concept beliefs.
In summary, although it is not clear as to the direction of causality, the
aforementioned studies confirm that efficacy is strongly correlated with help-seeking and
self-regulatory behaviors in the academic context. In addition, subject and task specific
self-efficacy are positively related to achievement, such as in mathematics.
Task value
Task value, a component of the modern expectancy value theory, refers to
individual’s perceptions and interpretations of the values of a particular task. According
to Eccles et al. (1983), there are four components of task value: attainment value, utility
value, intrinsic value, and cost. Attainment value, in particular, refers to the importance
individuals place on succeeding at a task. If a person seeks to engage in a task as a means
of confirming beliefs about himself, he upholds high attainment value. Utility value
refers to one’s belief about the relevance and application of a task to future goals. For
example, if a student takes mathematics courses for the sake of satisfying prerequisites
for a major, he is placing high utility value in the task. If, however, a student decides to
take math classes for pure enjoyment and challenge, he places high intrinsic value on the
task. Finally, cost refers to the negative aspects that one associates with a task.
56
Task Value and Achievement
Although earlier studies (Eccles, 1984; Pintrich & Schunk, 1996) have shown that
expectancy is predictive of achievement rather than task value, more recent research has
shown that task values not only predict course plans and career choices (Wigfield et al.,
1997; Eccles, Vida, & Barber, 2004; Meece et al., 1990), but also academic achievement
(House, 2006; Lepper, Corpus, & Iyengar, 2005; Pintrich & Schrauben, 1992; Shim &
Ryan, 2005; Yperen, 2003). In other words, students who valued tasks they engaged in
were more likely to enroll in related courses, pursue advanced studies in the domain, and
above all, achieve at higher levels than those who saw less value in the tasks.
In a study of college students, researchers found that task value related indirectly
with achievement (Pintrich & Schrauben, 1992). Particularly, students who found more
interest in the subject were more likely to engage in critical thought, exert more effort,
and utilize more self-regulatory strategies. Since cognitive engagement and self-
regulated learning have both been found to foster learning and achievement, researchers
hypothesized that students with high levels of interest in the subject would achieve at
higher levels, as an indirect result. Analyses confirmed the hypothesis, though direct ties
between the task value and achievement was not found.
To investigate task value’s direct influence on academic performance, Yperen
(2003) controlled for the personal goal orientations. In the neutral goal context, the
researcher found a positive relationship between task interest and actual performance.
However, within goal contexts, a relationship between task value and achievement held
57
only for mastery approach goal contexts. These results imply that task value is more
predictive of academic achievement when the moderating variables of goal structure and
goal orientation are controlled for.
Lepper, Corpus, and Iyengar’s (2005) examination of the relation between task
values and academic achievement yielded data that confirmed the positive influence of
intrinsic value on grades and standardized test scores. Additionally, data revealed that
extrinsic motivation, which corresponds to utility value, proved to be negatively
correlated with achievement.
In assessing the link between goal structure, personal goal orientation, and
achievement, Greene, Miller, Crowson, Duke, and Akey (2004) tapped into the concept
of perceived instrumentality, or what is better known as task value. Based on the
assumption that goal structure influences students’ adoption of personal goal orientations
and achievement indirectly, the researchers looked at task value as a possible moderating
variable. Specifically, the researchers proposed that when students perceive tasks to be
valuable and instrumental to their future goals, they would be more likely to adopt
mastery goals. In turn, students’ adoption of mastery goal orientations would yield
positive academic outcomes. Data from the study provided support for their claims,
verifying the influence of task value on achievement. However, whether task value has a
direct impact on achievement cannot be concluded since goal structure and personal goal
orientation are not accounted for.
58
In a recent study, Shim and Ryan (2005) again looked at the relationship between
intrinsic value and grades in a sample of college students. Data collected substantiated the
earlier findings that intrinsic value correlates with achievement outcomes. More
interestingly, grades moderated the students’ task value beliefs along with goal
orientations. When students received low grades, students’ performance approach goal
orientation was coupled with a decrease in intrinsic value. In the face of challenges,
however, mastery goals were not associated with fluctuations in intrinsic value. These
findings demonstrate that performance goal orientations are maladaptive despite its
positive influence on achievement outcomes.
Task Value and Math Achievement
The role of task value beliefs in math achievement has likewise been found in
cross-cultural settings (House, 2006; Rao, Meoly, & Sachs, 2000; Skaalvik & Valas,
1999). In examining the relationship between task value beliefs and achievement of
elementary students in the United States and Japan, House (2006) found that students
who enjoyed learning mathematics earned high scores on the math tests while students
who reported that math was boring tended to earn lower scores.
At an early age, students generally hold more task value, which result in higher
levels of achievement. As students transition from primary to secondary school,
however, their self-efficacy beliefs as well as their task values start to decline (Wigfield
& Eccles, 2000). Wigfield and Eccles (2000) suggested that the decrease in task value
might be the result of increasingly more difficult tasks that are harder to grasp and might
59
lead to lower levels of math achievement. Their study revealed that task value was
predictive of students’ intent to take higher math courses but not significantly related to
actual mathematics achievement. This is congruent with some of the earlier findings
supporting the notion that expectancy of success is more predictive of achievement than
task value.
In sum, task value correlates with achievement when controlling for other
variables such as personal goal orientation and perceived goal structure. Students
holding more task value generally outperformed others before adolescence. However, as
students progressed to high school and college, their task values declined. At the same
time, achievement levels in mathematics decreased. Though some studies indicated that
lower task value corresponded to the decline in math achievement, other studies have
refuted the results.
Help Seeking and Task Value
Help seeking, like any other social interaction, involves costs. These costs, a
component of one’s task value beliefs, govern whether individuals find it necessary and
worthwhile to seek assistance. As defined earlier, costs refer to any negative aspects
associated with a task. Given the task of seeking help, individuals may perceive the costs
to be anything ranging from time to social losses. Lee (1997) proposed that there are
three types of social costs or losses related to help seeking: acknowledgement of
incompetence, acknowledgement of inferiority, and acknowledgement of dependence.
Although there are other potential costs associated with help seeking, the social costs are
60
enough to prevent individuals from taking necessary actions to improve their learning or
academic achievement.
Lee (2002) investigated the influence of perceived social costs on help seeking
tendencies. The results of the study indicated that social costs indeed impact help
seeking. When social costs were higher, individuals decreased their help seeking
behaviors. For example, when help from individuals of equal status is unavailable, a
person many perceive the cost to be greater since he must seek help from those of higher
status or expertise. As a result, the person’s willingness to engage in help-seeking
behavior lowers or is inhibited entirely. On the other hand, when perceived costs were
lower, individuals exhibited more help seeking behaviors. This is expected because there
are more perceived benefits from acquiring aid than not.
In sum, the above findings corroborate with previous evidence, indicating a
correlation between various components of task value and academic achievement. In
particular, the results are suggestive that increases in intrinsic motivation are linked to
increases in achievement and that utility value is strongly correlated with decreases in
academic performance.
Summary
This chapter explored various motivational factors influencing achievement, as
well as help seeking tendencies. As a whole, studies found that motivational constructs
of personal goal orientation, perceived goal structure, self-efficacy, and task value, all
significantly impacted students’ academic performance either positively or negatively.
61
In examining the relationship between goal orientation and achievement, findings
were mixed. While some studies revealed a positive correlation between mastery goal
orientation and achievement, in general and in mathematics, and a negative correlation
between performance goal orientation and achievement, other studies refuted these
findings. Research conducted on college student samples support the conclusion that
although mastery goal orientations are associated with higher levels of cognitive
engagement, they are only predictive of interest. In contrast, performance approach goal
orientations are predictive of actual achievement in terms of teacher assigned grades in
spite of its link to lower levels of cognitive engagement or use of learning strategies. The
results, however puzzling, provide further evidence that performance approach goals,
rather than mastery goals, are directly linked to student achievement. A possible
explanation could be that because grades are assigned based on normative standards and
performance approach goal orientations match the evaluation criteria used by teachers,
performance goal orientations are more closely linked to achievement. This also may
explain why researchers have not found significant relations between performance
avoidance goal orientations and achievement, since performance avoidance behaviors are
not tied to teachers’ evaluation practices. There is also much evidence that motivational
climate or classroom goal structure is associated with students’ adoption of personal goal
orientations and achievement. Research revealed that students’ perception of the
classroom goal structure influenced their adoption of personal goal orientations.
Specifically, students who perceived the goal structure to be mastery oriented were more
62
likely to uphold mastery orientations, while those who perceived the goal structure to be
evaluative and performance based were more likely to exhibit performance goal
orientations and achieve at higher levels. Parallel with the findings on personal goal
orientation and academic achievement, students who perceived the classroom goal
structure to be performance oriented received better grades. However, studies also
revealed that when past achievement and existing personal goal orientations were
accounted for, students’ perception of goal structure had little or no impact on
achievement. In other words, personal goal orientations influenced students’ subjective
ideas about the classroom goal structure in the same way goal structure influenced their
adoption of personal goal orientations. In some cases, personal goal orientations
rendered classroom goal orientation useless in predicting achievement. This implies, in
order to gain a better understanding of the relation between goal structure, personal goal
orientation, and achievement, one must look into the objective component of classroom
goal structure and motivational climate, which include teacher practices, teacher-student
interactions, and other classroom events. With respect to help seeking tendencies,
researchers found that mastery approach goal orientations and perception of goal
structures as mastery oriented were related to the presence of help seeking behaviors. On
the other hand, performance orientations and perceptions of classroom motivational
climates as performance based were associated with an absence of help seeking. Since
students who are performance oriented or perceive the learning environment as
performance oriented focus on relative comparisons and engage in tasks for the purpose
63
of outperforming others or avoiding embarrassment, it is not surprising that they will
exhibit less help seeking behaviors, which are a reflection of their dependence.
In examining self-efficacy and achievement, researchers found that, in general,
self-efficacy perceptions were related to achievement levels. In particular, students with
high self-efficacy beliefs performed better than those with low self-efficacy. However,
some studies revealed that while males and females differed in their levels of self-
efficacy, achievement did not vary significantly. Similarly, the relation between self-
efficacy and achievement was found tenuous among ethnically diverse groups of
students. These findings point to the possibility that general self-efficacy beliefs are
influenced by other factors such as response biases or stereotypes, which play a role in
students’ forming of self-efficacy beliefs. When such beliefs are formed not solely on the
basis of one’s judgment of his or her ability to successfully complete a task, it is likely
then that self-efficacy will be less predictive of actual achievement. Research on math
self-efficacy, on the other hand, has yielded similar results. Students who held high
subject specific, math self-efficacy perceptions achieved at higher levels in the domain of
mathematics. This can be attributed to the fact that there is a direct alignment of the math
specific self-efficacy beliefs to the subject of mathematics. The correlation between
specific self-efficacy and actual achievement was further corroborated by studies
examining the predictive utility of task-specific self-efficacy. Together, self-efficacy
research indicates that when individuals are asked to gauge their ability to accomplish a
more specific and concrete task, such as mathematics, they are more accurate in their
64
self-appraisals. This may be due to the fact that prior achievement or experience in the
particular domain gives students a basis for forming specific self-efficacy beliefs, which
are then more closely aligned to future performance in the subject or task. In the case of
help seeking and self-efficacy, research revealed a positive correlation between high self-
efficacy beliefs and high frequency of help seeking behaviors. In contrast, students with
low self-efficacy beliefs exhibited help avoidance. It was further found that self-efficacy
beliefs were related to self-regulated learning. In other words, individuals with high self-
efficacy demonstrated more self-regulatory behaviors. This points to the notion that
highly efficacious students are more likely to view help-seeking as cognitive engagement
and a way to regulate their own learning, whereas those less efficacious see help seeking
as a reflection of their incompetence, much like performance avoidant students.
Lastly, research on task value and achievement indicated that there was a
significant relationship between the two variables only when other factors were
controlled for. Task value was predictive of academic performance, for example, only in
mastery approach goal contexts. Intrinsically motivated, these students learn for
learning’s sake and capture the essence of the material taught. Therefore, it is more
likely that they view the given tasks as a means of gaining a deeper understanding and
therefore valuable. In contrast, performance orientations that focus on relative ability and
standing, play a role in moderating the task value and thus make the motivational
construct less predictive of achievement. In addition, data revealed that utility value was
negatively related to achievement. This illustrates that individuals who find only utility
65
value in their tasks are extrinsically motivated and once the extrinsic reinforcements
become obsolete, they are less likely to demonstrate sustained achievement. Furthermore,
researchers found task value significantly correlated with mathematics achievement.
Studies indicated that higher interest levels in the subject were coupled with higher
mathematics performance. Likewise, lower interest in math was linked to lower math
achievement. With respect to help seeking tendencies, research revealed that cost was
most predictive. If the perceived costs of asking for assistance outweighed the benefits,
students were more likely to refrain from seeking help. All in all, the data advances the
popular conception that when students find value in learning beyond the immediate
tangibles and see more potential benefits than costs arising from help seeking, they will
achieve at much higher rates and levels. Though researchers do not agree on which
component of the expectancy value construct is more predictive of achievement, the
findings clearly support the role of task value in students’ help seeking behaviors.
Together, these findings illuminate the factors underlying individuals’ help
seeking behaviors or avoidance and point to the importance of considering these variables
in facilitating student learning and achievement.
66
CHAPTER 3
METHODOLOGY
The purpose of this study was to examine motivational variables that might play a
role in students’ help-seeking behaviors and achievement in mathematics in a community
college setting. Particularly, this study scrutinized the degree to which perception of
classroom goal orientation, self-efficacy, task value, and help-seeking tendencies, predict
students’ actual help seeking through math tutoring as well as students’ actual grade
performance. The study primarily aimed to answer the following questions:
1. Are perceived goal structures, self-efficacy beliefs, and expectancy values, factors
that influence help seeking behaviors in community college students?
2. Does help seeking lead to higher achievement as compared to students who fail to
seek help?
In addition, the proposed study sought to understand the following:
3. What are students’ perceptions of the math tutoring services provided and how do
these perceptions influence their help seeking behaviors?
4. What do students who seek math tutoring expect from the services?
5. What are the barriers related to students seeking help?
Studying the relationship among the variables may yield valuable knowledge
pertaining to students’ persistent underachievement in mathematics, which will enable
community colleges to design or redesign intervention programs, such as tutoring
services that successfully foster students’ learning and achievement.
67
Participants and Setting
The unit of analysis was individual students. The sample size consisted of 309
students enrolled in Math A at a community college located in Southern California,
referred to as College X. Of the 309 students, 115 (37.2%) were male, 168 (54.4%) were
female, and 26 (8.4%) whose gender were unidentified. This sample was representative
of the college, as the percentages of students that were African-American, Asian,
Hispanic, Other Non-White, and White were 13.9, 4.9, 8.1, 49.2, 5.8, and 18.1,
respectively. This sample is appropriate because it is similar to the population of interest
– urban community college students. Accordingly, 25.2%, 17.5%, 12.3%, 0.3%, and
36.2%, fell into the age groups 20-24, 25-34, 35-54, 55 and over, and under 20. The
sample consisted of students who most likely require assistance in math, particularly,
students enrolled in Math A. Students’ GPA varied from 0.0 to 4.0 and students’ number
of units completed ranged from 0 to 100. Although students from other math classes or
disciplines can obtain tutoring from the math lab, only those who were enrolled in Math
A sections during the Fall 2007 semester were examined because Math A is a
requirement for obtaining the Associate of Arts (A.A.) degree at College X and a
prerequisite math course for all of the other math courses offered. A large sample size
(approximately N=300) and course sections (N=25) was required in order to diminish
instructor effects on students’ perception of the classroom goal structure. Sections of
Math A were taught by full-time as well as part-time instructors.
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Students enrolled in Math A were provided with information on general tutoring
services and math lab tutoring services offered by the college. Instructors announced
information regarding these services at the beginning of the semester both verbally and in
written form. Additionally, brochures were available and flyers were visibly posted
throughout the college campus during the term of investigation.
The math lab, from which data on students’ help seeking behaviors was extracted,
is a part of a campus wide tutoring service that offers individualized and small group
tutoring on a walk-in basis in a regular-sized classroom. Students are encouraged to seek
help any time from 9:30 a.m. to 6:30 p.m. Monday through Thursday and 10:00 a.m. to
3:00 p.m. Friday and Saturday. A full-time math specialist or math faculty supervises the
math lab at any given time, although paid tutors who are former and current students of
College X provide most of the tutoring. Only applicants who have successfully passed
the interview and written math exam are hired as tutors at the math lab. The tutors are
available to answer any questions related to math such as homework assignments and to
help students review for upcoming exams.
Procedure
Data collection began in Fall 2007. The researcher first obtained IRB approval
from the appropriate institution and permission from the math faculty chair to conduct
studies in the classrooms. Upon gaining permission from the math chair, all instructors
teaching Math A were invited to participate in the study. Course sections were selected
using the college’s Management Information System, which lists all sections of Math A
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and student enrollments by ID number. The statistical program SPSS was used to
identify the course sections. Surveys aimed at examining perception of classroom goal
structure, task value, math self-efficacy, and help seeking tendencies, were administered
during the middle of the16-week semester. The timing of the survey had allowed
students time to adjust to the class and to be able to answer the survey items regarding
perceived goal structure, math self-efficacy, task value, and help-seeking tendencies. The
frequency of actual help seeking through tutoring was collected using the math lab
computer system, which recorded students’ math tutoring attendance during the semester
by the number of times one’s school identification card is swiped upon entering the lab.
The researcher arranged times to sit in to observe the students in the math lab in
order to get an accurate picture of what goes on in the social contexts, including but not
limited to how receptive the tutors were to the students’ needs and how effectively the
tutoring program was delivered. Specifically, the researcher observed whether the tutors
were able to provide assistance to all the students present at the math lab during any
given period, whether tutors allotted the amount of time needed to carefully explain the
concepts to the students, whether tutors approached the students to offer assistance, and
how frequently students asked questions in the lab when they were there. Additionally,
three focus groups consisting of five students each were conducted to supplement the
observations. The focus groups were held upon the completion of the surveys to allow
students to elaborate on their tutoring experiences in the math lab. During the 20-minute
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focus group sessions, the researcher used the following guiding questions to find out
more about students’ perceptions and experiences concerning the Math Lab:
1. How did you find out and become involved with the Math Lab?
2. What characteristics do you think good tutors should possess?
3. What do you think of the Math Lab (i.e.- environment, staff)?
4. Do you feel the Math Lab contributes to student learning?
5. To what extent do you feel tutoring provided by the Math Lab help students like
yourself
6. What do you expect to gain from utilizing the lab's services?
7. What is the reason you think many students do not take advantage of the
free services that the lab has to offer?
8. Where do you think other students go when they need assistance with
their math?
9. How do you think the lab can attract more students?
10. Are there any additional comments you would like to make regarding your
experience?
Prior to administering the survey, the researcher explained the purpose of the
study in the Math A sections, assured students of confidentiality, and obtained consents
from the student participants. Students were then asked to complete a 43-item survey
consisting of 40 Likert scale items to be answered on a scantron provided by the
researcher and 3 open-ended questions to be answered on the last page of the survey.
The researcher administered all surveys at the beginning of the class period. Students
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then deposited the completed surveys, including student identification numbers, in an
envelope provided by the researcher. All surveys were collected by the researcher and
sent for data analysis.
Instruments
In order to measure the influences of all the aforementioned variables, several
instruments were utilized. The items used were adapted from the following instruments:
Patterns of Adaptive Learning Strategies (P.A.L.S), Ryan and Shim’s (2005) Help
Seeking Survey, the Value Perception Scale (Condly, 1999), and Math Self-Efficacy
Scale – Revised (Betz & Hackett, 1983).
The P.A.L.S. survey instrument (Midgley, Hruda, Anderman, Anderman,
Freeman, Gheen, Avi Kaplan, Kumar, Middleton, Nelson, Roeser, & Urdan, 2000) was
adapted to assess perceived classroom goal orientation. All items in the instrument used
a Likert scale, ranging from 1= not at all true to 5= very true. Numerous studies using
middle school students have established the validity and reliability of this instrument
(Midgley et al., 2000). Recently, the instrument was found reliable (coefficient alpha of
0.76 for classroom mastery goal structure, 0.70 for classroom performance-approach goal
structure, and 0.83 for classroom performance-avoid goal structure) for college student
populations as well (Ross, Shannon, Slisbury-Glennon, & Guarino, 2000). Specifically,
Ross et al. (2002) declared P.A.L.S. an instrument suitable for making inferences about
motivational constructs across various grade levels.
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Perceived Classroom Goal Orientation
Perception of classroom mastery goal orientation was measured using items such
as, “In our class, learning new ideas and concepts is very important,” “In our class, it’s
important to understand the work, not just memorize it,” and “ In our class, really
understanding the material is the main goal,” all adapted from P.A.L.S. The internal
consistency reliability (coefficient alpha) of scores for perception of mastery goal
orientation scale was found to be 0.76 (Midgley et al., 2000).
Perception of classroom performance-approach goal orientation was assessed
utilizing the following items taken from P.A.L.S.: “In our class, it’s important to get high
scores on tests,” “In our class, getting right answers is very important,” and “In our class,
getting good grades is the main goal.” The internal consistency reliability (coefficient
alpha) of scores for perception of classroom performance-approach goal orientation scale
was found to be 0.70 (Midgley et al., 2000).
Perception of classroom performance-avoidance goal orientation was measured
using P.A.L.S. items such as, “In our class, it’s important not to look dumb,” “In our
class, one of the main goals is to avoid looking like you can’t do the work,” and “In our
class, it’s important not to do worse than other students.” The internal consistency
reliability (coefficient alpha) of scores for perception of classroom performance-
avoidance goal orientation scale was found to be 0.83 (Midgley et al., 2000).
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Math Self-Efficacy
Math self-efficacy was assessed using the following items adapted from the Math
Self-Efficacy Scale –Revised (Betz & Hackett, 1983). Students were given 10 items in
the form of math problems and asked to indicate how confident they were in giving the
correct answer to each problem without actually solving the problems on a Likert scale,
ranging from 1= not at all confident to 5 = completely confident. Items used included,
“About how many times larger than 614,360 is 30,668,000?” “If y = x/5, find x when y =
10,” and “On a certain map, 7/8 inch represents 200 miles. How far apart are two towns
whose distance apart on the map is 3 ½ inches?” The internal consistency reliability of
scores of the scale was 0.92 (Betz & Hackett, 1983).
Task Value
The Value Perception Scale developed by Condly (1999) was adapted to assess
task value. All items in the instrument use a Likert scale, ranging from 1=not at all to 5=
very much. The items used included, “How important is it to you to get a good grade in
this course?” “ How interesting do you consider the subject matter of this course to be?”
and “I feel that, to me, understanding the subject matter of this course is important.” The
internal consistency reliability (coefficient alpha) of scores for the scale was found to be
between 0.52 and 0.84 (Condly, 1999).
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Help-Seeking Attitudes and Behaviors
Ryan and Shim’s (2005) survey instrument was used to tap into students’ help-
seeking attitudes and behaviors. In particular, adaptive and avoidance of help seeking,
respectively defined as students’ tendency to request assistance and tendency to avoid
asking for help, was assessed.
Adaptive help seeking was measured using survey items such as, “If I don’t
understand my work, I usually want someone to show me the steps involved in answering
the questions,” “If I get stuck on a difficult problem, I ask someone for just enough help
so that I can keep working through it,” and “If there is something I don’t understand, I’d
prefer someone give me hints or clues rather than the answer.” The internal consistency
reliability (coefficient alpha) of the adaptive help seeking scale was found to be 0.72.
Avoidance of help seeking was assessed adapting the following items: “If I need
help to do part of my coursework, I skip it,” “If my course work is too hard for me, I just
don’t do it rather than ask for help,” and “I don’t ask questions in my classes, even when
I don’t understand the work.” The internal consistency reliability (coefficient alpha) of
the avoidance of help seeking scale was found to be 0.80.
In addition to the items mentioned above, open-ended items were included to
acquire information regarding students’ perception of the math lab and whether or not
they sought help from the math lab during the semester.
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Achievement and Ability
Students’ ability was controlled for through the college’s math placement process,
whereby a placement exam determined prior knowledge and ability in mathematics.
Mathematics achievement was defined by students’ cumulative grade point average,
which is reflective of students’ grade point average in any course taken.
Data Analysis
Factor analyses were performed to ensure that factor loadings between the survey
items and respective factors were statistically significant. The means and standard
deviations were computed for each of the items included in the survey. Cronback’s alpha
revealed that the scales were internally consistent and reliable. Item analyses confirmed
that each of the items correlated highly with the sum of the remaining items, giving
indication that the items fit well together in measuring the internal consistency of an
individual’s responses. Valid percentages were computed to exclude individuals who
responded outside the valid range for the items. Finally, regression analyses were
conducted to assess the variance in help seeking attributed to perceived goal structure,
math self-efficacy, and task value.
In sum, this chapter provided an overview of the methodology to be employed in
assessing the variables of perceived classroom goal orientation, math self-efficacy, and
task value, in relation to help seeking behaviors and tendencies. Specifically, participants
and setting, procedure, measures and sample items, and data analysis, were described in
detail.
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Research results, descriptive analyses, correlations, and structural equation
modeling, are presented in the following chapter.
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CHAPTER 4
RESULTS
This chapter first presents the statistical outcomes for the previously presented
research questions: 1) Do students’ personal goal orientations, perceptions of the
classroom goal structure, self-efficacy beliefs, and task values influence their help
seeking behaviors? 2) Do students who seek help achieve at higher levels than students
who fail to seek help? Specifically, descriptive data for the variables under study for the
309 students surveyed, including demographic information, means, standard deviations,
and intercorrelations, are presented. In the latter part of the chapter, qualitative data
synthesized from the open-ended responses on the survey and focus group discussions are
summarized.
Quantitative Findings
Descriptive Statistics
A summary of the means, standard deviations, and internal-consistency reliability
for the analysis sample is presented in Table 1. Reliability estimates for scores on
Classroom Mastery Goal Structure, Classroom Performance-Approach Goal Structure,
Classroom Performance-Avoidance Goal Structure, Adaptive Help-Seeking, Help-
Seeking Avoidance, Attainment Value, Intrinsic Value, Utility Value, and Math Self-
Efficacy were .76, .73, .80, .70, .80, .33, .89, .79, and .88, respectively. Item 22 was
excluded from the item analysis because it was the only item assessing value in terms of
cost.
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Table 1
Descriptive Statistics and Estimates of Internal-Consistency Reliability (Coefficient
Alpha)
Variable M SD Reliability
1. Class Mastery Goal Structure 4.56 0.64 0.76
2. Class Performance-Approach Goal Structure 4.14 0.76 0.73
3. Class Performance-Avoidance Goal Structure 2.13 1.08 0.80
4. Adaptive Help-Seeking 4.04 0.72 0.70
5. Help-Seeking Avoidance 2.04 0.88 0.80
6. Value In Terms Of Cost 4.15 1.03 --
7. Attainment Value 4.48 0.62 0.33
8. Intrinsic Value 3.63 1.12 0.89
9. Utility Value 3.23 1.04 0.79
10. Math Self-Efficacy 3.80 0.81 0.88
11. Age 24.93 9.01 --
12. Units Completed 23.67 20.26 --
13. Cumulative GPA 2.38 0.94 --
14. Math Grade 2.25 1.27 --
15. Group Visits 6.12 9.48 --
16. Workshops 2.27 1.67 --
17. Total Math Lab Hours 2.36 9.48 --
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Intercorrelations
A summary of the zero-order correlations for the analysis sample is presented in
Table 2. The correlation analyses yielded some interesting data. In particular, results for
the sample revealed a significant positive correlation between classroom mastery goal
structure and adaptive help seeking (r = .327, p < .001). This implies that students who
perceive the classroom goal structure as being mastery oriented are likely to exhibit
adaptive help seeking tendencies. Similarly, a significant correlation was found between
classroom performance-approach goal structure and adaptive help seeking (r = .245, p <
.001). This indicates that students who see their classroom goal structure as being
performance-approach oriented are just as likely to exhibit adaptive help-seeking
tendencies as students who perceive their classroom goal structure as mastery oriented.
However, results showed no correlation between classroom performance-avoidance goal
structure and adaptive help seeking (r = 0.012, p > .05). On the other hand, a significant
negative correlation was found between classroom mastery goal structure and help-
seeking avoidance (r = -.249, p < .001). This is expected since students who have
adaptive help seeking tendencies logically do not avoid seeking help. No correlations
yielded between classroom performance-approach goal structure and help-seeking
avoidance (r = -.041, p > .05). As predicted, a positive correlation was found between
classroom performance-avoidance goal structure and help-seeking avoidance (r = .187,
p < .01). Additionally, task value in terms of cost was found to be positive (r = .211,
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p < .001) and negative (r = -.239, p < .001) with respect to adaptive help seeking and
help-seeking avoidance, respectively. The analysis revealed comparable correlative data
between other measures of task value, including attainment value, intrinsic value, utility
value, and the two help-seeking tendencies. Specifically, a positive correlation was
found between attainment value and adaptive help seeking (r = .311, p < .001), intrinsic
value and adaptive help seeking (r = .192, p < .01), utility value and adaptive help
seeking (r = .197, p < .01). On the contrary, a negative correlation was found between
attainment value and help-seeking avoidance (r = -.315, p < .001), intrinsic value and
help-seeking avoidance (r = -.332, p < .001), and utility value and help-seeking avoidance
(r = -.241, p < .001). This implies that the more students value the task, the more likely
they are to exhibit adaptive help-seeking tendencies and less likely to avoid seeking
assistance. Results also established that a positive correlation (r = .250, p < .001) existed
between students’ math self-efficacy and adaptive help seeking, but a negative correlation
(r = -.285, p < .001) between math self-efficacy and help-seeking avoidance. This
suggests that individuals who feel more efficacious in mathematics, the more likely they
are to engage in adaptive behaviors. Despite the many significant correlations between
motivational variables (classroom mastery goal structure, classroom performance
approach goal structure, classroom performance avoidance goal structure, value in terms
of cost, attainment value, intrinsic value, utility value, and math self-efficacy) and help-
seeking tendencies, only significant relationships were found between attainment value
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and actual help-seeking behaviors as defined by the total hours of math lab usage (r =
.120, p < .05), and between math self-efficacy and actual help seeking (r = -.103, p < .05).
The data analyses also revealed significant relationships between some of the
motivational variables and math achievement, as defined by students’ semester math
grades. In particular, a significant negative correlation existed between help-seeking
avoidance and math grade (r = -.337, p < .001). This indicates that students who
exhibited higher help-seeking avoidance tendencies achieved lower grades in math for
the semester term. On the other hand, significant positive relationships were found
between various dimensions of the motivational construct value and math grade. The
positive relationships between attainment value and math grade (r = .220, p < .001),
intrinsic value and math grade (r = .220, p < .001), utility value and math grade (r = .122,
p < .05), together suggest that students achieve better grades in math when they value the
task. Similarly, a significant positive correlation was found to exist between math self-
efficacy and math grade (r = .232, p < .001). That is, the more efficacious students felt,
the more likely they were to achieve higher math grades.
Lastly, of the 21% who sought help through the math lab during the semester,
more attended group tutoring when compared with those who attended workshops. For
those who sought group tutoring at the math lab, the average attendance was about six
times during the semester (M = 6.12, SD = 9.48); for those who attended the workshops,
the average attendance was twice during the period (M = 2.27, SD = 1.67). No
differences in the frequency of help seeking were found between students enrolled in
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different sections of the prerequisite math course, which is congruent with the finding
that there is no significant correlation between perceived classroom goal structure and
students’ actual help seeking.
In sum, in assessing correlations between the variables, some results followed the
hypotheses while others were contrary to expectations. Specifically, the higher the
students’ task values, the more likely they were to exhibit adaptive help seeking
tendencies and actually seek help through math lab services, and the less likely they were
to exhibit help seeking avoidance. Although students’ math self-efficacy also related
directly to their adaptive help seeking and inversely to help seeking avoidance
tendencies, student who were high in math self-efficacy were not likely to seek help
through tutoring. Regardless of the actual help-seeking behaviors, math grades correlated
positively with task value and math self-efficacy.
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Table 2
Means, Standard Deviations, and Pearson Product Correlations for Measured Variables (N=260)
Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12
1. TM 2.36 9.48 --
2. MG 2.25 1.27 .011 --
3. GS1 4.56 .64 .102 .127 --
4. GS2 4.14 .76 .082 -.019 .358*** --
5. GS3 2.13 1.08 -.012 -.071 .043 .277*** --
6. HS1 4.04 .72 .065 .087 .327*** .245*** .012 --
7. HS2 2.04 .88 -.013 -.337*** -.249*** -.041 .187** -.169** --
8. V1 4.15 1.03 .074 .129* .297*** .102 -.134* .211***-.239*** --
9. V2 4.48 .62 .120* .220*** .231*** .146** -.018 .311***-.315*** .410*** --
10. V3 3.63 1.12 .015 .220*** .159** .004 .009 .192** -.332*** .304*** .501*** --
11. V4 3.23 1.04 -.011 .122* .165** .056 .068 .197** -.241*** .305*** .438*** .557*** --
12. MSE 3.80 .81 -.103* .232*** .216*** .109* -.058 .250***-.285*** .211*** .207*** .287*** .174*** --
Note: TM = total math lab hours; MG = math grade; GS1 = classroom mastery goal structure; GS2 = classroom performance-
approach goal structure; GS3 = classroom performance-avoidance goal structure; HS1 = adaptive help-seeking; HS2 = help-
seeking avoidance; V1 = value in terms of cost; V2 = attainment value; V3 = Intrinsic Value; V4 = Utility Value; MSE = Math
Self-Efficacy. * p < .05; ** p < .01; *** p < .001
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Research Question 1
Do students’ personal goal orientations, perceptions of the classroom goal
structure, self-efficacy beliefs, and task values influence their help seeking behaviors?
Squared multiple correlations revealed that 3.1% of the variance in adaptive help-seeking
as defined by the total number of hours spent at the math lab was accounted for by
attainment value and math self-efficacy. On the contrary, classroom goal structure and
help-seeking tendencies were not correlated to actual help seeking. Thus, hierarchical
regression analysis was performed to account for the variance in an interval dependent
(total math lab hours) based on the additive combinations of the independent variables
attainment value and math self-efficacy only. In other words, the purpose of the
regression analysis was to determine the amount of variation in total hours of help
seeking that could be accounted for by each motivational variable or combination of
variables. Particularly, the predictor variables attainment value and math self-efficacy
were entered into the model one by one for analysis because the two variables correlated
most significantly with the total number of hours spent at the math lab. Magnitude of the
relationship between the motivational variables and the total hours of math lab usage
were obtained. In this analysis, attainment value was entered as the first step since it was
most highly correlated to actual help seeking and math self-efficacy was entered as the
second step. The results of the hierarchical regression are presented in Table 3. At the
first step, attainment value explained 1.4% of variance in actual help seeking as defined
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by the total number of hours spent in the math lab (F(1, 302) = 4.169, p = .042). When
math self-efficacy was entered next, they explained 3.1% of the variance, which is an
additional 1.7% of the variance in help seeking (F (1, 301) = 5.476, p = .020). In
analyzing the standardized coefficients to assess the magnitude of the relationship
between the independent variables (attainment value and math self-efficacy) and
dependent variable (total number of hours spent at the math lab), results showed that
those participants who indicated higher attainment value attended the math lab more ( β =
.149, p = .011) and those who indicated higher math self-efficacy sought help at the math
lab less ( β = -.137, p = .020). This means that attainment value had less weight on the
outcomes of help seeking when everything else was held constant than when math self-
efficacy was included in the analysis. With the addition of math self-efficacy, which has
an inverse relationship with actual frequency of help seeking, the relationship of
attainment value and total hours of help seeking was further magnified.
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Table 3
Regression Analyses Predicting Help-Seeking Behaviors from Attainment Value and
Math Self-Efficacy
Step and Variable R R
2
B β Step 1 .117 .014
Attainment Value 1.713 .117*
Step 2 .177 .031
Attainment Value 2.181 .149*
Math Self-Efficacy -1.619 -.137*
* p < .05; ** p < .01; *** p < .001
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Research Question 2
Do students who seek help achieve at higher levels than students who fail to seek
help? Results of the regression analyses showed that there is no correlation between
math achievement and help seeking in terms of total hours spent at the math lab. The
total hours of math lab attendance did not correlate with students’ math grades for the
semester. For instance, students with higher math self-efficacy achieved higher math
grades despite their lesser tendency to seek help at the math lab. This implies that there is
no difference in the math achievement of students' who utilize the math lab and those
who do not seek help at the math lab.
Lastly, cumulative GPA was entered into the stepwise regression analysis to
determine whether it would explain any variance in help seeking. A summary of the
hierarchical regression analysis including GPA, attainment value, and math self-efficacy
is presented in Table 4. At the first step, cumulative GPA was entered. Results yielded
no correlation between the variables giving the implication that there is no significant
relationship between cumulative GPA or achievement and hours spent at the math lab,
and thus no variance can be attributed to cumulative GPA. At the second step, attainment
value explained 1.6% of variance in actual help seeking as defined by the total number of
hours spent in the math lab (F(1, 271) = 4.153, p = .043). When math self-efficacy was
entered next, they explained 3.5% of the variance, which is an additional 1.9% of the
variance in help seeking (F(1, 270) = 5.419, p = .021). In analyzing the standardized
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coefficients to assess the magnitude of the relationship between the independent variables
(attainment value and math self-efficacy) and dependent variable (total number of hours
spent at the math lab), results showed that those participants who indicated higher
attainment value attended the math lab more ( β = .149, p = .011) and those who indicated
higher math self-efficacy sought help at the math lab less ( β = -.137, p = .020). This
means that cumulative grade point average had no weight in governing the total number
of hours students sought help at the math lab, when all other variables were controlled for
and when combined with attainment value and math self-efficacy. In other words,
students’ cumulative grade point averages did not account for the discrepancies in actual
help seeking.
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Table 4
Regression Analyses Predicting Help-Seeking Behaviors from Cumulative GPA,
Attainment Value, and Math Self-Efficacy
Step and Variable R R
2
B β Step 1 .027 .001
Cumulative GPA .285 .027
Step 2 .126 .016
Cumulative GPA .024 .002
Attainment Value 1.917 .125*
Step 3 .188 .035
Cumulative GPA .300 .028
Attainment Value 2.314 .151*
Math Self-Efficacy -1.803 -.145*
*p < .05
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Qualitative Findings
To further understand the factors that contribute students’ help seeking through
math tutoring offered by the math lab, students were asked to give detailed responses for
open-ended questions that provided answers to secondary research questions: What are
students’ perceptions of the math tutoring services? What are students’ expectations of
the math tutoring services? What are the barriers related to students' help seeking?
Specifically, students were asked to answer the following two questions: 1) When you
sought tutoring from the math lab, did you get the help that you needed? 2) If you did not
go to the math lab to seek help with the math work during this course, please tell us why
you did not seek help.
Research Question 3
Responses gathered from the survey showed that students’ perceptions of the
tutoring services offered by the math lab were generally positive. This positive
perception is illustrated by the following student comments: “When I went to the math
lab, they were very helpful;” “They are very patient with you;” “The people at the math
lab are doing a great job in helping us;” “The tutors responded nicely to my questions;”
and “Yes, I have only been once for a short amount of time, however, it was a very
positive experience. The tutors approached me to help rather than me having to ask them
for help.” These comments, which are representative of most student responses, indicate
that positive perceptions relied on students’ evaluation of the overall helpfulness or
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availability of help from the math lab staff. In contrast, students who held negative
perceptions of the math lab believed that the tutors were rude, arrogant, and that the lab
was too busy and crowded. This is suggested in the following student responses: “No
one answered me. They were rude;” “There were too many people and too few tutors;”
and “I felt the person whom I asked for help for tutoring was very arrogant and had no
patience.” Here, the negative perceptions were formed based on the environmental
ambience of the math lab and students’ evaluation of tutors who they interacted with, in
terms of personal characteristics. Altogether, these findings show that students perceived
their math lab tutoring services as being positive and helpful overall, when tutors
demonstrated patience, were available to give help, and actively provided assistance, and
on the contrary, students perceived the math lab as being negative when not enough
tutors were present to accommodate students requiring help, when the environment was
not conducive for learning, and when tutors lacked patience when answering questions.
Research Question 4
With regards to student expectations of math lab services, majority of the
responses indicated that the tutoring offered by the math lab did in fact meet students’
needs and expectations. This is illustrated by the following student comments: “Yes, the
tutors pretty much teach us new or alternative techniques other than the way our
professor teaches us;” “Yes, some staff are very helpful and they have actually helped me
achieve good test scores;” “They help me with my questions and prepare me for my
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quizzes and eventually I am getting a satisfactory grade;” “It was very helpful toward me
having a better understanding;” and “I received better grades.” As a whole, students’
expectations were based on their assumptions that math lab tutoring would enhance their
success in learning math and achieving better grades on tests. When they received higher
grades, students’ considered their needs met. No specific expectations of the staff or the
type of tutoring were raised. In sum, students indicated that the math lab met their
expectations based on the degree to which they were able to perform successfully on
math tests given in their math classes.
Research Question 5
While those who attended the math lab, as a whole, pointed out that the math
tutoring offered was a positive experience that helped them achieve their goals, many
students did not go to the math lab to seek help. Among the barriers related to students’
help seeking at the math lab is the lack of time, the lack of knowledge about the tutoring
services, other sources of help, and high self-efficacy. These are illustrated by the
following student comments: “Because I already fully understand the course material;” “I
did not know when or how it was being offered;” “I have no time between full-time work
and school;” “I pretty much understand most of the work and could figure it out at home
what I have trouble with;” “I know math very well so there is no point for me to go there
and waste my time;” and “I understand the material and do almost all at home. Whatever
I don’t understand, I ask my teacher to show me the steps or help me solve them.” Of the
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reasons offered for not seeking help at the math lab, high self-efficacy was highly
reported. Many of the students felt confident in their knowledge and ability to do the
math work independently, and therefore did not attend the math lab. This is inconsistent
with the research on math self-efficacy, which indicates that only individuals with low
self-efficacy demonstrate help-avoidance (Ryan, Gheen, & Midgley, 1998). However,
the qualitative data provided is in alignment with the quantitative yield of a negative
correlation between math self-efficacy and total number of hours spent at the math lab.
This means that when students held the belief that they were capable of successfully
performing a given task and attaining productive results, they saw no need to acquire
assistance from another individual. In this case, particularly, students felt that their prior
knowledge and math instructors equipped them with the ability to work through the tasks
independently, and thus regarded math lab tutoring as unnecessary. In addition to high
math self-efficacy, lack of time was offered by a large percentage of the students as a
reason for not seeking help. This points to the little importance students placed on their
math class or grades in math and supports the quantitative finding that lower attainment
value correlates with decreased frequency in actual help seeking.
In addition to the survey responses, qualitative data was gathered from students
who volunteered to participate in the focus groups. Specifically, students were asked to
answer the following questions in detail:
1. How did you find out and become involved with the Math Lab?
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2. What characteristics do you think good tutors should possess?
3. What do you think of the Math Lab (i.e.- environment, staff)?
4. Do you feel the Math Lab contributes to student learning?
5. To what extent do you feel tutoring provided by the Math Lab help students like
yourself?
6. What do you expect to gain from utilizing the lab's services?
7. What is the reason you think many students do not take advantage of the free
services that the lab has to offer?
8. Where do you think other students go when they need assistance with their
math?
9. How do you think the lab can attract more students?
10. Are there any additional comments you would like to make regarding your
experience?
According to the responses, students who participated in the focus groups claimed
that they found out about the math lab through friends who had gone in the past.
Interestingly, although most instructors have made announcements with regard to the
availability of math lab services and flyers are widely distributed on campus, none of the
focus group students indicated those sources of information as how they discovered the
tutoring math lab offered. Most agreed that the math lab was a suitable environment for
learning and that the tutors were extremely helpful in answering questions and reviewing
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concepts. As one student indicated, “I go to the math lab because I can focus on my work
there and get help when I get stuck on problems or if I don’t understand the concepts.”
Essentially, students attended the math lab with the goal of completing an assignment and
had in mind specific questions to be answered, rather than to be given lessons on
concepts related to the chapters they were studying. Moreover, students felt that the math
lab helped them prepare of examinations in their math class and achieve higher grades, as
illustrated by a student’s comment: “Before I am about to take a test for math, I go to the
lab and go over questions with the tutors there. Usually, they help me prepare for tests
and I do better.” Again, the expectation that math lab tutoring would help them achieve
better academically emerged. When asked about the qualities they look for in tutoring
centers and tutors, students indicated patience, knowledge, and modesty, as the main
criteria. As one student stated, “Tutors who are there to help others should be patient and
not arrogant. Even though they know the material, if they don’t have patience, they
shouldn’t be there.” This is consistent with the survey responses in that tutor
characteristics contributed to students’ overall impression of math lab services. Although
they attend the math on a more frequent basis, some of the students indicated that their
peers do not take advantage of the math lab because many of them work and do not have
time to go to the lab, which again, points to the low attainment value many students held
for their math class and math grades. Lastly, when asked how the math lab can attract
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more students, the students affirmed that there was nothing the math lab can do because
some individuals will simply not go despite their apparent need.
Summary
The data gathered together point to the importance motivational variables in
influencing help seeking behaviors. It was hypothesized that classroom goal structure,
task value, and math self-efficacy would correlate with help seeking behavior, however,
classroom goal structure did not correlate with actual help seeking. Quantitative analyses
indicated attainment value and math self-efficacy correlated significantly with actual help
seeking, and qualitative data further supported the quantitative finding that math self-
efficacy helps explain students’ help seeking. Specifically, results revealed a positive
correlation between attainment value and help seeking, and conversely, a negative
correlation between math self-efficacy and help seeking. In other words, the higher
students’ attainment value, the more likely they were to seek help; whereas the higher
students’ math self-efficacy, the less likely they were to seek help. No relationship was
found between actual help seeking at the math lab and math grades for the semester,
although all dimensions of task value and math self-efficacy correlated positively with
math grades. Lastly, qualitative data indicated for those students who sought help, most
viewed their math lab experiences to be generally positive. These findings are further
discussed in Chapter 5, along with implications and recommendations for future research
and application.
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CHAPTER 5
DISCUSSION
There is an increasing body of literature suggesting that help seeking is conducive
to learning and achievement (Arbreton, 1993; Nelson Le-Gall, 1985; Karabenick, 2006).
This ability to cope with one’s academic difficulties through the assistance of others is an
important strategy that can have profound impact on one’s achievement as well as
lifelong learning. This current study extended previous research on help seeking by
examining motivational variables that might contribute to help seeking and elucidate the
persistent gap in math performance at the community college level. In particular, this
study looked at the degree to which classroom goal structure, task value, and math self-
efficacy influenced help seeking via math tutoring, and how the presence or absence of
help-seeking behaviors relates to achievement. The previous chapter provided a
quantitative analysis of the relationship between the motivational variables and the help-
seeking behaviors of community college students, including correlations and regression
analyses. In this section, insights offered by the study regarding the relationships
between motivational variables and help-seeking behavior will be discussed first,
followed by relationships between help seeking and achievement. Next, students’
perceptions and expectations of the math tutoring services will be elaborated on. Lastly,
barriers related to students' help seeking is discussed.
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Relationship Between Motivational Variables and Help-Seeking
Students' task value correlated with help-seeking behaviors. Specifically, results
revealed significant correlations between students' attainment value and total number of
hours spent at the math lab. This finding illustrates that when students place great
importance on a given task, in this case, on completing math assignments and attaining
satisfactory grades on math exams, they will more likely go to the math lab for tutoring.
In other words, students will seek help from the math lab more frequently when they
view the accomplishing of the task as being important to them. Although previous
research on task value point to cost as the indicator of the degree to which individuals are
willing and likely to ask for help in the academic context, this study has shown that
attainment value can be significant in predicting actual help-seeking behaviors (Lee,
1997). When students regard the attainment of a given task as having tremendous value,
the emphasis placed on the costs of help seeking are perhaps moderated. In spite of
having to deal with the social costs of acquiring assistance of other individuals, thus
revealing one's struggles or incapability, students will seek help via tutoring as long as
attaining the grade is valued more. In addition, since peers rather than those of higher
status provided the tutoring at the math lab, the social costs of seeking help were not as
great and thus students' attainment value took precedence.
Furthermore, math self-efficacy was also found to correlate with help seeking
through math tutoring. The quantitative analyses showed that there was a negative
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relationship between students' math self-efficacy and total number of hours spent at
the math lab. In other words, students who held higher math self-efficacy were less
likely to attend the math lab. Contrary to previous research on self-efficacy and help-
seeking, students who believed that they had the capabilities to take actions to achieve
desired outcomes were less likely to seek help through the math lab tutoring services
offered. As described in earlier chapters, the majority of the research conducted in the
past indicates that students who are more academically efficacious are more open to
asking for help and likely to take actions to seek assistance (Dweck, 1986; Dweck &
Leggett, 1988; Elliot & Dweck, 1988; Newman, 1990; Ryan, Gheen, & Midgley, 1998;
Ryan & Pintrich, 1997; Silver, Smith, & Greene, 2004). This is mainly due to the fact
that students who are more academically efficacious are more cognitively and socially
efficacious, and thus see themselves capable of acquiring assistance to achieve positive
results. However, the results of the current study raise the question as to why students
with high math self-efficacy sought help less than those with low math self-efficacy. It is
plausible that these highly efficacious students sought assistance from the math lab less
frequently because they were confident in their own ability to perform and succeed at
tasks assigned. This is supported by the finding that math self-efficacy indeed related
inversely to actual help seeking through the math lab. The positive correlation between
math self-efficacy and math grades corroborated students’ belief that they could succeed
at the mathematical tasks given to them without additional assistance. Students’ math
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self-efficacy, rather than being inflated evaluations of ability, appeared to accurately
reflect students’ abilities in the domain of mathematics. Therefore, in the current study,
math self-efficacy was predictive of actual math achievement.
With the goal of also advancing the understanding of the relationship between
classroom goal orientation and help-seeking, the current study sought to replicate
Karabenick's (2004) finding that students who perceive the classroom goal structure as
being mastery oriented would more likely seek help than students who perceive the
classroom goal structure as being performance oriented. It was expected that the
classroom goal structure, which is communicated to students in several ways, including
the perceived amount of support in the classroom, the types of tasks that are assigned,
and how students are evaluated, would have an impact on help seeking behaviors since
much research has found a significant relationship between the two variables (Ryan &
Pintrich, 1997; Ryan et al., 1998). Although the results of the current study showed a
positive correlation between mastery oriented classroom goal structure and adaptive help-
seeking and also a positive correlation between performance avoidance classroom goal
structure and help-seeking avoidance, the relationship between the various classroom
goal structures and actual frequency of help-seeking as indicated by hours spent at the
math lab was nonexistent. This implies that despite the fact that a mastery oriented
classroom goal structure may encourage students to ask questions and seek assistance in
class, classroom goal structure does not govern help seeking in the form of tutoring
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outside the classroom. However, for students who perceive their classroom goal structure
as being performance-avoidance oriented and exhibit help-seeking avoidance tendencies,
there exists a parallel in actual help-seeking via the math lab. This further suggests that
when students view their classroom goal structure as being harsh and evaluative, they
will not only adopt help avoidant tendencies within the classroom and likely not seek
help at all. Even in a context beyond the classroom in which the perception was formed,
such as the math lab, students might form preconceived notions of what the goal structure
may or may not be. Similarly, there was no relationship between classroom goal
structure and mathematics achievement. In other words, differences in students’
perception of their classroom goal structure did not correlate with students’ math grades
for the semester. This can be attributed to the fact that the brief exposure to the
classroom goal structure of their math classes during one semester was not sufficient to
alter their help seeking behaviors and math abilities dramatically. It appears that
classroom goal structure would have more profound effects in primary and secondary
settings where students remain in stable classroom settings and interact with their math
teachers on a daily basis for several semesters over the course of the year.
Relationship Between Help Seeking and Achievement
Given the existing relationships between help seeking and various motivational
factors including perceived classroom goal structure, task value, and math self-efficacy,
and the fact that help seeking contributes to achievement, one might predict that there is a
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relationship between help seeking and achievement. Contrary to past research (Allsopp,
1997; Gardner et al., 2001; Karabenick, 2003; Robinson et al., 2005; Ryan & Pintrich,
2001), there was no direct relationship between help seeking and math achievement. In
other words, students who sought help more frequently at the math lab did not achieve
higher grade point averages or higher math grades than those who sought help less during
the semester. For example, although students with high math self-efficacy exhibited
lower frequencies of help seeking through math lab tutoring services, their math grades
were comparable to that of students who sought math lab help. This implies that the
presence or absence of help seeking behaviors alone do not necessarily predict academic
achievement, or vice versa. Furthermore, this leads to the question of whether the type of
help sought contributed to the understanding of the material or merely the completion of
math assignments. It may be that students engaged in expedient help seeking or
acquiring aid for the sake of avoiding mental effort, and therefore never learned the
content. If that were the case, one would hardly expect higher achievement in math.
Only through actual adaptive help seeking could students have acquired skills that allow
them to successfully approach tasks and attain high grades in their math classes.
Student Perceptions of Math Lab Services
A synthesis of the open-ended questions on the survey and focus group responses
revealed that students generally perceived the math lab tutoring offered to be beneficial,
and the math tutors knowledgeable and helpful. On the other hand, those who perceived
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the math lab negatively attributed their attitudes to their experiences with impatient and
arrogant tutors. This is an interesting finding because the positive perceptions were based
on practical aspects of the tutoring offered, whereas the negative perceptions were based
on affect and emotion. This points to the importance of the quality of the tutors selected,
including how knowledgeable as well as how personable they are. Without interpersonal
skills that are central to helping others in the tutorial setting, even the most
knowledgeable staff will induce unwanted perceptions. The perceived amount of
patience and encouragement on the part of the tutors is instrumental in getting students to
attend the math lab on a regular basis or attend it at all.
Student Expectations of Math Lab Services
As a whole, students held the same expectations of the math tutoring services.
For one, they expected a knowledgeable staff that was expert in math and able to explain
the solutions clearly to them. Also, students attending the math lab expected that the
tutoring offered would help them review and prepare for their math exams. Last but not
least, students hoped that going to the math lab would help them achieve satisfactory
grades for the semester. For the most part, students’ expectations seem reasonable.
However, judging from the average total hours of math lab attendance (2.32 hours during
the one semester), seemingly reasonable expectations become merely wishful thoughts.
It appears unlikely that any expectations can be met when students do not seek help and
devote time to acquiring tutoring to the extent that is necessary for learning and higher
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achievement. It is therefore important to examine students’ expectations for themselves
in addition to their expectations of the math lab tutoring services, and ensure that the
expectations are congruous and realistic.
Barriers Related to Help-Seeking
According to the open-ended and focus group responses, the main barriers for
students’ help seeking are lack of time, the lack of knowledge about the tutoring services,
other sources of help, and high self-efficacy. Given that many of these community
students hold jobs while attending classes, it is understandable that students have limited
time. However, this finding raises the question of how much students value the tasks
they are given in math. Past research have found task value to be related to engagement
in critical thinking, exertion of effort, use of self-regulatory strategies, help seeking, and
achievement (Lee, 1997; Lepper et al., 2005; Pintrich & Schrauben, 1992; Shim & Ryan,
2005). Congruent with past research findings, the current study found that task value, in
particular, attainment value, was predictive of actual help seeking. In other words,
students who valued the successful completion of a task tended to seek more assistance
from the math lab tutoring services. The real barrier, is therefore not necessarily the lack
of time as most students have indicated; rather, it is the amount of value students place on
the successful attainment of mathematical tasks that hinders them from taking time away
from other activities to seek help.
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In addition to offering time as a reason for not seeking help, some students
claimed they had no knowledge of the math lab services. Again, task value emerges as a
plausible cause for help avoidance. As demonstrated by Pintrich and Schrauben (1992),
students who have higher task value are more likely to exert effort and regulate their own
learning. This implies that students with high task value can overcome barriers such as
the lack of knowledge of math lab services by actively seeking help to attain their goals.
Lastly, high math self-efficacy posed as a barrier to help seeking through math lab
tutoring. Contrary to Ryan, Gheen, and Midgley’s (1998) research finding that students
with low self-efficacy tended not to seek help, the current study found that students with
high math self-efficacy tended not to seek help. This makes sense intuitively because
students with higher math self-efficacy would feel efficacious in performing the assigned
tasks and achieving satisfactory grades independent of outside help. In other words,
students who felt capable did not seek help because they did not see the need rather than
the sole purpose of avoiding help seeking. These results point to the need to further
investigate the relationship between math self-efficacy and help seeking.
Implications
As shown in the present study, attainment value and math self-efficacy were
found to play important roles in students’ help seeking behaviors. These imply that
specific aspects of students’ motivation are central to their willingness to seek help
through tutoring. Although the findings did not substantiate past research results with
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regards to the relationship between help seeking and overall or math achievement, the
interrelationships among motivational variables, help seeking, and academic achievement
cannot be ignored and must be further explored. On the practical note, math instructors
and math lab staff can instill task value and math self-efficacy in their students
throughout the course of the semester by using teaching tips similar to those methods
outlined in the Motivated Strategies for Learning Questionnaire, also known as the
MSLQ. First, since students vary in their interest in the course content, the importance
they place on math, and beliefs about the usefulness of math, it is important to ascertain
students’ overall task value. Specifically, following methods outlined in the MSLQ,
instructors should learn and use students’ names in class, describe explicitly the value of
the material that will be covered over the semester, and assess student interests and
design activities that revolve around them. These actions not only allow students to
recognize the ways in which the tasks relate to their own learning, but also increase
students’ motivation and likelihood of developing interest and seeing value in math.
Next, in order to foster high math self-efficacy in students, instructors can ask students to
evaluate their current levels of learning from a variety of perspectives, including their
own point of view and that of other people, as well as assure students that there are
tutoring resources available to them outside of class.
In addition, Dembo and Seli’s (2004) outline for developing a strategic plan for
helping students become self-regulated learners can be employed. The outline consists of
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four stages: 1) self-observation and evaluation, 2) goal setting and strategic planning,
3) strategy-implementation and monitoring, and 4) strategic-outcome monitoring.
Specifically, students can be asked to analyze their own problems and needs, set goals
and think of strategies to achieve the goals, monitor their use of strategies, and assess the
outcomes of employing those strategies. When students are consciously able to regulate,
monitor, and evaluate their own learning, they will gain a more realistic sense of their
progress and an increased sense of math self-efficacy.
Lastly, instructors and math lab tutors can contribute to students’ motivation by
imparting the following strategies during the class or tutorial sessions. One, instructors
and tutors should explicitly explain to the students how the material builds to broader
concepts in math and how the math they are learning are not isolated facts. Next,
instructors and tutors should provide sample problems and demonstrate the key steps to
reaching the solutions. Thirdly, instructors and tutors should provide students with
practice problems that require synthesis and application of multiple concepts. Lastly, the
teaching staff should encourage students to set specific goals for each assignment or
study period. Together, the outlined strategies will help students build a more solid
mathematical foundation and help them become self-regulated learners. In terms of
resource management, instructors and the math lab staff can help students organize their
use of time and place for study by emphasizing the time management skills and the role
of the study environment. Finally, instructors and math lab staff can encourage help
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seeking behavior by asking students to discuss why they do or do not seek help, modeling
the acceptability of seeking help, asking students to analyze their own strengths and
weaknesses, and inviting students to seek help. In doing so, students will recognize that
seeking help is a normal part of the learning process.
Limitations
This study focused on only students enrolled in the sections of one particular
prerequisite math course at a community college. Differences in gender, age, and
ethnicity were not explored.
Conclusion
In sum, this study examined the degree to which goal orientation, perception of
classroom goal structure, task value, and math self-efficacy influence help seeking
through math tutoring. The quantitative and qualitative results revealed that attainment
value and math self-efficacy were significant predictors of actual help seeking.
However, the relationship between help seeking and achievement were not found in this
study. These findings imply that motivation plays a major role not only in students’ help
seeking behaviors but also overall learning. It is, therefore, vital that instructors and math
lab tutors employ strategies that enhance students’ task value and math self-efficacy, as
well as encourage help seeking behaviors, which will promote greater learning and
academic success at the community college.
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Appendix A
Recruitment Speech for Students
Hello, my name is Teresa Lai and I am a doctoral candidate in the Rossier School of
Education at the University of Southern California. USC and Los Angeles Valley
College (LAVC) are currently working together to learn more about LAVC student
success. Therefore, I would like to invite you to participate in a research study. This
study is being conducted as part of a requirement for my doctoral program. Between 400
and 500 students will be invited to participate in this study. You were selected as a
possible participant because you are a student enrolled in Math 115 here at LAVC. Your
participation is voluntary. You must be aged 18 or older to participate.
For the purpose of this study, only the principal investigator administering this survey
will see your student ID. Your responses will be held in the strictest professional
confidence. Instructors will not have access to the data collected during the course of
this research study and your answers will not influence the grade you receive in this
course.
The survey will take 20-30 minutes to complete. If you are willing to participate in this
study, you will be asked to complete a survey. Please read it carefully and sign on the
last page. Your student ID is needed to view other data for this study. If you do not
know your student ID, you should contact your class instructor. Due to privacy issues, I
cannot provide it to you. Whether or not you complete the survey, please put the paper
work it in the box located at the back of the room.
Also, I will arrange times to sit in to observe the students in the math lab in order to get
an accurate picture of what goes on in the social contexts, including but not limited to
how receptive the tutors are to the students’ needs and how effectively the tutoring
program is delivered. Specifically, I will observe whether the tutors are able to provide
assistance to all the students present at the math lab during any given period, whether
tutors allot the amount of time needed to carefully explain the concepts to the students,
whether tutors approach the students to offer assistance, and how frequently students ask
questions in the lab when they are there. If you do not want to be observed, you can let
me know in private.
Lastly, 3 focus groups consisting of 5 students each will be conducted to supplement the
survey and observations. The focus group will be held 3 times during the semester to
allow students to elaborate on their tutoring experiences in the math lab. Specifically, the
focus groups will be held at 12:00 pm, 12:30 pm, and 1:00 pm at the math lab during the
131
2
nd
Wednesday of November (November 14
th
, 2007). During the 30-minute focus group
sessions, the researcher will find out more about students’ perceptions and experiences
concerning the Math Lab. For example, students will be asked to give their opinion for a
question such as, “To what extent do you feel tutoring provided by the Math Lab help
students like yourself?” or “What do you think of the Math Lab (i.e.- environment,
staff)?”
If you volunteer to participate in one of the three focus groups consisting of 5 students
each, I would ask you to do the following things: First, please indicate that you agree to
participate in a focus group on the last page of the informed consent. Second, please
print your name on the Focus Group Sign In Sheet and indicate the time you will
participate in the focus group.
Do you have any questions or concerns?
Thank you.
132
Appendix B
Informed Consent for Students
University of Southern California
Rossier School of Education
Waite Phillips Hall 600 C
Los Angeles, CA 90089-4036
INFORMED CONSENT FOR NON-MEDICAL RESEARCH
********************************************************************
CONSENT TO PARTICIPATE IN RESEARCH (for students)
Student Success in the Community College
You are invited asked to participate in a research study conducted by Dr. Myron H.
Dembo, PhD (Faculty Advisor) and Chung-Yin Teresa Lai, M.S., (Principal Investigator)
a doctoral candidate from the Rossier School of Education at the University of Southern
California because you are a student at LAVC, attend a Math 115 class and are aged 18
or older. The results of this study will be contributed to a dissertation. A total of between
400 and 500 subjects will be selected from to participate. Your participation is voluntary.
You should read the information below, and ask questions about anything you do not
understand, before deciding whether or not to participate.
PURPOSE OF THE STUDY
The purpose of this study is to better understand how students view math tutoring
services, and how and why students use the service at a community college. This will be
accomplished by assessing students’ perceptions of the math tutoring services offered by
the Math lab, as well as help sought from the service during the semester in relation to
GPA and gender.
PROCEDURES
If you volunteer to participate in this study, we would ask you to do the following things:
You will be asked to complete a survey in class, which asks 43 questions about your
perception and use of math tutoring services at your community college, 40 Likert-scale
133
items and 3 open-ended questions. This survey will take approximately 20 to 30 minutes
to complete in class. For example, you will be asked to rate your opinion with items 1 –
40 using variations of the following scale “Not at all,” Somewhat,” and “Very true.” A
survey sample item will ask you to rate your opinion with a statement such as: “In our
class, getting good grades is the main goal.” Another example of a statement you are
asked to rate your opinion on is as follows: “In our class, learning new ideas and
concepts is very important.”
In addition to filling out a survey, you may be observed during your visits to the math
lab. I will arrange times to sit in to observe the students in the math lab in order to get an
accurate picture of what goes on in the social contexts, including but not limited to how
receptive the tutors are to the students’ needs and how effectively the tutoring program is
delivered. Specifically, I will observe whether the tutors are able to provide assistance to
all the students present at the math lab during any given period, whether tutors allot the
amount of time needed to carefully explain the concepts to the students, whether tutors
approach the students to offer assistance, and how frequently students ask questions in
the lab when they are there. If you do not want to be observed, you can let me know in
private.
Lastly, 3 focus groups consisting of 5 students each will be conducted to supplement the
survey and observations. The focus group will be held 3 times during the semester to
allow students to elaborate on their tutoring experiences in the math lab. Specifically, the
focus groups will be held at 12:00 pm, 12:30 pm, and 1:00 pm at the math lab during the
2
nd
Wednesday of November (November 14
th
, 2007). During the 30-minute focus group
sessions, the researcher will find out more about students’ perceptions and experiences
concerning the Math Lab. For example, students will be asked to give their opinion for a
question such as, “To what extent do you feel tutoring provided by the Math Lab help
students like yourself?” or “What do you think of the Math Lab (i.e.- environment,
staff)?”
If you volunteer to participate in one of the three focus groups consisting of 5 students
each, I would ask you to do the following things: First, please indicate that you agree to
participate in a focus group on the last page of the informed consent. Second, please
print your name on the Focus Group Sign In Sheet and indicate the time you will
participate in the focus group.
This study will also be looking at your GPA in relation to the surveys, and demographic
data (e.g., gender and ethnicity), which require your permission to access.
You will be asked to place your student ID number on the survey. Your responses will be
134
held in the strictest professional confidence. Instructors, or anyone else at the school,
will not have access to the information you provide on this survey and your answers will
not influence the grade you receive in this course.
POTENTIAL RISKS AND DISCOMFORTS
This study does not pose and identifiable risks beyond minor discomfort. You may be
uncomfortable due to spending time away from your studies, from your GPA being
reviewed, or concerned with the confidentiality of your answers on the survey. If you
feel discomfort you may stop and withdraw from the study at any time. Confidentiality
will be protected at all times during data collection, analysis, and presentation of the
written research report.
POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY
There will be no direct benefit to you for participating in this study. However, the
information from this study may be used to help inform decisions and improve the
academic and student support services for students.
PAYMENT/COMPENSATION FOR PARTICIPATION
You will not receive payment for your participation.
CONFIDENTIALITY
Any information that is obtained in connection with this study and that can be identified
with you will remain confidential and will be disclosed only with your permission or as
required by law.
Any personal information and data collected for the study will be coded to ensure
privacy. Only members of the research team will have access to the data associated with
this study. The data will be stored in the co-investigator’s office in a locked file
cabinet/password protected computer. The data will be destroyed upon the completion of
the study.
Course instructors will not have access to the information you provide on this survey and
your answers will not influence the grade you receive in this course. Responses will be
held in the strictest professional confidence and will only be viewed by the principal
investigator and co-investigator. The informed consent forms with your Los Angeles
Valley College ID and name will be stored separately from your completed survey so that
no connection can be made to them. When the results of the research are published or
discussed in conferences, no information will be included that would reveal your identity.
135
PARTICIPATION AND WITHDRAWAL
You can choose whether to be in this study or not. If you volunteer to be in this study,
you may withdraw at any time without consequences of any kind. You may also refuse
to answer any questions you don’t want to answer and still remain in the study. The
investigator may withdraw you from this research if circumstances arise which warrant
doing so.
ALTERNATIVES TO PARTICIPATION
Your alternative is to not participate. You can use the time to read silently or work on
class assignments.
RIGHTS OF RESEARCH SUBJECTS
You may withdraw your consent at any time and discontinue participation without
penalty. You are not waiving any legal claims, rights or remedies because of your
participation in this research study. If you have questions regarding your rights as a
research subject, contact the University Park IRB, Office of the Vice Provost for
Research Advancement, Stonier Hall, Room 224a, Los Angeles, CA 90089-1146, (213)
821-5272 or upirb@usc.edu.
IDENTIFICATION OF INVESTIGATORS
If you have any questions or concerns about the research, please feel free to contact the
Principal Investigator, Chung-Yin Teresa Lai via email at chungyil@usc.edu or Faculty
Advisor, Dr. Myron Dembo via email at dembo@usc.edu.
136
SIGNATURE OF RESEARCH SUBJECT
I have read the information provided above. I have been given a chance to ask questions.
My questions have been answered to my satisfaction, and I agree to participate in this
study. I have been given a copy of this form to keep.
□ I agree to have my demographic information accessed.
□ I do not agree to have my demographic information accessed.
□ I agree to have my GPA accessed.
□ I do not agree to have my GPA accessed.
□ I agree to have my information regarding attendance at the Math Lab accessed.
□ I do not agree to have my information regarding attendance at the Math Lab
accessed.
□ I agree to participate in a focus group.
□ I do not agree to participate in a focus group.
Student ID #: __________________________________________
Name of Subject
Signature of Subject Date
SIGNATURE OF INVESTIGATOR
I have explained the research to the subject and answered all of his/her questions. I
believe that he/she understands the information described in this document and freely
consents to participate.
Name of Investigator
Signature of Investigator Date (must be the same as
subject’s)
137
Appendix C
Recruitment Speech for Math Lab Tutors
Hello, my name is Teresa Lai and I am a doctoral candidate in the Rossier School of
Education at the University of Southern California. USC and Los Angeles Valley
College (LAVC) are currently working together to learn more about LAVC student
success. Therefore, I would like to invite you to participate in a research study. This
study is being conducted as part of a requirement for my doctoral program.
As part of my study, I will arrange times to sit in to observe the students in the math lab
in order to get an accurate picture of what goes on in the social contexts, including but
not limited to how receptive the tutors are to the students’ needs and how effectively the
tutoring program is delivered. Specifically, I will observe whether the students present
are able to acquire the assistance they need at the math lab during any given period and
how frequently students ask questions in the lab when they are there. You will not be
asked to do anything during the time you are at the math lab except to conduct tutoring as
usual. If you do not want to be observed, you can let me know in private.
Data collected from the observations will not in any way impact your work. Your
identity will also be held in the strictest professional confidence. If you do not want to be
observed, you can let me know in private.
Thank you.
138
Appendix D
Informed Consent for Math Lab Tutors
University of Southern California
Rossier School of Education
Waite Phillips Hall 600 C
Los Angeles, CA 90089-4036
INFORMED CONSENT FOR NON-MEDICAL RESEARCH
********************************************************************
CONSENT TO PARTICIPATE IN RESEARCH (tutors)
Student Success in the Community College
You are invited asked to participate in a research study conducted by Dr. Myron H.
Dembo, PhD (Faculty Advisor) and Chung-Yin Teresa Lai, M.S., (Principal Investigator)
a doctoral candidate from the Rossier School of Education at the University of Southern
California because you are a student at LAVC, attend a Math 115 class and are aged 18
or older. The results of this study will be contributed to a dissertation. Your participation
is voluntary. You should read the information below, and ask questions about anything
you do not understand, before deciding whether or not to participate.
PURPOSE OF THE STUDY
The purpose of this study is to better understand how students view math tutoring
services, and how and why students use the service at a community college. This will be
accomplished by assessing students’ perceptions of the math tutoring services offered by
the Math lab, as well as help sought from the service during the semester in relation to
GPA and gender.
PROCEDURES
If you volunteer to participate in this study, you may be observed during your tutorial
sessions at the math lab. I will arrange times to sit in to observe the students in the math
lab in order to get an accurate picture of what goes on in the social contexts, including but
not limited to how receptive the tutors are to the students’ needs and how effectively the
tutoring program is delivered. Specifically, I will observe whether all the students
present at the math lab are able to acquire the assistance they need during any given
139
period, whether tutors allot the amount of time needed to carefully explain the concepts
to the students, whether tutors approach the students to offer assistance or students
approach tutors actively for help, and how frequently students ask questions in the lab
when they are there. If you do not want to be observed, you can let me know in private.
POTENTIAL RISKS AND DISCOMFORTS
This study does not pose and identifiable risks beyond minor discomfort. You may be
uncomfortable due to being observed. If you feel discomfort you may request that the
primary investigator stops observing you. Confidentiality will be protected at all times
during data collection, analysis, and presentation of the written research report.
POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY
There will be no direct benefit to you for participating in this study. However, the
information from this study may be used to help inform decisions and improve the
academic and student support services for students.
PAYMENT/COMPENSATION FOR PARTICIPATION
You will not receive payment for your participation.
CONFIDENTIALITY
Any information that is obtained in connection with this study and that can be identified
with you will remain confidential and will be disclosed only with your permission or as
required by law.
Any personal information and data collected for the study will be coded to ensure
privacy. Only members of the research team will have access to the data associated with
this study. The data will be stored in the co-investigator’s office in a locked file
cabinet/password protected computer
The data will be destroyed upon the completion of the study.
PARTICIPATION AND WITHDRAWAL
You can choose whether to be in this study or not. If you volunteer to be in this study,
you may withdraw at any time without consequences of any kind. The investigator may
withdraw you from this research if circumstances arise which warrant doing so.
ALTERNATIVES TO PARTICIPATION
Your alternative is to not participate. You have the choice of moving to an area in the
math lab where the primary investigator will not make observations.
140
RIGHTS OF RESEARCH SUBJECTS
You may withdraw your consent at any time and discontinue participation without
penalty. You are not waiving any legal claims, rights or remedies because of your
participation in this research study. If you have questions regarding your rights as a
research subject, contact the University Park IRB, Office of the Vice Provost for
Research Advancement, Stonier Hall, Room 224a, Los Angeles, CA 90089-1146, (213)
821-5272 or upirb@usc.edu.
IDENTIFICATION OF INVESTIGATORS
If you have any questions or concerns about the research, please feel free to contact the
Principal Investigator, Chung-Yin Teresa Lai via email at chungyil@usc.edu or Faculty
Advisor, Dr. Myron Dembo via email at dembo@usc.edu.
SIGNATURE OF RESEARCH SUBJECT
I have read the information provided above. I have been given a chance to ask questions.
My questions have been answered to my satisfaction, and I agree to participate in this
study. I have been given a copy of this form to keep.
□ I agree to be observed during math lab activities.
□ I do not agree to be observed during math lab activities.
Name of Subject
Signature of Subject Date
SIGNATURE OF INVESTIGATOR
I have explained the research to the subject and answered all of his/her questions. I
believe that he/she understands the information described in this document and freely
consents to participate.
Name of Investigator
Signature of Investigator Date (must be the same as
subject’s)
141
Appendix E
Student Survey
Dear Student: Student ID# ________________
When responding to the following survey items please think about the extent to which
you have experienced the feeling or situation at LAVC. When you are finished, please
turn in your surveys and signed consent form in the box provided at the back of the room.
1 Please mark your multiple-choice responses on the scantron using a #2 pencil.
2 Please write your fill-in answers on this survey.
3 Your responses are confidential.
For questions 1-21, please fill in the circle on your scantron that best describes your
opinion using the following rating scale: 1 = Not at all true, 3 = Somewhat true, and 5 =
Very true.
Not at all true Somewhat true Very true
1 2 3 4 5
1. In our class, learning new ideas and concepts is very important.
2. In our class, it is important to understand the work, not just memorize it.
3. In our class, really understanding the material is the main goal.
4. In our class, it is important to get high scores on tests. .
5. In our class, getting right answers is very important. .
6. In our class, getting good grades is the main goal.
7. In our class, it is important not to look dumb.
8. In our class, one of the main goals is to avoid looking like you can’t do the work.
9. In our class, it is important not to do worse than other students.
10. When I don’t understand my math work in this class, I often guess instead of
asking someone for help.
11. If I don’t understand something in my math class, I usually want someone to
explain it to me and not just give me the answer.
12. I don’t ask questions in this class, even when I don’t understand the work.
13. When I don’t understand how to do something in this class, I usually want
someone to give me examples of similar problems we have done.
14. If there is something I don’t understand in this class, I’d prefer someone give me
hints or clues rather than the answer.
15. When I don’t understand my work in this class, I often put down any answer rather
than ask for help.
PLEASE CONTINUE ON THE NEXT PAGE 
142
Not at all true Somewhat true Very true
1 2 3 4 5
16. When I don’t understand my work in this class, I usually want someone to show
me the steps involved in answering the questions.
17. I usually don’t ask for help with my work in this class, even if the work is too hard
to do on my own.
18. If I need help with my math work in this class, I ask questions so the person will
provide enough information so I can figure it out myself.
19. If my math work is too hard for me, I just don’t do it rather than ask for help.
20. If I get stuck on a difficult math problem, I ask someone for just enough
help so that I can keep working through it.
21. If I need help to do part of my work in this class, I skip it.
For questions 22-30, please fill in the circle on your scantron that best represents your
response using the following rating scale: 1 = Not at all, 3 = Neutral, and 5 = Very much.
Not at all Neutral Very much
1 2 3 4 5
22. Is the amount of work it takes to do well in this course worthwhile to you?
23. How important is it to you to get a good grade in this course?
24. How much do you like learning the subject matter of this course?
25. How interesting do you consider the subject matter of this course to be?
26. How useful is learning the course content for what you want to do after you
graduate and go to work?
27. How useful is what you learn in this course for your daily life outside the school?
28. How useful is the information learned from this course for your other classes?
29. I feel that, to me, understanding the subject matter of this course is important.
30. In general, I find learning the subject matter of this course interesting.
PLEASE CONTINUE ON THE NEXT PAGE 
143
Suppose you were asked math questions 31-40. Please indicate how confident you are
that you would give the correct answer to each question without using a calculator on a
scale of 1to 5, 1 = Not confident at all, 3 = Somewhat confident, and 5 = Completely
confident. You do not have to solve any of the problems.
PLEASE DO NOT ATTEMPT TO SOLVE THE PROBLEMS.
Not at all
confident
Somewhat
confident
Completely
confident
1 2 3 4 5
31. In a certain triangle, the shortest side is 6 inches. The longest side is twice as long
as the shortest side, and the third side is 3.4 inches shorter than the longest side.
What is the sum of the three sides in inches?
32. ABOUT how many times larger than 614,360 is 30,668,000?
33. There are three numbers. The second is twice the first and the first is one-third of
the other number. Their sum is 48. Find the largest number.
34. If y = 9 + x/5, find x when y = 10.
35. A baseball player got two hits for three times at bat. This could be represented by
2/3. Which decimal would most closely represent this?
36. If P = M + N, then which of the following will be true?
I. N = P - M
II. P - N = M
III. N + M = P
37. The hands of a clock form an obtuse angle at ____ o'clock.
38. Bridget buys a packet containing 9-cent and 13-cent stamps for $2.65. If there
are 25 stamps in the packet, how many are 13-cent stamps?
39. On a certain map, 7/8 inch represents 200 miles. How far apart are two towns
whose distance apart on the map is 3 1/2 inches?
40. Five points are on a line. T is next to G. K is next to H. C is next to T. H is next
to G. Determine the positions of the points along the line.
PLEASE CONTINUE ON THE NEXT PAGE 
144
41. When you sought tutoring from the math lab, did you get the help that you
needed? Please explain to what degree the math tutoring offered helped you
achieve your goals.
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
42. If you did not go to the math lab to seek help with the math work during this
course, please tell us why you did not seek help.
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
43. How old are you? _______
Thank you for your time and attention to this survey. Please place your completed survey
and signed consent form in the box located at the back of the room.
If you have any questions regarding the statements and/or content of this survey, please
contact Teresa Lai at (626) 676-8899 or Dr Myron Dembo at (213) 740-2364.
145
Appendix F
Focus Group Questions
1. How did you find out and become involved with the Math Lab?
2. What characteristics do you think good tutors should possess?
3. What do you think of the Math Lab (i.e.- environment, staff)?
4. Do you feel the Math Lab contributes to student learning?
5. To what extent do you feel tutoring provided by the Math Lab help students like
yourself?
6. What do you expect to gain from utilizing the lab's services?
7. What is the reason you think many students do not take advantage of the
free services that the lab has to offer?
8. Where do you think other students go when they need assistance with
their math?
9. How do you think the lab can attract more students?
10. Are there any additional comments you would like to make regarding
your experience?
146

Abstract (if available)

Abstract The purpose of the current study was to examine predictor variables that might help explain the students ' lack of proficiency in mathematics at a community college. Particularly, this study scrutinized the degree to which personal goal orientation, classroom goal structure, task value, and math self-efficacy, influenced the extent of help seeking behaviors via math tutoring, and how help seeking related to math achievement. A sample of 304 students enrolled in 25 sections of a prerequisite math course at a community college participated in the study. Statistical analyses revealed that students ' attainment value and math self-efficacy influenced help seeking behaviors. Together, the attainment value and math self-efficacy accounted for approximately three percent of the variance in help seeking. However, results showed no significant relationship between help seeking and achievement.

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Asset Metadata

Creator Lai, Chung-Yin Teresa (author)

Core Title What motivational factors influence community college students' tendency to seek help through math tutoring?

School Rossier School of Education

Degree Doctor of Education

Degree Program Education

Publication Date 06/15/2008

Defense Date 04/04/2008

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

Tag help-seeking,OAI-PMH Harvest

Language English

Advisor Dembo, Myron H. (committee chair), Clark, Ginger (committee member), Shin, Luz (committee member)

Creator Email chungyil@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m1272

Unique identifier UC1274057

Identifier etd-Lai-20080615 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-71427 (legacy record id),usctheses-m1272 (legacy record id)

Legacy Identifier etd-Lai-20080615.pdf

Dmrecord 71427

Document Type Dissertation

Rights Lai, Chung-Yin Teresa

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