Injecting warm fuzzies into cold systems: defining, benchmarking, and assessing holistic, person-centered academic advising

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INJECTING WARM FUZZIES INTO COLD SYSTEMS:

DEFINING, BENCHMARKING, AND ASSESSING HOLISTIC,
PERSON-CENTERED ACADEMIC ADVISING

by

Holly Brooke Ferguson

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

December 2010

Copyright 2010 Holly Brooke Ferguson

ii
DEDICATION
To my nephew, Jack “Dodger” Kopa.

To my Nana, Peggy Ferguson; my Grandma, Mary Kalaha; my Mom, Barb Ferguson; my
sister, Krystal-Lynn “Cheezy” Ferguson-Kopa; and my brother-in-law, Randy Kopa.

To my Dad, Thomas Ferguson, Jr., whose research was the inspiration for the title of this
work – bridging the worlds of an engineer and an educator.

And to all of my teachers and mentors, thank you.

iii
ACKNOWLEDGEMENTS
My heartfelt gratitude to my dissertation committee, Dr. Kimberly Hirabayashi, Dr.
Kristan Venegas, and Dr. Jerry Lucido, for their time, patience, and guidance. A very
special thank you to Ms. Heather Cartagena, whose dedication and compassion made this
research possible. To my mentor, Dr. Michele Dunbar, thank you for being a tireless
guide, empathic confidante, and joyful friend. To Dr. Jerry Lucido, thank you for taking a
chance on my potential, trusting my work, and empowering me to grow into my own. To
Ms. Alcyone Moore and Ms. Renee Contreras, thank you for all of your work behind the
scenes to ensure my success. To Dr. Kim Hirabayashi, thank you for all of the long talks
and warm fuzzies (often disguised as kicks in the butt) that propelled me to finish this
work. Shout-outs to The Thursday Night Fam, Master Tiberius, the Little Princess, and
Mr. Henry Ford for taking this ride with me. Tons of appreciation to my partners-in-pie,
TGD and Hoolia. And to all of my family, friends, and folks I know, thank you for your
inspiration, your energy, and your love. Rock on.

iv
TABLE OF CONTENTS

Dedication ii

Acknowledgements iii

List of Tables vi

Abstract vii

Chapter 1: The Study and Its Underlying Framework 1
Overview 1
Background of the Problem 1
Statement of the Problem 5
The Case Study 7
Purpose of the Study 9
Research Questions 10
Significance of the Study 10
Methodology 11
Definition of Terms 12
Organization of the Study 13

Chapter 2: Review of the Literature 15
The Changing Student Demographic 15
The Evolution of Advising 17
An Integrative Theoretical Approach 19
Bronfenbrenner: Individual Development and the Ecology
of Systems 19
Weber: Personalization and the Malleability of Systems 21
Rogers: The Person-Centered Perspective and the
Therapeutic Relationship 23
Conclusion: Transforming History and Theory into Practice 26

Chapter 3: Research Methodology 29
Overview 29
Research Questions 30
Focus of the Study 30
Research Design 32
The Training 32
Benchmarking and Assessment of Student Contact Data 36
The Sample 37

v
Data Analysis 42
Content of Contact (RQ 1) 42
Timing of Contact (RQ 2) 45
Coding of Data 45

Chapter 4: Results 48
Analysis of the Training 48
Need for Contact 48
Holistic Review 49
Strengths-Based, Person-Centered Guidance 49
Personalized and Individualized Student Contact,
Referrals, and Follow-up 50
Research Question 1 50
Demonstrating Holistic Reviews of Student Records 51
Demonstrating Strengths-Based, Person-Centered Guidance 53
Demonstrating Personalized and Individualized Student
Contact, Referrals, and Follow-up 55
Research Question 1 Results Summary 57
Research Question 2 58
Number of Advisor Contacts per Student Record 58
Time Between System Notification and Advisor Contact 60

Chapter 5: Discussion 63
Study Findings 63
Relationship of the Training to Advising Practices 63
Quality of Academic Advisors’ Student Contact 64
Summary Discussion 67
Implications 71
Limitations 74
Conclusion 77

References 79

Appendices 85
Appendix A: Researcher-Provided Notes for Academic Advisor
Training Module Development 85
Appendix B: Coding Rubric 89

vi
LIST OF TABLES

Table 1 Mid-term Content within Sampled Student Records 39

Table 2 Advisor Training among Sampled Student Records with
Mid-term Content 40

Table 3 Mid-term Content within the College Sample by Cluster 41

Table 4 Holistic Review of Student Records with Mid-term Intervention 51

Table 5 Strengths-Based, Person-Centered Guidance in Student Records
with Mid-term Intervention 54

Table 6 Personalized and Individualized Student Contact, Referrals and
Follow-up in Student Records with Mid-term Intervention 56

Table 7 Number of Advisor Contacts per Student Record among those
Flagged as Eligible for Mid-term Intervention 59

Table 8 Time Between First System Notification and Advisor Contact
for Student Records with Mid-term Intervention 61

Table B1 Benchmark 1: Demonstrating a Holistic Review 89

Table B2 Benchmark 2: Utilizing Strengths-Based, Person-Centered
Guidance 90

Table B3 Benchmark 3: The Student Point of Contact 91

Table B4 Benchmark 4: Documentation of Referrals and Follow-Up 92

Table B5 Benchmark 5: Time 93

Table B6 Summary Data and Point Totals for Benchmarks 1 - 5 94

vii
ABSTRACT
This study examines if and how holistic, person-centered academic advising, based on
an integrative framework of educational psychology (Bronfenbrenner), sociology
(Weber), and counseling (Rogers) theories, can be fostered, implemented, and assessed at
a research university. The study design uses the coding of qualitative data and its
translation into numeric results to understand how training in the tenets of integrative
theory would affect the quality and quantity of advising content at a key juncture for
student retention, persistence, and graduation. The analysis of the data is based on
benchmarks culled from the theoretical framework, incorporated into the training, and
defined by criteria regarding holistic reviews of student records, evidence of strengths-
based, person-centered guidance, personalized and individualized student contact,
referrals, and follow-up, and the quantity and timing of advisor contacts. Results indicate
that there is a relationship between training in ecological systems and person-centered
theories and performance on a benchmarked assessment, particularly when assessing for
the quality of advising content. The relationship was more pronounced within the sample
of college student records than for those in the professional schools, leading to further
research questions regarding the specific implications of organizational infrastructure and
systems on performance outcomes. Additional questions regarding the link between
advisor motivation, training, and performance also surfaced. Overall, the study provides a
model for developing enrollment initiatives and educational programs that are not only
rooted in theory and driven by data, but are also holistic, strengths-based, and aligned to
training curriculum, benchmarked standards, and outcome-based assessments.
1

CHAPTER 1
THE STUDY AND ITS UNDERLYING FRAMEWORK
Overview
Over the past 40 years, student retention has become a critical issue for
institutions of higher education. Not only are universities charged with admitting and
enrolling diverse populations of talented students, they now must demonstrate that they
can retain and graduate a significant portion, ideally all, of their students. The student
retention rate has become a metric on which all universities are compared to each other,
as well as a measure the university uses in-house to measure performance and financial
stability (Astin, 1993, 1997). With an emphasis on the retention of students, universities
were prompted to examine their view of students, the institution’s relationship with
students, and where to locate student needs within the mission and vision of the
university system.
Background of the Problem
At first, the retention efforts of universities directed the spotlight on the students
themselves. Students were analyzed and categorized based on predictive models of how
well they would fare in the transition to university life and academia (Astin, 1997;
Camara & Echternacht, 2000; McGrath & Braunstein, 1997; Robbins, Allen, Casillas,
Peterson, & Le, 2006; Terinzini, Lorang, & Pascarella, 1981; Tinto, 1993). Essentially,
the models looked at the cost-benefit of admitting certain students and highlighted any
risk factors that may impede student progress towards graduation. In this process, a
university culture developed that situated a risk factor model as the foundation on which
2

interventionist strategies could be built (Braunstein & McGrath, 1997; Terinzini et al.,
1981; Trombley, 2001). Successfully identifying and locating “at-risk” students provided
universities with specific demographics to target for extra support, as well as clearly
delineated populations to track for their effect on the university’s overall graduation rate.
In identifying at-risk students, many universities began to scaffold services and
supports to aid the students both in their transition to college and along the path to
graduation; specific systems were put into place to aid in this process (Trombley, 2001).
The focus began to shift from attributes of individual students to conditions of the whole
system that existed or could be created within the institution to bolster student success
(Kuh, 2001, 2007; Kuh, Kinzie, Schuh, Whitt, & Associates, 2005; Pike, Kuh, & Gonyea,
2003; Smith & Robbins, 1993). Universities created offices to provide advising and
counseling in the areas of academic support, minority student services, religious life and
other systems to which students could be directed through referrals or targeted through
outreach efforts. While this retention movement was gaining momentum, the frontline
academic personnel with whom the students primarily interacted at universities was
changing (Frost, 2000). For a time, the faculty was the primary bridge between the
university and students (Gelwick, 1974; Kuh & Hu, 2001; Lamport, 1993). At many large
research universities, however, the role of faculty shifted away from curricular logistics
and more towards academic major and work life mentoring (Campbell & Campbell,
1997). In response, the field of professional academic advising emerged (Frost, 2000;
Wyckoff, 1999) and the National Academic Advising Association, or NACADA, became
the organizing body of professional advisors (Beatty, 1991). NACADA’s key
3

contributions to the field have been to outline core values of academic advising and to
initiate a movement towards professional advising standards in higher education
(Gordon, Habley, & Grites, 2008). In compiling and investigating contextually-specific
definitions of advising, NACADA identified the underlying concept of advising to be
curriculum, pedagogy, and student learning outcomes (National Academic Advising
Association, 2003, 2006). Additionally, NACADA examines trends in practice, such as
advising approaches at various institutions and time spent on advising, as well as research
on advising curriculum, pedagogy, movements, and outcomes (Beatty, 1991). Over time,
enrollment research revealed academic advising – now representing the frontline
personnel with whom students interact at the university – to be a telling variable of
student engagement and a crucial component of student retention (Crockett, 1978; Tinto,
1993, 1998). Thus, academic advising became, and continues to be, one of the primary
avenues through which the university system could interact and connect with students.
Initially, the role of academic advisor was limited to the practical implications of
supporting student progress towards degree completion – checking the sequencing of
courses and planning remaining major requirements. Institutions of higher education
essentially divided academic advisement into two parts, with different personnel
responsible for each: 1) the faculty were experts in domain specific questions related to
the student’s major and work path aspirations, and 2) the advisors served as guides to
assist students in mapping, tracking, and meeting the university’s published requirements
for timely degree completion. Additionally, the socioemotional needs of students were
often placed within a set of systems different from advising, most often within student
4

affairs (Banta & Kuh, 1998; Eickmann, 1989). Thus, student lives were
compartmentalized into the guidance they needed to progress towards graduation and the
support they needed to thrive both in and beyond the classroom. In the process, the
formation of relationships between university representatives and students was difficult to
empirically note and measure (Tinto, 1998, 2005).
The emphasis appeared to shift toward systems – academic advising as a system
within the larger context of the institution – rather than on the relational. In practice, the
university seemed to be focused more on the end-product of student graduation than on
the process of graduating students. With a systems approach in place, the academic
advisor served as a point-person when academic questions or concerns would arise for
the student. The formation of relationships between advisors and students, however, was
contextually-dependent on the nature of advising at the institution; the system dictated the
mission and function of advising at the university (Petress, 1996).
Although research catalogs numerous retention variables of interest, current
trends suggest that the development of relationships within the university system –
including academic affairs as well as student life – is essential to student persistence,
retention, and graduation (Kuh, 1996). In part, the trend is indicative of the type of
student now attending university (Howe & Strauss, 2000, 2003). Some are arriving with
contextual factors that may pose challenges to their academic success – such as poor
preparation for college-level work, limited resources in their home life and communities,
learning English as a second language, being from out of state or from another country,
or attending university for reasons other than their own. For these students, their
5

retention, persistence, and graduation may be linked to their connection to the university,
specifically their relationships with personnel who view their academic and personal lives
as interdependent and not separate. Additionally, the generation of students currently
attending university is equipped with a greater sense of the “bigger picture” – of hope for
social justice, community and personal growth, and change as products of education –
and is more driven by the relational and affective than their predecessors (Howe &
Strauss, 2000, 2003). Thus, the changing demographic of students entering college
requires university systems to evolve in order to the meet their unique needs and retain
them as students at the institution.
Statement of the Problem
The ways in which relationships between personnel and students develop within
the university system, as it pertains to students’ academic success, persistence and
graduation, need to be examined. Questions to explore are: 1) how can relationships
between individuals be constructed outside of merely the systems in which the
individuals are located, and 2) how can university advisors be proactive in engaging
students in conversations that are relevant to their academic experiences and address
students’ lives holistically? In order for academic advisors to connect with students
specifically, the content of their communication must provide more than just information
about graduation progress prompted by system indicators of risk (e.g. failing or dropping
a class, falling behind in unit progress, etc.). This requires a shift from a deficits, risk
factor model of intervention, to one founded on the strengths and assets of both students
and staff – the relational connection that enhances students’ experiences with and
6

persistence in the university system. It can be argued that, in theory, institutions
recognize the importance of the relational connection to directing and influencing student
experiences of the academy and their rates of persistence and graduation. The challenge
is that personnel representing systems within the university often struggle to manifest
theory into action (Tinto, 2005). The difficulty lies in translating the workings of a
system into the language of the people it serves, transforming the operational into the
relational.
While the evolution of advising appears to be moving towards an integrated
model meshing the conceptual framework of the profession with the relational aspect of
the practice (Andrews, Andrews, Long, & Henton, 1987; Frost, 2000; Heisserer &
Parette, 2002; Trombley, 2001), research has yet to detail how the merger of systems and
counseling theories will occur. For many advisors, their training has focused on seeing
students within the specific context of advising towards graduation and not in terms of
holistic personal guidance (Frost, 1991). Furthermore, many have not had specific
training in counseling skills and techniques that aid in the establishment of rapport and, in
turn, the development and maintenance of therapeutic relationships (Gordon, 1980;
Heisserer & Parette, 2002). If advisors were expressly taught how to view students-in-
context beyond just graduation goals, to see the limitations of depersonalized systems,
and to build empowering and engaging relationships with students, they might be
equipped better to bridge their work as institutional agents with the contextual
experiences and lived realities of their students.

7

The Case Study
This study focuses on frontline university personnel responsible for supporting
student success, persistence and graduation. Specifically, it examines how academic
advisors foster connections between the university and the students it serves. The
university at which this study was conducted—a private, research university located in an
urban area of the western United States—has made concentrated and centralized efforts
to strengthen the role of academic advisors as agents of student support, retention and
graduation. Since spring 2008, leaders in the university’s central administration have
enacted initiatives and built an infrastructure to support this effort that spans the
organizational structure of the university, consisting of a traditional liberal arts college
with departments in the humanities, arts and sciences (referred to as “the college”) and
several professional schools, including business, engineering, health professions,
communications, and others. These efforts and infrastructure include the following:
- Providing advisor training that articulates the expectations of advisors with regard
to the quality and quantity of student contact.
- Designing a central advisement database that supports the role of advisors and
provides a shared, secure space for all documentation related to advising and
contacting students.
- Implementing accountability measures and assessments of the quality and
quantity of student contact that are outlined for the college’s and the professional
schools’ leaders and advisors.
8

- Providing feedback to leaders and advisors of the college and the professional
schools about their performance on the assessments, with recommendations of
steps for improvement.
- Collecting student mid-term grades and progress reports from faculty to facilitate
early intervention student contact by academic advisors as warranted for low mid-
term grade reports.
Based on the ongoing assessments as of fall 2009, new advisors – who have
received and only been exposed to the training that articulates the theoretical approach to
student contact and relationship-building and the aligned expectations for enacting the
theory into practice with students – have met and often exceeded the performance
expectations with regard to the quality and quantity of their student contact. This suggests
the initiatives and infrastructure created, including the training, articulation of
expectations and the performance assessment, demonstrate a successful model of
advising and accountability for the university. However, despite this, there appears to
remain a gap in performance for a number of academic advisors, despite the assessment
outcomes and feedback they and their supervisors have received. Some of the ongoing
performance gaps include:
- Some advisors use a “template” or “form” for student contact that fails to provide
individualized personal guidance and engagement in the advisor-student
relationship.
- Some advisors indicate in their email contact to students that they have been
“told” or “mandated” to contact the student with the information being provided,
9

suggesting the advisor misunderstands the relationship-building intention behind
the student contact initiatives.
- A newly enacted low mid-term grade student contact initiative, by which advisors
receive early academic progress reports on students from faculty for the purpose
of prompting intervention meetings as warranted, has not yielded substantial
results – there are few student contacts being prompted by the advisors’ receipt of
mid-term grade reports.
The observed performance gaps among advisors suggest an advising culture at
this university that seems to favor a systems approach that primarily focuses on student
progress toward graduation and not on relationship-building. The question, then, is how
can a cultural shift toward a relational, strengths-based approach to advising be fostered
in a systems-focused environment?
Purpose of the Study
This study bridges theory and practice to explore whether advisor training in the
tenets of ecological systems theory and person-center theories can prompt a shift in
advising from a systems approach focused on guiding students in the requirements of
graduation to a relational approach that engages students holistically and connects them
to the institution via individuals. The purpose of the study is to determine how a culture
shift from a deficits, risk factor model of intervention to one founded on strengths and
assets can be generated in higher education through academic advisor training in and
adoption of new knowledge and skills.
10

Research Questions
The following research questions are explored in this study:
1. How does a combination of ecological systems and person-centered theories
training affect the quality of academic advisors’ contact with students, specifically
their ability to meet benchmarks demonstrating:
a. holistic reviews of student records?
b. strengths-based, person-centered guidance?
c. personalized and individualized student contact, referrals, and follow-up?
2. How does the number of advisor contacts per student record and time between
system notification and advisor contact compare between advisors who receive
training in the tenets of ecological systems theory and person-centered theories
and those who do not?
Significance of the Study
This study is an outcomes-based assessment of theory translated into practice and
measurable action. The research findings regarding the effectiveness of the training for
improved student engagement and retention provides universities with evidence-based
strategies that can be implemented broadly into their advising and counseling practices
overall, and specifically into their academic advising activities. The results of this study
offer insight to the field of professional academic advising by identifying a more
universally-accepted definition of the role, mission and vision for academic advisors in
higher education. Of special significance to the literature is that this study uses
documented advisor-student contact rather than hypothetical or role-played scenarios.
11

The university-wide database that provides the data for this study captures student record
information and all advising notes and student contacts made by academic advisors,
while also providing a longitudinal depository of both advising quality and student
progress. As a case study of advising in action, this research shows the documented
realities of efforts to turn theory into practice, as well as the possibilities of system
malleability through relational dynamics and its potential effects on individual student
progress. Furthermore, the findings of this study are applicable to educational
practitioners outside of the university setting, including K-12 schools, non-profit
organizations, and other arenas in which personnel are involved in developing,
implementing, and assessing educational programs.
Methodology
The research design of this study consists of two parts: 1) a training module on
ecological systems theory and person-centered theories presented to academic advisors,
and 2) the benchmarking and assessment of the student contact practices of advisors that
compares the quality and quantity of student contact between advisors who received the
training and a control group of advisors who did not receive the training. The outcomes
assessment is based on a qualitative content analysis of academic advisors’ documented
student contact, the data of which was retrieved from the university’s advisement
database. Independent of the training module, expectations for documentation on the
advisement database include both quality and quantity of student contact. Therefore,
some results of the analysis in this study are quantified.
12

Definition of Terms
The following is a list of terms used throughout the course of this study:
Academic advisor: A person employed by the university to guide and direct students
on the path to graduation.
Advisement database or system: A secure, online, university-wide database that stores
and collects undergraduate student information, namely demographic data, semester
course schedules, mid-term and end-of-term grades, university and student
communication, and advisor comments.
At-risk: A flag on a student’s record at mid-term indicating that the faculty of a
course believes the student is in danger of failing a class or should withdraw from a class
due to poor performance on graded work or class attendance.
Form contact: Documentation on the advisement system from an advisor to a student
that is not student-specific or individualized.
Holistic review: An advisor's documented review of a student record that
demonstrates the advisor has looked at all aspects of the student's experience, including
reviewing notes from previous meetings with the student, and looking at his or her
overall academic performance, major choice and work path, course enrollment, and life
outside the classroom.
Low mid-term grade: A grade of “at-risk” received half-way through the semester in
a specific course. An at-risk grade is assessed and reported by faculty based on five
criteria: student failed to complete/submit assignments; student has poor/no attendance;
student failed mid-term exam; student does not participate in class; student failed to meet
13

minimum standards by the mid-term cut-off. Low mid-term grades are reported by
faculty to the advisement system with the expectation that the information will be culled
by advisors and reported to students.
Mid-term grade: An early warning flag placed on a student’s record with either a
numerical or letter-grade value of faculty’s appraisal of the student’s performance in a
specific course approximately half-way through the semester.
Strengths-based, person-centered guidance: An advisor's documented contact with a
student that demonstrates the Rogerian principles of empathy/compassion, trust in the
student's abilities, a general positive regard for the student, and a focus on the student's
strengths.
Student contact or point of contact: Documentation in the student record regarding
the manner in which a student is contacted by an advisor. For example, students may be
contacted via email, phone, or in-person by an advisor.
The university: A research institution of higher learning compromised of two separate
entities: a traditional liberal arts college with departments in the humanities, arts and
sciences (referred to as “the college”) and several professional schools, including
business, engineering, health professions, communications, and others.
Organization of the Study
Chapter 1 has presented the overview of the study, the background of the
problem, the statement of the problem, the purpose of the study, the significance of the
study, and the definitions of terms.
14

Chapter 2 is a review of relevant literature. It addresses the following topics: the
changing student demographic, the evolution of advising, Bronfenbrenner’s view on
individual development and the ecology of systems, a discussion of Weber’s theory of the
personalization and malleability of systems, Rogers’ person-centered perspective and the
therapeutic relationship, transforming history and theory into practice, and a restatement
of the problem.
Chapter 3 presents the methodology used in the study, including the research
questions and research design, an overview of the training module and the training
participants, the sampling procedure and the resulting sample, and the focus of the study.
The data collection procedures and data analysis are described, including the benchmarks
and the set of conditions that need to be satisfied in order to meet an individual
benchmark.
Chapter 4 presents the results of the study, and Chapter 5 is an analysis and
discussion of the results and limitations, with conclusions and recommendations
delineated.

15

CHAPTER 2
REVIEW OF THE LITERATURE
The following literature review is designed to outline the framework for the study.
Research related to the shift in the student demographic enrolling at institutions of higher
education will first be examined. Next, research will be presented that highlights how the
field of academic advising - who does it, how the job is defined, and what the driving
forces are behind current trends in the field - began to evolve due to institutional and
professional practice pressures to meet the changing needs of students. Lastly, research
on the correlation between relationships, specifically within academic advising systems at
institutions, and student retention will be reviewed. Additionally, the theoretical basis for
understanding the person in relation to context, in relation to systems, and in relation to
others will be discussed, as well as the implications for moving from historical
perspectives and theoretical frameworks to practice.
The Changing Student Demographic
During the late 1980s, enrollment and retention research noted a shift in the
characteristics of the undergraduate student population enrolling in institutions of higher
learning. Middle-class students who once dominated the admissions radar were now
interspersed amongst a more diverse student population seeking college admission
(Gordon & Grites, 1984). Students were becoming increasingly varied in terms of race,
class, familial and contextual connection to university life, academic and social
preparation for higher education, cognitive and emotional ability to transition to a new
school context, and mental and physical struggles and strengths (Howe & Strauss, 2000;
16

Moneta & Kuh, 2005; Zis, 2002). As a result of these shifts, institutions were forced to
adapt to the needs and assets of a new type of undergraduate student: one who brought
diverse experience to the university, as well as a non-homogenous vision for what
university life should be.
For the most recent cohorts of undergraduate students, their unique experience of
the school context has sharpened the lens on relationships within and between university
systems (Kuh, 2001; Moneta & Kuh, 2005; Pike et al., 2003). Undergraduate students
today, most often referred to as “millennials,” expect guidance and feedback as part of
the educational process and, at times, are content to relinquish self-direction to the
directive support of others (Howe & Strauss, 2000; Zis, 2002). When these students
arrive on campus, they can be enmeshed in relationships with family, friends, and peers
and struggle to find voice and vision in the expanse of university life (Chickering &
Reisser, 1993; Howe & Strauss, 2000). Although students’ strengths are now more than
ever tied to affective variables and relationships, institutions of higher education, for a
time, did not note the distinct connection between the emotional or relational and
performance (Braunstein & McGrath, 1997; Pike et al., 2003). However, as more
research began to reveal the connection between the relational and university variables of
interest, such as persistence, retention, and graduation, the notion of personalized
education came into focus (Terenzini, 1993; Tinto, 1993). Research indicates that
individualized, strengths-based education may predict certain student retention variables
and, in turn, student graduation rates (Waldeck, 2007). Thus, personalized student contact
17

is a key facet of providing the new demographic of undergraduate students with the
support and guidance they need to navigate and negotiate the university system.
The Evolution of Advising
In order to meet the needs of the changing undergraduate student population in
higher education, the position of academic advisor was created. For many schools, the
faculty-mentoring model continues to be the standard for both advising and teaching
students. However, research universities in particular, have shifted from a faculty model
to a professional staff model of advisement.
Initially, the role of advisor was to be prescriptive, recommending to students the
best course of action to take to meet their needs (Brown & Rivas, 1994). In the
prescriptive model, the student is a passive recipient of directives about how to navigate
university systems, plan their courses and register for classes (Crookston, 1972). As
academic advising initiated its own internal movement towards professionalization,
however, the role of advisor shifted from a prescriptive specialist to a developmental
guide and, in some cases, counselor (Bostaph & Moore, 1980; Fielstein, 1989; Gordon,
1994; Ivey & Van Hesteren, 1990; Kadar, 2001; Raushi, 1993). Whereas prescriptive
advising is done on behalf of the student, developmental advising occurs in collaboration
with the student.
Some students prefer the prescriptive advising model because it provides directive
guidance (Brown & Rivas, 1994). However, a key criticism of the prescriptive model is
that the student never fully takes ownership as a partner in the advising process and is a
passive recipient of information. In a developmental advising model, on the other hand,
18

the student is viewed as an active partner in decision-making and problem-solving
processes (Winston, Miller, Ender, & Grites, 1984). Furthermore, the advisor is
positioned as a facilitator on the student’s educational journey, not the director
(Crookston, 1972; Ender, Winston, & Miller, 1982; Schreiner & Anderson, 2005). For
some students, the developmental model is too “hands-off,” neglecting to teach them the
conceptual and procedural knowledge necessary for tapping into and maximizing
university resources (Herndon, Kaiser, & Creamer, 1996). Advisors may see the
developmental advising model as unrealistic, putting too much strain on their time and on
departmental resources for training (Gordon, 1994).
A third perspective on advising, the intrusive model, emerged in recent years to
meet the growing number of students identified as at-risk for not persisting to graduation
(Heisserer & Parette, 2002). Under the intrusive model, the student is matched with an
advisor and mandated to receive advising services in an intentional effort to increase
student persistence, retention, and graduation (Heisserer & Parette, 2002). Research has
shown the intrusive model to be effective with specific student populations, however, as
an interventionist model, it is often limited in reach to students identified by the
institution as at-risk (Heisserer & Parette, 2002).
Overall, the evolution of advising appears to be moving towards an integrated
model of advising, a combination of guidance and counseling (Andrews et al., 1987;
Frost, 2000; Heisserer & Parette, 2002; Trombley, 2001). Despite interest in an
integrative model of advising, research has yet to detail how the merger of systems and
counseling theories is to be realized in practice.
19

An Integrative Theoretical Approach
Academic advising is a profession seeking to be rooted in theory (Creamer, 2000),
but the question of what theories to use – developmental, sociological, psychological –
remains. An integrated model of the advising practice, it seems, would have to be
founded on an integrative theoretical model linking varied theoretical focuses into a
cohesive framework. The following section details how a current view of advising can
encompass the developmental perspective (Bronfenbrenner), questions of sociological
structures (Weber), and psychological theory (Rogers). Once the theoretical views
regarding the individual student, the system of advising, and the advisor as practitioner
are clarified, questions about the application of theory to practice can be investigated.
Bronfenbrenner: Individual Development and the Ecology of Systems
Bronfenbrenner’s ecological systems model embeds the intrapersonal nature of
the individual in all of the other systems with which the individual may interact and,
reciprocally, over which the individual may exert personal agency and influence. In his
theory, Bronfenbrenner (1979) stresses the interconnectivity of the layers and the
relational reciprocity active between and amongst all systems: a primary intrapersonal
context, or microsystem, embedded in all other social and cultural domains (chrono-,
macro-, meso-, and exo- systems), that positions individual behaviors as the result of
negotiation and conceptualization of personal experience in light of interconnected
contextual factors and sets the stage for the development of the self (2004). With all of
these simultaneous relationships occurring between individuals and amongst systems, the
development of the self from an ecological perspective is essentially the perception of,
20

value for, and personal interaction within context – the individual as personal agent
(Bronfenbrenner 1975, 1979). However, simply because all of the systems are nested
within each other does not necessarily imply that they are always in synch. The impact
that the systems have on each other varies based on dynamic sociocultural forces beyond
the individual’s control. For individuals, life is not merely a measure of what they
experience or are capable of experiencing. Rather, it is how they experience and
understand their self and their self in relation to everything else around and beyond them.
Individuals are at the center of making meaning of their world, but the systems in which
they are embedded act to mediate, influence, and at times direct their involvement in
context.
Although Bronfenbrenner stressed the transactional nature of the individual and
systems in his theory – of both influencing and being influenced by each other – the
individual’s engagement with context is limited to their experience and feeling of
connectedness with the system itself. However, if the individual feels disconnected from
a system, or a specific component thereof, the desire to cease trying to relate with that
system arises and the individual, instead, focuses on the affective, relational feedback
received from another system or from the sense of self-in-isolation. Bronfenbrenner’s
theory neglects to position the individuals who are agents of the systems as crucial to the
development of individuals’ self-in-context. Individuals do not relate to or influence
systems, so much as they connect to the individuals within those systems. Additionally,
the ecological systems model aids others, including system agents, in viewing the
individual “holistically.”
21

Bronfenbrenner’s theory opens up a multitude of possibilities on how
development arises through the perceived realities of individuals and the interaction
among systems. However, the research tends to focus on when individuals struggle
within systems or when systems fail individuals. Additionally, the theoretical focus is on
each individual existing and developing within their own contextual universe – everyone,
whether an agent or an individual, belongs to their own ecology of experience and
understanding. The question is whether or not Bronfenbrenner’s holistic understanding of
the individual can translate into the relational, both between system and individual and
among ecologies. Furthermore, there is a question of whether system agents – particularly
those charged with relating to, as well as guiding and being of service to others – can
bridge their knowledge and unique understandings of contextual ecologies with the lived
experiences of those they serve. Without a relational bridge between the individual and
the system, the holistic view of person-in-context is constrained by separateness.
Weber: Personalization and the Malleability of Systems
A critical issue with Bronfenbrenner’s theory is its reliance on the interaction with
systems as a mechanism for growth and change. The systems themselves, however, do
not possess affective, relational dimensions; it is the individuals acting within or as agents
of those systems that prompt connectedness between individual and context. According
to the antipositivist theories of Weber, systems – even those designed as a resource for,
and in service to, others – by their very nature, can close themselves off into what Weber
labeled stahlhartes Gehäuse, commonly translated as the “iron cage” (Baehr & Wells,
2002; Weber, 1978, 2002). In essence, any system is prone to fall into bureaucratic rule
22

and, in time, collapse in isolation onto itself. In order to combat the tendency to become a
system for the sake of being a system, personalization and relationships are crucial. The
principal tenet of Weber’s critique is that when systems become depersonalized fixtures
of context instead of dynamic relationships among individuals, person-systems
interactions cease to be effective or to occur at all (Weber, 1978). Thus, the
personalization of the systems – of emphasizing the individuals within the system as
agents of interconnectedness – is the key.
While Bronfenbrenner’s ecological systems model sets the stage for the need to
assess self and others in relationship to social context, Weber repositions person-to-
person contact as essential to the very nature of a systems theory of development and
service. The question then arises as to how systems – some not even within the
experiential realm of the individual – can become individualized and relational, instead of
bureaucratic. For Weber, the notion of stahlhartes Gehäuse is more closely translated as
“shell as hard as steel” (Baehr & Wells, 2002; Weber, 2002). The difference in semantics
between “cage” and “shell” is the disconnect between being trapped in something (a
cage) and being held in something that one can embrace as part of growth or choose to
crack and break through (a shell). The more salient point is the fact that Weber is
referring to “steel” in his expression and not “iron” (Baehr & Wells, 2002; Weber, 2002).
Whereas iron is a naturally-occurring metal – unrelenting and unrefined, steel is created
to be flexible and malleable. While iron denotes being trapped by and within systems,
steel indicates the construction and adaptation of systems by way of human ingenuity –
through relationships and not against them.
23

The key, it appears, is to target the individuals working within systems, where
mutual influence can be exerted by both system agents and the individual. For system
agents, specific skills and knowledge training is needed in how to bridge what is
available within the system to the relational plane of the individual – a holistic appraisal
of the person-in-context. Such a training will act to personalize the system – making it
more accessible, as well as more appealing to the individual – and will prompt the
individual to engage with the system via an agent with whom the individual can feel
connected. Nonetheless, there is an inherent struggle to shift systems from their
bureaucratic tendencies to become person-centered.
Rogers: The Person-Centered Perspective and the Therapeutic Relationship
The way to bridge a holistic conceptualization of the individual with the
perspective of an agent of a system is to foster and form relationships – to create a
connection between the two parties so as to locate and build upon each other’s strengths
(the agent of the system, as expert guide and the individual, as expert on self).
Historically, it has been easier to locate individuals’ deficits – the factors that put them at
risk for not succeeding in any given domain or context – and scaffold supports around
them. If an individual were to choose not to engage with a system, the deficit model
would posit that the lack of connectedness was due to deficiencies on the part of the
individual. However, as Weber (2002) pointed out, bureaucratic shortcomings on the part
of the system can also be to blame for individual disengagement. Nonetheless, the
humanistic view of psychology, in much the same way as Bronfenbrenner’s systems
theory, positions the individual at the center of the universe of experience. In essence, it
24

is not what others think an individual can or cannot do, it is up to the individual to be
self-directive in choosing a path, including whether or not to engage with a system.
For Rogers (1961), the relational is the crucial facet of supporting individuals on
their journey of self, providing conditions conducive to change and growth. In many
ways, Rogers’ person-centered model of development guides individuals to build on their
own assets, shifting power from external forces (from contexts beyond the individual’s
direct influence) to their own sense of self-directive control. On the other hand, the theory
provides the necessary conditions for a relationship to be formed so that individual
growth and change can occur. The person-centered approach outlines how the relational
can facilitate individual development when person-to-person contact is achieved.
According to Rogers, in any system, three core conditions must be met for the
relationship to bridge the individual and an agent (usually in the role of guide):
congruence, positive regard, and empathy. Since person-to-person contact is an essential
aspect of developing the relational, the guide must model the meeting of each other in the
relationship in an authentic, genuine manner, which Rogers names congruence. In
essence, the guide sets the standard for realness as necessary to the formation of the
relationship; there is no putting on of airs or wearing of façades, there is only meeting
each other in the present and accepting the self that each brings at the time. The
relationship between the individual, now a learner in the context of the relationship, and
the guide is collaborative, but not egalitarian. They are not equals in the learning
dynamic, as they have separate, distinct roles to fulfill in the relationship.
25

Rogers’ second condition outlines how the relationship develops from the
presentations of self to the formation of a connection. Although equality is not inherent in
fostering the relationship between learner and guide, trust and acceptance are. The guide
demonstrates a fundamental positive regard for the learner to be trusted as a partner in the
process of building a relationship. Most importantly, the guide highlights the learner’s
capacity for trustworthiness, for acceptance as an individual acting in and directing their
own ecological system. The learner is met by the guide with attentiveness (e.g. nodding
head, leaning forward in chair, mirroring client affect) and calm presence (e.g. embracing
silences, using a soft voice) and is capable of self-direction, of finding answers and
knowing what to do.
The guide’s empathic understanding not only fulfills the third condition for
learning, but also nurtures a climate in which the learner can embrace the capacity for
self-direction and safely contend with any potential cognitive and affective challenges
that may arise. Empathy is the feeling generated in the relationship when the learner is
seen by the guide as facilitating their own internal processes of growth and change, and
not as a passive recipient of information. The sense of safety generated by not feeling
judged, but understood, within the context of the relationship allows the learner to
explore the ecological systems in which they are embedded and to navigate and negotiate
the systems on the learner’s own terms. The relationship between guide and learner is
thereby built on perspective-sharing, on a relational bridge between themselves as
individuals within separate, yet shared, systems of being. Although Rogers initially
intended his theory for the realm of clinical psychology, his ideas about the interpersonal
26

containing necessary conditions for learning and growth have been adapted to
educational settings (Freire, 2001). For Rogers (1969), the guide must act as the conduit
through which the learner becomes engaged in context. The guide is responsible for
creating the setting, for being with the learner in a supportive, positive manner and
empowering the learner to engage with and explore the self in context. Once a relational
bridge has been built, the system becomes personalized and the mutually influential
interaction between individual and context can be realized.
Conclusion: Transforming History and Theory into Practice
The experience of the individual can be positioned within an integrative
framework of sociological and psychological models that can be employed to examine
connections between systems and individuals, and within interpersonal relationships.
Beyond the contextual variables of institutional structure, student demographics, and
advising culture, how does an integrative theoretical model actually translate into
advising practice? To answer this question, this case study examines how history and
theory operate in practice within a specific context, subject to field training and testing,
and accompanied by measurable outcomes.
The institution that is the focus of the study, an urban research university in the
western United States, has made concentrated and centralized efforts to strengthen the
role of academic advisors as agents of student support, retention and graduation. One of
the key initiatives is the development of a long-term operations plan for systematic
student contact and follow-up at critical points of semester-by-semester academic
performance, as well as overall student progress towards graduation. The mission of the
27

plan is to increase proactive student communication and outreach through advising.
Leaders in the university’s central administration have built an infrastructure to support
this effort, including the following:
- Providing advisor training that articulates university-wide advising benchmarks
and expectations.
- Designing a central advisement database that supports the new role of advisors
and provides a shared, secure space for all documentation related to advising
students.
- Implementing accountability measures and assessments of student contact and
advising.
- Providing feedback to school administration and advisors about their performance
on the assessments, with recommendations for further growth.
Expectations for academic advisors’ documentation of student contact on the
advisement database system are usually outlined in memorandums from university
officials. When specific action steps are disseminated, the quality of advisor contact is
high, as determined by previous university assessments of advising at critical points in
students’ progress towards graduation, such as next semester registration and academic
progress by the third and fifth semester of enrollment. However, the reliance on templates
and form language that has been used to fulfill the expected action steps depersonalizes
the contact and renders it more system-based than relational. Thus, for the mid-term
grade intervention, which is the focus of this study, the expectation to complete the task
was delineated, but specific university-wide action steps were not provided. The
28

emphasis was on meeting the students where they are at and providing student and
context specific guidance, not to impose university-mandated guidelines, or a “one-size-
fits-all” model, on advisors. The mid-term grade intervention is, by design, an
opportunity for advisors to initiate contact with students who, in their estimation, would
benefit from additional attention and support. However, in the initial stages of the
intervention, it had not yielded substantial results; there were few student contacts and
even fewer advisor notes being prompted by the receipt of mid-term grades. The gap
appeared to be between having information regarding student progress and knowing what
to do with the knowledge – knowing how to bridge the system and the individual.
The next chapter outlines the research methodology and design – including the
advisor training module that was designed and delivered to equip advisors with the
knowledge and skills to build relational advising – and the data analysis used in this
study, all of which were informed by the integrative theoretical framework presented in
this chapter.

29

CHAPTER 3
RESEARCH METHODOLOGY
Overview
This study took place at a private research university located in an urban area of
the western United States. The research design is based on a qualitative assessment of
documented student contact by the university’s academic advisors, comparing the quality
and quantity of the student contact of advisors who received a training module to a
control group of advisors who did not receive the training.
1
Documentation of student
contact is recorded onto, and was retrieved from, the university’s advisement database,
the communication and documentation tool provided by the university as part of the
concentrated and centralized efforts to strengthen the role of academic advisors as agents
of student support, retention and graduation. Expectations for documentation on the
advisement database include both quality and quantity of student contact, which was
communicated to the advisors in previous routine advisor training sessions and in
memoranda about the new student contact initiatives sent by the university
administration, independent of the training module that was the focus of this study.
Benchmarks and quality conditions to determine how well each benchmark was met were
derived from the theoretical content used in the training module and were central to the
assessment of data. The overall analysis in this study is qualitative in nature, with results
quantified for ease of comparison and discussion.

1
Since the research design and student contact data used in this study were part of the university’s
professional practice of advising, the university Institutional Review Board granted the study exemption
status.
30

The primary focus of this study was to examine advising in the traditional liberal
arts college with departments in the humanities, arts and sciences (referred to as the
college). Advisors who work in one of the professional schools, as well as those who did
not attend the meeting altogether, are used as control groups against which to measure the
effectiveness of the training for advisors in the college. Comparison groups are essential
to the formation of baseline quality benchmarks for the training, as well as to
systematically note the variability in quality of advising across the university.
Research Questions
The following research questions are explored in this study:
1. How does a combination of ecological systems and person-centered theories
training affect the quality of academic advisors’ contact with students, specifically
their ability to meet benchmarks demonstrating:
a. holistic reviews of student records?
b. strengths-based, person-centered guidance?
c. personalized and individualized student contact, referrals, and follow-up?
2. How does the number of advisor contacts per student record and time between
system notification and advisor contact compare between advisors who receive
training in the tenets of ecological systems and person-centered theories and those
who do not?
Focus of the Study
Early intervention with students believed by faculty to be at-risk of failing a
course can impact and direct student progress in the course, and, ultimately, towards
31

graduation (Beck & Davidson, 2001). The theory is that when students are notified of
course standing and offered corrective action early in the semester, the number of
students successfully passing the course or withdrawing from the course in a timely
fashion is projected to increase, while the number of students failing the course, either
due to course grade or unofficial withdrawal, is projected to decrease. Thus, the low mid-
term grade notification spotlights an advising benchmark at a critical point of contact
with students. A low mid-term grade notification does not indicate that the student will
fail the course, but that the faculty believe that the student is at-risk of failing if certain
conditions are not met before the end of the semester (e.g. if attendance does not increase,
if performance on graded work does not improve). Thus, the advisor’s role at this
juncture is to discern trends in student performance and how best to guide the student.
Although the mid-term grade system affects advisors and students university-
wide, the spotlight is on the college as the cornerstone of the university’s graduation rate
and as the population most often used in comparative school research. The college not
only houses the most students of any one school on campus, with over 6,000 students
pursing majors in the college, it also is home to a significant number of students who are
either undecided in their major or who are awaiting admittance to a professional school
(undeclared). Students who are undecided or undeclared in their major may benefit
further from increased student contact and advising than those with a declared major.
Furthermore, the college has the greatest number of major departments on campus that do
not conduct mandatory in-person advising every semester—a practice that reduces the
minimum amount of expected student contact with the advisor. The professional schools,
32

on the other hand, have the greatest number of students mandated to meet with an advisor
every semester. Mandatory advisement in the professional schools is required for
students’ next semester registration clearance and coincides with the mid-term grade
reporting period.
Research Design
The study consists of two parts: first, the design and implementation of a training
module for all academic advisors at the university on ecological systems theory and
person-centered theories and second, the benchmarking and assessment of mid-term
grade student contact data on the advisement database system documented by advisors.
The assessment compared the quality and quantity of student contact by advisors who
attended the training module to those who did not (the control group). Thus, the unit of
analysis of the study is the student record, with primary variables of interest being 1)
whether the academic advisor associated with the student record attended the training
module, and 2) the academic unit to which the student record and the associated
academic advisor belong (college or professional school).
The Training
The training was designed as an addendum to the basic advising and advisement
database system training all new advisors to the university must complete, and it was
offered prior to, and in preparation for, the mid-term grade period during the semester. In
collaboration with the researcher, the university staff person responsible for providing the
routine advisor training sessions developed and delivered a presentation of the training
session content (see Appendix A for the training material notes the researcher provided to
33

the training session facilitator). Previous assessment of the university’s advisor-student
contact on other initiatives revealed that templates, often in the form of a “form email,”
had been a preferred method of contacting students, possibly due to the perceived
increased efficiency and time-saving it can produce. However, a central goal of this
training module was to reframe advisors’ student contact as highly individualized which,
in practice, would be antithetical to a template or form email. The overall focus of the
training was on the process of holistic, strengths-based advising, not on the logistical
requirements of completing a university-mandated initiative.
The training lasted 45 minutes and consisted of three phases. In phase one of the
training, the advisors were shown examples of the low mid-term grade notifications on
the system and the resulting action that was documented on the system, including
examples of the following:
1. Individualized student contact that addresses the personalized needs of the student
and contains specific student directives – where to go, with whom to speak, what
to do – regarding student academic performance and plans
2. Student contact that is depersonalized (e.g. a forwarded email of a system
notification, a mass-mailing template)
3. No action documented on the system after the low mid-term grade system
notification
The advisors were prompted to discuss and decontextualize the examples’ specificity and
note the underlying processes and mechanisms at work. Question prompts included:
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1. When should the low-grade mid-term system notification prompt the advisor to
contact the student?
2. What contact, beyond simply telling the student they have a low mid-term grade,
might be a helpful intervention?
3. How will you make referrals based on the low mid-term grade that are beneficial
to the student, especially if they do not have any prior knowledge of, or
connection to, the place to which they are being referred?
As a wrap-up of phase one, the advisors were told that the purpose of the training
was not to supply them with a template for how to conduct or document student contact;
rather, it was to develop in them an awareness of the process needed to create holistic,
person-centered contacts with students. Advisors were encouraged to examine the
connections between and within categorizations of good examples of student contact and
those that need improvement. After noting the examples’ similarities, as well as
differences, they were asked to get into groups and discuss what constitutes a good record
of student contact.
During the second phase of the training, the facilitator briefly outlined the
theoretical frameworks for approaching student contact from a relational, rather than
strictly systems, perspective. She explained how the student exists within several
different contexts, one of which is the university, and how the university and the student
are interconnected, influencing each other but also being influenced by a number of other
systems. The advisors were told that systems – even those with the best of intentions –
35

can fail to be effective or of service when they become depersonalized. Two specific
points were emphasized:
1. The student exists within numerous contexts and is best seen through a holistic
lens.
2. Individuals, such as students, relate to the people who are agents of any given
system, not the systems themselves.
The third phase of the training focused on the application of the theoretical
frameworks to advisors’ direct work with students – how advisors can form and build
relationships with students. The facilitator pointed out that, even with numerous resource
and time constraints, advisors can be learner-centered in their relationships with students
by employing three strategies:
1. Strive for authenticity and genuineness in being present with the student,
relinquishing pretense for realness.
2. Demonstrate positive regard and care for the student, locating strengths, as much
as struggles, and strive to build on the positive.
3. Show empathy for the student’s narrative and perspective, allowing the student to
be self-directive while still being present and offering guidance.
The training concluded with the facilitator explaining that the low mid-term grade
notification is merely a prompt for the advisor to conduct a holistic review of the student
record – looking at the student’s life in a number of different contexts, both within and
beyond the classroom. She further pointed out that the advisor should use professional
judgment in deciding whether or not to contact the student, as well as how best to
36

monitor and follow-up on student progress. Advisors were also informed that regardless
of whether the advisor decides to contact the student or not, all notes pertinent to the
advising process, including the rationale for contacting or not contacting a student, should
be documented on the system, in addition to all points of contact (email, phone, in-person
meeting) with students.
Training participants. All university advisors were invited to participate in the
training module; it was presented during a regularly scheduled advisor meeting about
which advisors were informed by email (following the typical procedure), as well as a
global notification posted on the advisement system. At the time of the study, there were
approximately 65 total advisors working in all of the professional schools combined, and
28 of them, or approximately 43%, attended the training. In the college, there were
approximately 45 total advisors working in all of the college academic units (clusters)
combined, and 19 of them, or approximately 42%, attended the training. Thus, nearly the
same percentage of professional school and college advisors attended the training.
Participants who attended the training varied in terms of their years of experience
as an advisor – both in the field in general, and at the university in specific – and in how
much time they are allocated to perform student-centered advising, as compared to
departmental and school administrative duties.
Benchmarking and Assessment of Student Contact Data
Benchmarks in this study serve two purposes: to clearly delineate the translation
of theory into measurable outcomes of practice and to demonstrate the standards of
evaluation employed to measure and compare the performance of the different university
37

groups in the assessment of the student contact data. For the purposes of this study, it
does not refer to the benchmarking process whereby a baseline assessment is conducted
to identify best practices or a norm to be used for comparison purposes. Rather, the
benchmarks serve as measures of particular behaviors, specifically the enactment of
knowledge and skills, in relation to an established integrative theoretical framework.
In this study, benchmarks were identified and developed from the essential
elements of the ecological systems and person-centered theories (Bronfenbrenner and
Rogers), and aligned broadly with the training module covering these theories and
presented to the advisors. Conditions of each benchmark were then developed to provide
standard criteria by which to measure the degree to which each benchmark had been met
(see Data Analysis section in this Chapter for further explication of the benchmarks and
conditions). In this way, the benchmarks and accompanying qualifying conditions used in
this study are standardized and applicable to any assessment of holistic, person-centered
approaches in education.
The Sample
At the time of data collection, there were 825 student records affiliated with the
professional schools and 528 student records affiliated with the college flagged with at
least one mid-term progress grade of at-risk from faculty, making them eligible for the
sample (students who received a letter grade at mid-term were excluded from the sample;
these students are members of special programs on campus and are subject to different
expectations for student contact). Although the total number of records eligible for
analysis appears to have been 1,353 (825 professional school and 528 college), the
38

number varied depending on when the sample was culled from the system. For example,
earlier in the study when the researcher was monitoring the progress of the mid-term
grade initiative on the advisement system, there were 1,426 records that met the criteria
for analysis. However, by the time the final data were ready to be sampled and collected,
only 1,088 records remained flagged on the system. The fluctuation in the number of
records eligible for the sample was due to administrative adjustments that were made
without the researcher’s knowledge; this will be discussed further in Chapter 5 as a
limitation to the study.
The randomized, semi-structured sampling procedure used was designed to yield
a sample of approximately 10% of the flagged/eligible student records in the professional
schools and 20% of those in the college. The college was intentionally oversampled to
account for the large heterogeneous population within the college, and because it is the
main focus of the study. The procedure for both the college and the professional schools
began with a random starting point within the student records eligible for analysis, and
sampling proceeded as described below.
The college was disaggregated into four clusters (general advising for undecided
or undeclared majors, the humanities, the natural sciences and the social sciences). In the
cases of the humanities and general advising, the clusters are official groupings of majors
by the college. For the other clusters, majors were grouped together based on the
similarity in curricular content. In order to obtain a large enough sample size within each
disaggregated cluster to make the findings meaningful, every 5
th
record within the
clustered groups was selected for analysis. This yielded a total sample size of 114 (22%
39

of all records in the college eligible for analysis). During the sampling procedure for the
professional schools, every 10
th
student record was selected within each individual school
that comprised the total professional school population, for a total of 85 sampled records
(10% of all records in the professional schools eligible for analysis). Table 1 summarizes
the number of records in the final sample that included a mid-term grade comment or
student contact, for both the college and the professional schools.

Table 1 – Mid-term Content within Sampled Student Records

Student Record
Affiliation
Total Sample of
Student
Records
Records with
Mid-term Content
# %
The College 114 48 42

Professional
Schools
85 56 66

As is shown in Table 1, there was some form of mid-term content, either advisor
contact with the student or a comment logged on the system, for 48 of the college
records, or 42% of the total sample. For the professional schools, 56 of the 85 records
sampled, or 66%, indicated some form of mid-term content by an advisor.
Once the full representative sample of student records was obtained, the advisors
who were affiliated with the sampled records of documented low mid-term grade
comment and/or student contact were compared to the list of advisors who attended the
training. Table 2 indicates the number of advisors responsible for documenting this
content who attended the training module.

40

Table 2 – Advisor Training among Sampled Student Records with Mid-term Content
Student Record
Affiliation
Records with
Mid-term
Content
Advisor Attended Training
# %
The College 48 33 69

Professional
Schools
56 28 50

For the 48 college records with mid-term content documented by an advisor, 33 of
those records, or 69%, where logged by an advisor who attended the training. In the
professional schools, 28 of the 56 records with mid-term content, or 50%, were
documented by advisors who attended the training.
Overall, the professional school advisors documented more mid-term student
contact and comments than the college, with 66% compared to 42% of the respective
samples (see Table 1). However, the mid-term contact/comments in the professional
schools were completed by fewer advisors who attended the training, compared to the
college: 50% of the records with mid-term content were documented by advisors who
attended the training, versus 69% of the records in the college (see Table 2).
Since the college is the main focus of this study, the sample is also disaggregated
by college cluster. The number of student records sampled for each cluster, as indicated
in Table 3, is representative of the total overall number of students in each cluster. The
social science and the natural science clusters, which house the larger majors in terms of
number of students within the college, have the greatest number of records sampled. The
humanities is in the middle, comprised of several smaller majors and only one major
41

comparable in number to those in the social and natural sciences. The general advising
unit is the smallest within the college, as it is responsible for a very specific population of
students that have not yet declared a major in the college. As a result, the sample sizes for
each cluster are representative of the proportion of students the cluster serves within the
larger college population.
Within the college, the general advising cluster logged the greatest percent of
mid-term content (student contacts or mid-term review comments), 100% of the sampled
records, while the humanities cluster logged the fewest with 9% (2 of 22 records). The
natural sciences cluster documented mid-term content for 38% of the sampled records,
and the social sciences cluster had mid-term review comments or student contact
documented for nearly half of the records sampled.

Table 3 – Mid-term Content within the College Sample by Cluster
College Cluster
Total
Sample of
Student
Records
Records with Mid-term
Content
# %
General Advising 9 9 100
Humanities 22 2 9
Natural Sciences 34 13 38
Social Sciences 49 24 49
Total 114 48

The sampling technique designed to over-represent student records affiliated with
the college yielded a total of 199 student records: 114 college records and 85 professional
school records. However, taking into account the key variable of interest – documented
42

mid-term content on the advisement system – the portion of the sample eligible for
further quality analysis and benchmarking is 48 college records and 56 professional
school records. The next section describes the data analysis procedure.
Data Analysis
All data was extracted from the online, university-wide database of individual
undergraduate student records and advisement notes, where the advisors document their
student contact. Data from the college clusters and the professional schools were
subjected to the same quality analysis and were coded using the coding rubric in
Appendix B. Benchmarks for quality are based on the theoretical frameworks presented
to the advisors in training. The benchmarks for the point of contact prompted by the
advisor receiving system notification of a low mid-term grade for the student are as
follows:
Content of Contact (RQ 1)
Advisor comments on system.
1. After receipt of a low mid-term grade notification for a student from the system,
did the advisor conduct a holistic record review and log notes with regard to
trends in:
- academic performance?
- major choice and work path direction?
- enrollment in classes and at the university?
- life outside of the classroom and the university?
43

- comments from the advisor and/or other university personnel regarding
the student?
2. Do advisor notes highlight the student’s strengths or are only risk factors
mentioned?
3. Do the comments the advisor logs onto the system highlight the Rogerian
principles of:
- empathy or compassionate understanding for the student’s narrative (as
detailed in the student record)?
- trust in the student, namely to progress to graduation in a timely manner,
to follow through on any guidance, and to be self-directive?
- overall positive regard for the student’s potential?
4. Does the advisor provide a rationale for choosing to contact or not contact the
student individually regarding mid-term grade performance and the student’s
record review?
Advisor contact and follow-up with student.
1. How did the advisor contact the student (email, phone, or in-person meeting)?
2. What did the advisor state was the reason for the contact:
- low mid-term grade only? (Is the class for which the grade was received
and any faculty comments concerning the grade detailed in the contact
with the student?)
- low mid-term grade and specific concerns regarding the student’s overall
academic performance?
44

- low mid-term grade and a more general check-in regarding how the
student is doing both in and beyond the classroom?
3. Are referrals made to resources available to the student, such as:
- a follow-up appointment with the advisor?
- guidance to schedule a meeting with faculty and/or teaching assistants?
- contact information for relevant on-campus support services (e.g. another
major department, counseling services, tutoring, disability services,
residential education, financial aid, academic review)?
4. If a referral is made, does the advisor supply the contact information for a specific
person at the support service with whom the student can connect? Does the
advisor let the contact at the support service know that the student has been
referred and the reason for the referral?
5. Does all contact the advisor has with the student emphasize the Rogerian
principles of:
- empathy, care, and compassionate understanding for the student’s
narrative (as detailed in the student record)?
- trust in the student, namely to progress to graduation in a timely manner,
to follow through on any guidance, and to be self-directive?
- overall positive regard for the student’s potential?
6. In the initial contact, does the advisor ask the student to check back in? Is a time
frame and manner of contact given for the follow-up?
45

7. Are any details logged on to the system regarding if or how the advisor will
maintain contact with the student?
Timing of Contact (RQ 2)
1. How much time (in days) elapsed between system notification of a low mid-term
grade for a student and a comment being logged on the system, indicating a
review of the student record had been completed?
2. If deemed appropriate, how long (in days) before personalized student contact
from the advisor is logged onto the system, either in the form of an email copied
directly to the system or as notes regarding a phone call or in-person meeting
between the student and advisor?
Coding of Data
Coding of the sampled student records was guided by the questions above and
translated into benchmarks. A set of conditions needed to be satisfied in order to meet
each individual benchmark. In order for an advisor to meet a benchmark, at least one
condition of that benchmark must have been met. If there was no advisor content on the
system for a student receiving a low mid-term grade, none of the conditions or
benchmarks were documented as having been met. For every condition and benchmark
that was met, the advisor received a point, and point totals were tallied on the coding
rubric (see Appendix B). The five benchmarks and their corresponding conditions are as
follows:

46

Benchmark 1: Demonstrating a Holistic Review
Condition A: Notes on overall academic performance
Condition B: Notes on major choice and work path
Condition C: Notes on course or university enrollment
Condition D: Notes on life outside the classroom
Condition E: Notes on other comments already logged on the system
Benchmark 2: Utilizing Strengths-Based, Person-Centered Guidance (Comments and
Contact)
Condition A: Lists student’s strengths (in addition to or in lieu of risks) or risks
only
Condition B: Notes empathy/compassion for student’s struggles, trust in student’s
ability to be self-directive, AND/OR general positive regard for student’s
potential and abilities
Benchmark 3: The Student Point of Contact
Condition A: Rationale for or against contacting student logged (yes/no)
Condition B: Manner of contact (email, phone, in-person)
Condition C: Reason for contact logged (mid-term grade only (MG), mid-term
grade and overall academic performance (MGAP), OR mid-term grade
and general check-in (MGCI)

47

Benchmark 4: Documentation of Referrals and Follow-Up
Condition A: Number and type of referral(s): advisor (ADV); faculty/TA
(FACTA); support services (SUPP); none noted (NN)
Condition B: Referral contact information noted (yes/no)
Condition C: Number and type of follow-up: check-in, no timeframe (CINT);
check-in, with timeframe (CIWT); maintain general advising contact with
student (MC); none noted (NN)
Benchmark 5: Time
Condition A: Days between system notification and advisor comment logged on
system
Condition B: Days between system notification and advisor point of contact with
student
The number of points achieved per student record for both conditions and
benchmarks were compared to the student’s school association (college or professional
school) and the advisor’s attendance at the training. Results from the analysis are
presented in the following chapter.

48

CHAPTER 4
RESULTS
This chapter presents numerical representations of the content analysis and
qualitative excerpts that contextualize the findings for each research question.
Analysis of the Training
Researcher observation of the training was conducted in order to note how the
trainer’s delivery of the material aligned with the theoretical framework of the researcher
and matched the benchmarked standards used in evaluating student points of contact.
This section provides an overview of that observation, organized by the key topics
covered by the trainer.
Need for Contact
During the training, the trainer stressed that research has shown that mid-term is a
critical point in student progress through the semester and towards graduation. According
to the trainer, the university has found that when students can make a timely decision
regarding course enrollment, specifically whether or not to withdraw from a course based
on mid-term performance, there is a significant drop in students who end the semester on
academic probation. The trainer also stated that there is no “lock-step template” for
contacting students; rather, the purpose of the contact is to “apply principles [presented in
advisor training] to [each individual] advisor’s style and departmental needs.”
Additionally, the trainer highlighted that the reporting of mid-term grades is mandatory
for faculty but that the mid-term information is transmitted to the student via advisor
contact. Thus, mid-term contact by advisors is a university expectation. If an advisor
49

chooses not to contact a student, a rationale for the action should be documented on the
advisement database.
Holistic Review
The trainer defined the term “holistic” as seeing the student as a “whole” and
operating within many, interdependent contexts. A mid-term grade was also defined
holistically as “not an isolated bit of information…but a snap shot” of everything going
on with the student. A holistic review of a student record was defined as one that
“assimilates all of the information” the advisor has about the student and one that locates
trends in the student record as a means to guide the student through mid-term and
towards graduation. The trainer demonstrated the process of completing a holistic record
review in real-time on the advisement system (as described in Chapter 3) and dialogued
with the attendees about the process.
Strengths-Based, Person-Centered Guidance
In accordance with the training content, the trainer pointed out that strengths-
based, person-centered guidance focuses on believing that the students can achieve,
succeed, and realize their potential (positive regard), as well as the principles of
authenticity, empathy and compassion, and mutual trust between advisor and student. The
trainer also pointed out the “3 Ps” of advising at the university: being present (being real
and forthright with students), being positive (locating student strengths, not just risks and
challenges), and being open to perspective-sharing (showing students a map of their
journey, but listening to where they want to go). The trainer showed examples and
dialogued with attendees about the concepts.
50

Personalized and Individualized Student Contact, Referrals, and Follow-up
The trainer used examples to discuss the personalization and individuation of
student contact: providing information specific to the student, using specific student
details to inform referrals, establishing rapport and building relationships with students so
they know who the person is contacting them with mid-term news. An emphasis was
placed on using every point of contact to build a relationship with the student, on looking
to differentiate between academic and non-academic struggles to inform referral
decisions, and on “closing the loop” and documenting what happened, if anything, after
the initial student contact.
Overall, the delivery of the training materials reflected the theoretical framework
the researcher had proposed, the notes the researcher prepared on the material to be
covered (see Appendix A), the pre-training discussion between the researcher and the
trainer on the material, and the benchmarks that would be used in evaluating content.
Research Question 1
How does a combination of ecological systems and person-centered theories training
affect the quality of academic advisors’ contact with students, specifically their ability to
meet benchmarks demonstrating:
a. holistic reviews of student records?
b. strengths-based, person-centered guidance?
c. personalized and individualized student contact, referrals, and follow-up?
The analyses of Research Question 1 that follow focus on the student records in
the sample that indicated a mid-term intervention by the advisor by way of a comment on
51

the advisement database and/or student contact initiated by the advisor and logged on the
advisement database. Thus, Tables 4, 5 and 6 reflect 42% of the college’s student records
in the sample and 66% of the professional schools’ student records in the sample, as
described in Chapter 3 and indicated in Table 1.
Demonstrating Holistic Reviews of Student Records
Student records meeting the conditions for holistic review noted trends in
students’ academic performance, major choice and work path direction, enrollment in
classes, life outside of the classroom and the university, and other comments regarding
the student logged by the advisor and/or other university personnel. Table 4 summarizes
the data pertaining to the holistic review of student records demonstrated within the
sampled records, for both the college and the professional schools.

Table 4 – Holistic Review of Student Records with Mid-term Intervention

Records with
Mid-term Content
Holistic Review of Records
Student Record
Affiliation
Total
Advisors
who
Attended
Training
Average #
of
Conditions
Met (Max.
5 Possible)
Mid-term
Comments/
Contacts
Meeting
Benchmark
# of
Advisors
Attended
Training &
Met
Benchmark
The
College
General Adv. 9 0 (0%) 0.00 0 (0%) 0
Humanities 2 2 (100%) 1.00 2 (100%) 2
Natural Sci. 13 10 (77%) 1.00 5 (38%) 5
Social Sci. 24 21 (88%) 2.00 8 (33%) 8
Total 48 33 (69%) 1.00 15 (31%) 15

Prof.
Schools
All Total

56

28 (50%) 1.26 38 (68%) 22

52

Comparing the college overall with the professional schools, 31% of the holistic
reviews of student records met the benchmarks, while 68% of those in the professional
schools did. All of the student records in the college meeting the benchmark were logged
by an advisor who attended the training, 15 of 15 (100%), compared to only 22 of 38
records (58%) in the professional schools logged by an advisor who attended the training.
Regarding the average number of conditions met in the holistic review, the
professional schools scored higher than the college, with 1.26 compared to 1.00 out of a
maximum five possible conditions. Within the college, general advising had the lowest
score with an average of zero conditions met. Of note is the fact that no advisors in the
college’s general advising unit attended the training. The social science cluster met an
average 2.00 conditions, the highest of all units. The social sciences cluster is the largest
sample of all the college clusters, and it includes several large majors reflected in the
sample (as described in Chapter 3). For these majors, student contacts and comments
consistently exceeded the minimum conditions needed to meet a benchmark, resulting in
this cluster’s 2.00 average number of conditions met, despite the fact that only 33% of the
records with comments or contacts met the benchmark (8 out of 24). Thus, while the
student contacts that were completed excelled, the results for the cluster need to be seen
in context, representing only 33% of the cluster, with the remaining student records not
meeting the benchmark or having no intervention documented on the advisement system.
The conditions most frequently met in the college sample were the ones
pertaining to enrollment, life outside the classroom, and academic performance. In the
professional schools, the conditions met with the greatest frequency were those related to
53

enrollment, academic performance, major choice and work path, and references to other
comments logged on the system. Both the college and professional schools met the
conditions of enrollment and academic performance, but they diverged with the college’s
emphasis on life outside the classroom and the professional schools’ emphases on major
choice and work path and the review of other comments pertaining to the student on the
advisement system.
The findings on the holistic review of student records suggest a relationship
between attendance at the training and the quality of advisor contact with students for the
college, but the relationship does not appear to exist for the professional schools. In the
college, all the student records meeting the benchmark were logged by advisors who
attended the training, and the unit that had no advisors attending the training (general
advising) had zero records meeting the benchmark. For the professional schools, there
appear to be factors in play that contribute to the advisors meeting the holistic review
benchmark other than attendance at the training.
Demonstrating Strengths-Based, Person-Centered Guidance
Student records meeting the conditions for strengths-based, person-centered
guidance noted students’ strengths and the Rogerian principles of empathy and
compassion, trust and self-direction, and/or positive regard, in either comments or
contacts logged on the advisement system. Table 5 summarizes the data for both the
college and the professional schools.

54

Table 5 - Strengths-Based, Person-Centered Guidance in Student Records with Mid-term
Intervention

Records with
Mid-term Content
Strengths-Based, Person-Centered
Guidance
Student Record
Affiliation
Total
Advisors
who
Attended
Training
Average #
of
Conditions
Met (Max.
4 Possible)
Mid-term
Comments/
Contacts
Meeting
Benchmark
# of
Advisors
Attended
Training &
Met
Benchmark
The
College
General Adv. 9 0 (0%) 0.00 0 (0%) 0
Humanities 2 2 (100%) 1.00 2 (100%) 2
Natural Sci. 13 10 (77%) 1.00 5 (38%) 5
Social Sci. 24 21 (88%) 1.12 17 (71%) 17
Total 48 33 (69%) 0.78 24 (50%) 24

Prof.
Schools
All Total 56 28 (50%) 1.24 29 (52%) 14

Regarding strengths-based, person-centered guidance, both the college and the
professional schools had about half of their student records meeting this benchmark, 50%
for the college and 52% for the professional schools. Of the 24 and 29 records meeting
the benchmark, respectively, 100% in the college and 48% in the professional schools
were logged by an advisor who attended the training.
For the average number of conditions met, the social sciences again led all
clusters in performance, but the overall college total was less than 1.00 due to the general
advising cluster not meeting any conditions for the benchmark in their contacts. The
professional schools had the highest overall scores, meeting more than 1.00 condition of
the benchmark, on average. For the conditions met in the college, the emphasis primarily
was on expressing empathy and compassion (e.g. “I know you have a tough schedule,”
55

“I know there has been a lot going on”), whereas in the professional schools, the
emphasis equally was on demonstrating positive regard for student potential (e.g. “I know
you can bring your grade up in the course”) and expressing empathy and compassion.
Once again, the findings regarding strengths-based, person-centered guidance in
student records suggest a relationship between attendance at the training and the quality
of advisor contact with students for the college, but it does not appear so for the
professional schools. In the college, all the student records meeting the benchmark were
logged by advisors who attended the training, and the unit that had no advisors attending
the training had zero records meeting the benchmark. For the professional schools, nearly
half of the advisors who did not attend the training still met the benchmark and met the
most conditions of the benchmark overall. It appears that although the training mediated
college advisors’ performance on the measure, there was no relationship between
attendance at the training and the number or quality of contacts made by professional
school advisors.
Demonstrating Personalized and Individualized Student Contact, Referrals, and
Follow-up
Table 6 summarizes the data pertaining to personalized and individualized student
contact, referrals, and follow-up demonstrated within the sampled records, for both the
college and the professional schools. This table represents a compilation of the data
collected for Benchmarks 3 and 4 in the rubric (see Appendix B), as well as researcher
notes on whether contacts logged for individual student records were form or
personalized and student-specific.
56

Table 6 - Personalized and Individualized Student Contact, Referrals, and Follow-up in
Student Records with Mid-term Intervention

For the college, 18 of the 48 records sampled, or 38%, were written as
individualized, student-specific contacts, while 31 of 56, or 55%, of the professional
schools’ records were personalized contacts. Of the 18 records in the college that met the
benchmark, 100% of the advisors who completed the individualized student contact
attended the training. Among the professional schools’ records meeting the benchmark,
only 58% of the advisors who completed the contact attended the training.
Within the college, the social sciences cluster had the greatest percentage of
personalized and individualized student contact, referrals, and follow-up, with 54%. The
general advising and humanities clusters did not send any student-specific contacts. The
general advising cluster logged contact for all of their students (see Table 3), however, all
of the contacts were completed by one advisor who sent a mass-emailing on the same

Records with
Mid-term Contact
Personalized & Individualized Student Contact,
Referrals, and Follow-up
Student Record
Affiliation
Total
Advisors
who
Attended
Training
Personal-
ized
Contacts
&
Referrals
(Not
Form)
# of
Advisors
Attended
Training
&
Personal-
ized
Contact
Specific
Advisor
Follow-
up Noted
# of
Advisors
Attended
Training &
Met
Benchmark
The
College
General
Adv.
9 0 (0%) 0 (0%) 0 0 (0%) 0
Humanities 2 2 (100%) 0 (0%) 0 0 (0%) 0
Natural Sci. 13 10 (77%) 5 (38%) 5 5 (38%) 5
Social Sci. 24 21 (88%) 13 (54%) 13 15 (63%) 15
Total 48 33 (69%) 18 (38%) 18 20 (42%) 20

Prof.
Schools
All Total 56 28 (50%) 31 (55%) 18 5 (9%) 0
57

day, and employed a form email that was not personalized and did not meet any of the
conditions or benchmarks used for evaluation in this study. On the other hand, the
humanities cluster, which logged contact for only 9% of the total records eligible (see
Table 3), used a form email that was not personalized and individualized but did meet the
benchmarks for both holistic review and strengths-based, person-centered guidance (see
Tables 4 and 5).
Additionally for the college, 20 of the 48 records sampled, or 42%, included
specific directives regarding student/advisor follow-up, and 100% of these records were
completed by an advisor who attended the training. For the professional school, only 5 of
the 56 records, or 9%, included notes regarding the specific type of student/advisor
follow-up to be conducted after the initial contact, and none of these records were
completed by an advisor who attended the training. For the college records, the
percentage of advisors who attended the training and met the benchmark (100%) suggest
a relationship between the two.
Research Question 1 Results Summary
The data suggest a relationship between attendance at the training and the quality
of advisors’ mid-term intervention and contact with students for the college, but not for
the professional schools. For the college, holistic review of student records, strengths-
based, person-centered guidance, and personalized and individualized student contact
with referrals and follow-up noted were demonstrated in student records logged on the
advisement database, and all the records meeting these benchmarks were logged by
advisors who attended the training. There was no consistent pattern found between
58

attendance at the training and meeting the benchmarks within the professional schools,
suggesting other factors contributing to the professional schools’ advisors meeting the
benchmarks.
Research Question 2
How does the number of advisor contacts per student record and the time between system
notification and advisor contact compare between advisors who receive training in the
tenets of ecological systems and person-centered theories and those who do not?
Number of Advisor Contacts per Student Record
The number of advisor contacts per student record was measured by how many
times an advisor logged content on the system at mid-term for each student record and
whether or not the advisor attended the training. Table 7 summarizes these findings for
the college and the professional schools.
For the college, 77% of the student records that showed one contact from an
advising unit at mid-term were completed by an advisor who attended the training.
However, student records with one or more advisor contacts account for 46% of the
college sample, with the greater percentage being records with no advisor contact (54%).
For these college records with no advisor contact documented on the system at mid-term,
approximately half of the advisors affiliated with those records attended the training,
while the other half did not. This suggests no relationship between college advisor
attendance at the training and the number of contacts completed, and there seems to be
little difference on this measure between those college advisors who attended the training
and those who did not.
59

Table 7 - Number of Advisor Contacts per Student Record among those Flagged as
Eligible for Mid-term Intervention

Advisor Affiliated with Eligible
Student Record
School
Affiliation
Number
of Contacts
per Record
Total Eligible
Records
Attended
Training
Did Not Attend
Training
The College
0 61 (54%) 30 (49%) 31 (51%)
1 52 (46%) 40 (77%) 12 (23%)
2+ 1 (0%) 0 (0%) 1 (100%)
Total 114

Professional
Schools
0 29 (34%) 18 (62%) 11 (38%)
1 53 (62%) 29 (55%) 24 (45%)
2+ 3 (4%) 0 (0%) 3 (100%)
Total 85

For the professional schools, records with one contact made up the greater
percentage of the sample (62%), and when records with two or more contacts are added
in, the total rises to 66%. Records with no contact documented on the system account for
34% of the sample, with 62% of these records affiliated with an advisor who attended the
training, thereby suggesting no relationship between attendance at the training and the
number of contacts. Similarly, for records with one advisor contact documented, there
seems to be little difference between advisors who attended the training and those who
did not, with the proportion of these records closely split: 55% attended the training, 45%
did not.
There were 20% more student records indicating at least one advisor contact made
by the professional schools than the college (66% compared to 46%), despite the fact that
the college had 22% more of their advisors who made student contacts attend the training
60

than did the professional schools: 77% for the college, compared to 55% for the
professional schools. These findings seem to confirm the fact that, for the college
advisors, attending the training did not have an impact on the number of contacts
completed. Other factors than advisors attending the training are likely impacting the
number of student contacts made by professional school advisors.
Time Between System Notification and Advisor Contact
The time between system notification and advisor contact is a measure of when
the advisor received system notification that faculty had reported a mid-term grade for a
student, when the advisor logged student contact on the system, and whether or not the
advisor attended the training. Table 8 summarizes these findings for the college and the
professional schools.
The most consistent finding regarding the timing of student contact for advisors
who attended the training and those who did not is found within the professional schools:
89% of student contacts made by advisors who attended the training (25 of 28 records)
were done within three days of system notification that the student had been flagged with
an at-risk indicator. Within the college, student contacts made within three days of
system notification by advisors who attended the training also made up the greatest
percentage of this category, with 45% (15 of 33 records). However, the remaining 18
records of contacts made by advisors who attended the training varied in amount of time,
with 21% occurring 10-12 days after system notification and 15% occurring after 13 days
or more. This comparison of the timing of student contact by the college and the
professional schools’ advisors who attended the training suggests that something else is
61

happening within the professional schools, independent of the training, to account for the
number of days between student contacts following system notification.

Table 8 - Time Between First System Notification and Advisor Contact for Student
Records with Mid-term Intervention

Advisor Affiliated with Contact in
Student Record
School
Affiliation
Time
(in days)
Records with
Advisor
Contact
Attended
Training
Did Not Attend
Training
The College
0-3 21 (44%) 15 (45%) 6 (40%)
4-6 6 (13%) 2 (6%) 4 (27%)
7-9 6 (13%) 4 (12%) 2 (13%)
10-12 8 (17%) 7 (21%) 1 (7%)
13+ 7 (15%) 5 (15%) 2 (13%)
Total 48 33 15

Prof.
Schools
0-3 43 (77%) 25 (89%) 18 (64%)
4-6 4 (7%) 1 (4%) 3 (11%)
7-9 2 (4%) 0 (0%) 2 (7%)
10-12 2 (4%) 1 (4%) 1 (4%)
13+ 5 (9%) 1 (4%) 4 (14%)
Total 56 28 28
*Note: Some column totals sum to greater or less than 100% due to rounding

Looking at the records of student contact completed by both groups of advisors
who did not attend the training reveals the college group’s timing of contact is more
distributed among the time categories than the professional schools, and the professional
schools’ timing of contact is more distributed among the time categories than their
colleague advisors in the professional schools who attended the training. For both non-
attendee groups, however, contact within 3 days of system notification remains the
62

highest percentage of the category, with 40% in the college and 64% in the professional
schools. Overall student contact by college advisors who did not attend the training is
considerably less than the other three categories: 15 records compared to 33 (college,
attended training) and 28 (both groups of professional school advisors). However, there
were some logistical challenges to the calendaring of completing the mid-term initiative
that might have affected the timing of contacts for all advisors, which will be discussed as
a limitation in Chapter 5.

63

CHAPTER 5
DISCUSSION
Prior research has shown that systematic student contact and follow-up by
university personnel that is individualized and personalized has a positive effect on the
retention, persistence, and graduation of students (Tinto, 1998). This study examined
whether advisor training in the tenets of ecological systems and person-center theories
can prompt a shift in the process of advising from an end-product perspective, which
emphasizes the movement of students from enrollment through to graduation, to a
relational approach that engages students holistically in the process of advising and forms
connections with students through individualized and personalized contact and follow-up.
Additionally, this study sought to determine if the tenets of strengths-based, holistic, and
person-centered theories could be transformed into a training curriculum, implemented in
practice, and assessed. This chapter summarizes the findings of the study, offers analysis
and discussion of the findings, and then moves on to implications, limitations and
concluding remarks.
Study Findings
Relationship of the Training to Advising Practices
The results of the study indicate a relationship between attendance at the training
and advising practice for certain groups. The relationship was observed for the college,
and more specifically the social sciences cluster, which performed consistently well on
meeting the benchmarks in the study. Furthermore, the relationship appeared the
strongest with the quality of the advisors’ student contacts, but not with the overall
64

quantity. While there was a difference in quality between advisors who attended the
training and those who did not, there did not appear to be a quantitative difference in the
number of student contacts the advisors completed.
Quality of Academic Advisors’ Student Contact
The first research question examined how a training integrating ecological
systems and person-centered theories would affect the quality of advisor contact logged
onto an advisement database at the mid-term point in the semester. The data, student
record content, was coded relative to benchmarked standards regarding holistic reviews
of student records, strengths-based, person-centered guidance, and personalized and
individualized student contact, referrals, and follow-up. The data suggest a relationship
between attendance at the training and the quality of advisors’ student contact during the
mid-term intervention for the college, but not for the professional schools. The college
demonstrated all three quality measures documented in the student records on the
advisement database, and all the records meeting these benchmarks were logged by
advisors who attended the training. There was no consistent pattern found between
attendance at the training and meeting the benchmarks within the professional schools.
This finding suggests a difference in the advising practices in the college compared to
those in the professional schools at this university.
Holistic review and the school mission. The focus of the holistic review for both
the college and the professional schools seemed aligned with their respective missions.
Results for the college indicated holistic reviews of student records that highlight life
outside the classroom. The data points to the college’s orientation toward examining what
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is happening with students beyond academic concerns and shows the college’s
recognition of the interconnected nature of personal and academic contexts. It also
demonstrates the college’s focus on providing students with a well-rounded college
experience, employing both academic and non-academic factors in assessing the student
record. For the professional schools, holistic reviews focused on major choice and work
path, which is aligned to the schools’ mission of preparing students for specific career
objectives.
Collaboration and the school’s organizational structure. The professional
schools’ emphases on reviewing other comments on the advisement system observed in
the analysis of Research Question 1 demonstrate the collaborative nature of advising
among the professional schools and between the schools and the university at large. The
migratory enrollment nature of students within the professional schools – namely,
students being admitted to professional programs and students changing programs – may
have resulted in the frequency with which other comments on the system were referenced
in completing holistic reviews of student records.
The collaborative nature demonstrated in the professional schools’ advisement
system content is likely indicative of the organizational infrastructure of the schools, in
which advising is centralized within each school and there are clear administrative and
reporting structures, as well as widespread mandatory advising procedures. The
professional schools also are able to provide “in-house” referrals for student support
services, which might contribute to the greater observed collaboration in the student
records. Unlike the professional schools, the college has a decentralized structure with
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separate major departments and few advisors working together as a cluster in the same
physical space, with the exception of the humanities. College advisors also refer students
to support services housed outside of the college, which appears to contribute to less-
shared advising content on the system.
The professional schools’ organizational framework may have mediated their
performance on the benchmarks, providing administrative support and a natural
alignment (given their mandatory advising practices) with the expectations of the mid-
term student contact initiative. On the other hand, the college’s decentralized
organizational framework – where some advisors work directly for department chairs and
others report to a director of advising – has a less consistent reporting structure,
potentially leading to less oversight for initiative implementation and a greater need for
process guidelines, which the advisors might seek through the use of templates in their
advising practices. The question that remains is whether or not the observed results of
this study were mediated by the organizational framework or system within which each
group must operate.
If this is the case, there might be lessons to be gleaned from the professional
schools that can be implemented into the college that would further strengthen the
advisor contact with students beyond the observed outcomes on the college’s
performance in this study. Since the study findings suggest a relationship between the
training and the quality of student contact for the college but not the professional schools,
it might be that the training provided a clearer framework than currently exists for the
college advisors that they could benefit from and use to improve their advising practice.
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On the other hand, the professional school advisors might already have such a structure in
place, making the training less meaningful for them in relation to their advising practices,
as witnessed by the study findings that there seemed to be no relationship between
whether a professional school advisor attended the training and the quality or quantity of
her or his student contacts.
Summary Discussion
The design of this study sought to explore and fill what appeared to be a gap in
some academic advisors’ performance on student contact initiatives that had been
implemented at this university over the two years prior to the study. The assumption was
that the most likely cause of the performance gap was knowledge and skills, rather than
motivation. The current study focused on a new initiative being implemented – the mid-
term intervention initiative – and attempted to transform the tenets of strengths-based,
holistic, and person-centered theories into a training curriculum that could be
implemented into practice, applied directly to the new initiative, and assessed. The
findings of the study point to organizational factors, as well as the possibility of
motivational factors, as impacting advisors’ performance on the student contact
initiatives overall, and specifically on the mid-term intervention initiative.
The observed relationship of the training with the quality of advisors’ student
contact for the college did not hold up for the number of student contacts logged on the
advisement database. This might be a function of the way the initiative was organized
and implemented. The initiative was set-up with mandatory reporting for faculty so that,
in theory, every student would receive a report on their mid-term progress for all classes.
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The information, however, was not transmitted directly from faculty to student, but was
sent from the faculty to the advisor via the advisement database system. The advisor was
then to relay the information to the student, with pertinent guidance, referrals, and follow-
up. With this plan, if the quantity of contacts logged in the advisement database is not
100%, then there will be students who are never notified of the grades and comments the
faculty submitted for them at mid-term, thereby impacting the success of the mid-term
intervention initiative.
The calendaring of the mid-term grade intervention may have affected both the
faculty and the advisors. The timeframe for faculty to report grades was shortened from
the original initiative design to only three weeks, shifting the calendaring of the initiative
to earlier in the semester than was originally intended and leaving open the possibility
that faculty were hesitant to flag students as at-risk so early in the semester. Also, faculty
may have been unsure if the information they could provide on student progress and
performance at this time in the semester was truly helpful for advisors when contacting
and guiding students.
Advisors were likely affected by the change in the calendaring of the initiative in
that it then overlapped with other initiatives that were mandatory for them to complete.
The mid-term initiative, although mandatory for faculty, was not so for advisors, and may
not have taken precedence among advising duties. In the end, student contact seemed to
be relegated either to later in the semester, or it did not occur at all. Similar to the faculty,
advisors might also have been hesitant to contact students with mid-term grades so early
in the semester, especially if a low percentage of coursework was covered by the reported
69

at-risk grades, the grades were not updated by faculty later in the semester to reflect a
greater percentage of the coursework, and the grades were reported during the open
add/drop period, when students are finalizing their course schedule and migrating
between courses. Additionally, the change in the calendaring for the initiative no longer
aligned it with pre-registration meetings for next semester, where advisors have the
opportunity to meet with students to review their academic record up to that point,
including discussions of mid-term grades, as well as to plan for next semester.
The many factors involved in the implementation and execution of the mid-term
intervention initiative and the collaboration it required across the university make it
difficult to determine if the lack of student contact demonstrated by advisors was
impacted by the structure of the initiative itself or by a lack of advisor motivation to
participate in an initiative that is not mandated, or perhaps a combination of the two.
For those advising units that demonstrated an acceptable quantity of student
contact, the quality of the contact in terms of demonstrating strengths-based, person-
centered holistic advising was not always present. For example, there is the matter of
contacting a student with a form email versus writing an individualized note to the
student. Personalized and individualized student contact was a key element of the mid-
term intervention initiative and the aligned training module, yet some advisors’ contact
with students used non-personalized, form email messages. It is unclear whether this may
be an issue of organizational constraints (e.g. advisors not given enough time to complete
individual student contacts along with other departmental assignments), or a question of
motivation to move beyond the systems approach to advising (focused on moving
70

students from matriculation to graduation) to the holistic approach that requires advisors
to delve more deeply into the individual narratives of their students.
One example is the form email that was sent by the college’s general advising
cluster to all students receiving at least one mid-term grade of at-risk. The form email
was a vague template that was not specifically addressed to the student, did not list the
course(s) for which a mid-term grade of at-risk had been submitted, and stated a blanket
referral to talk with professors (however, without listing the course(s) for which a mid-
term grade had been submitted, it is impossible for a student to know with which
professors to speak). Advisor comments made during the training session and observed
by the researcher suggest that the advisor might have aimed to peak the curiosity of the
student by sending a “mystery” email in the hopes it would prompt a reply, and thereby
increase the possibly of engaging the student in a dialogue. While this strategy might be
well-intentioned, it does not demonstrate the Rogerian principles of trust in the student
and overall positive regard toward the student, which were key elements in the training
module. Furthermore, the template might not be the best match for the student population
the general advising cluster serves – undecided and undeclared students who do not yet
have a permanent home in a major department or school – or for the focus of the
initiative. This study did not investigate whether this advising strategy had systemic
and/or motivational roots, as it was beyond the scope of the study design.
In addition to the potential explanation about the form email strategy described
above and gleaned from the researcher’s observation of the training, most of the advisor
questions and comments during the training focused on the logistics of mid-term advising
71

(such as the timeline for the mid-term initiative). During the discussion, the advisors did
not engage as much on the topic of the advising process or strategies for working with
students, despite the training’s focus on a strengths-based, person-centered holistic
approach to advising. This observation, combined with the findings described above,
highlights the difficulty in prompting a change in educational practice through knowledge
and skills training without addressing the organizational, or systems, framework and
underlying motivational elements.
Implications
The overall purpose of this study was to determine if training in ecological
systems and person-centered theories could and would affect advising outcomes at a
specific time in the semester for a particular initiative, when built upon and aligned with
prior initiatives and advisor training. Results indicate that a training of this type, when
paired with a complementary pre-existing advisor curriculum, can have an impact on
advising outcomes on a specific benchmarked assessment. More specifically, the findings
presented in this study further the research in strengths-based, person-centered training
and its effect on the advising process for all students—whether they arrive at the
university well-prepared or under-served, as traditional college students or returning adult
learners, first-generation or legacy students. Regardless of the individual and contextual
factors students carry with them into the academy, their subjective experience as students
within the educational institution will be enhanced by the connection and relationships
they build with others, including academic advisors as agents of the university system.
This enhanced student experience and deeper connection with individuals at the
72

institution, forged through personalized and systematic contact and follow-up, will affect
the desired end-product outcomes of retention, persistence, and graduation (Kuh, 1996;
Tinto, 1998). This is true particularly for the current generation of students who are
seeking community, personal growth and relationships through their higher education
experience (Howe & Strauss, 2000, 2003). Students who feel they belong to the
university community, who feel the university cares about their success, and who have
connections with individuals who can support their academic and social progress at the
institution, are more likely to persist and graduate. Without such relational connections to
agents of the system, students are more likely to feel disconnected and disinterested in
relating to that system (Bronfenbrenner, 1975, 1979), which can affect their retention,
persistence, and graduation.
Furthermore, the benefit of relationship-building is mutual: university advisors’
professional experiences also will be enhanced and enriched through the deeper
connections they create with their advisees. However, despite the opportunity to create
mutually beneficial and supportive relationships between students and advisors, there
remains the potential for resistance to change within a well-established institutional
culture not accustomed to them. The larger questions that remain, therefore, are can
trainings in ecological systems and person-centered theories prompt and/or foster a
culture change towards a more individualized and personalized dynamic system-wide,
and will the organizational and structural makeup of the system accept and support such
change? And, if so, what types of long-term effects will the implementation of strengths-
73

based practices have on student learning, retention, persistence, and graduation
outcomes?
This study has implications for the practice of aligning enrollment initiatives with
theory and research, training curriculum, benchmarked standards, and evaluation
expectations. The direct research-trainer collaboration on the training materials was a
unique twist on the train-the-trainer model. The curriculum built upon researcher
knowledge and trainer experience in a collaborative way that is often missing in
educational research and practice. After the training was over, the trainer remarked to the
researcher that it was “tough not knowing the initial reaction of the audience” to the
content and delivery of the training materials developed. On the other hand, the trainer
stated that the best part of doing the training was “not just giving [the advisors] a
template to follow,” but having an “interactive discussion” that was “self-directive” with
advisors “asking questions and eliciting responses,” not only from the trainer, but from
their colleagues as well. In a sense, the rapport between researcher and trainer manifested
itself in the delivery of the training and, in turn, modeled aspects of the desired outcomes
for advisors in their post-training contact with students.
The research design and methods used in this study demonstrate a model for using
integrative theory to inform practice and assessment. The study highlights the use of data
to show the progression from a theoretical framework, to a training curriculum, to
practice, and finally, to assessment and evaluation. The methodology employed in the
study is a unique way to approach the content analysis of educational data through
benchmarking – with the intent of staying true to the qualitative details, but with the
74

ability to present and discuss numeric results. Furthermore, the findings of this study are
applicable to educational practitioners outside of the university setting, including K-12
schools, non-profit organizations, and other arenas in which personnel are involved in
developing, implementing, and assessing educational programs. The movement towards
holistic, person-centered practices and the resulting relationships that are formed affect
all members of educational systems, and the widespread benefits – to practitioners and
learners, alike – will become more apparent as further research is conducted.
Limitations
The limitations of the study included logistical complications with the
implementation of the initiative and limitations inherent to the design of the study.
Logistical limitations that were beyond the control of the researcher and the research
design were the changes to the calendaring of the mid-term grade initiative, as described
above, and a change to the data that occurred during the study without the researcher’s
knowledge.
Regarding the change to the data, mid-term grades, and the corresponding at-risk
system flags, were removed from some of the student records originally flagged as
having at least one mid-term grade of at-risk. The researcher was monitoring the number
of student records eligible for analysis and began to notice a decline in the number totals
midway through the study. The advisement system programmer informed the researcher
that some faculty had requested that, when a student withdrew from their class, a grade of
‘W’ be assigned as both the mid-term and final grades on record. The ‘W’ grade, in
effect, acted as an override for the mid-term grades that had been posted originally,
75

thereby removing the system flags for those records and rendering them unsearchable on
the system.
The first limitation specific to the study design stems from the assumptions that
academic advisors are motivated to develop a personal rapport and relationship with their
students and that the institutional system supports them in doing so. If these assumptions
hold true, then a training that focuses on skills and knowledge development will affect
advisor performance on benchmarked measures. However, assumptions regarding advisor
motivation and organizational structures/supports may be incorrect, may moderate, and,
in some cases, possibly nullify any effect of knowledge and skills training on
performance. For example, in the professional schools, there appeared to be factors that
impacted performance seemingly unrelated to the training, but perhaps related to the
organizational structure of advising at the schools (i.e. mandatory advising). Thus, the
limitation of the study is that it is difficult to examine learning outcomes focused on
knowledge and skills, independent of measures of motivation and organizational or
structural effectiveness.
Secondly, even with all of the measures of performance included in the study, it is
not possible to make causal ties between the results and attendance at the training; there
is no way to state that exposure to the theoretical tenets in the training caused any of the
performance results. The most that can be stated, given this study’s design and the nature
of the topic, is that there are relationships evident in the data between the training and the
work of the advisors.
76

The third limitation is that the data to which the researcher had access was limited
to content the advisors chose to document on the advisement system. The researcher
assumes that advisors were forthright and honest in documenting their comments and
student contacts, and the issue of thorough documentation on the advisement system was
reviewed in the training. However, the content advisors choose to log, and how they
choose to log it, is, ultimately, at the discretion of the advisor. Therefore, the content may
or may not accurately reflect the full picture of the quality of the student contact or the
advisor’s relationship with the student. For example, it may be that the relationship found
between the training and the outcomes for the college was a result of thorough system
documentation by individual advisors. Additionally, the relationship for the college may
have been more pronounced because the results were skewed by outliers – individual
advisors who did very well in meeting and/or documenting the benchmarked standards,
either due to their exposure to the training or because they had already implemented the
practices prior to the training. For those advisors who did poorly in meeting the
benchmarks, it is possible that some of them experience the university’s request for
documentation on the system as a hindrance to having the time to develop better rapport
with their students and deepen the connection. If this holds true, the administrative need
for oversight and outcomes assessment might, in some ways, work against the very
outcomes it hopes to foster through the training and various enrollment initiatives.
Finally, there was a limit to the researcher’s control over how the training was
presented to the advisors and which advisors attended the training. The training was
conducted by the university’s advisor training coordinator, under the guidance of the
77

researcher. It appeared aligned to study objectives, but nonetheless, was delivered by a
party other than the researcher. Additionally, advisors self-selected whether or not to
attend the meeting at which the training was held; the researcher had no control over who
was present. In the future, similar efforts to provide advisors training might seek to
involve, to a greater extent than was done for this initiative, the supervisory level of the
advising unit’s administration in fostering staff attendance and/or linking the outcomes to
staff performance evaluations.
Conclusion
In summary, this study examined if and how holistic, person-centered student
advising – based on an integrative framework of the theories of Urie Bronfenbrenner,
Carl Rogers, and Max Weber, and enrollment and retention research – can be fostered,
implemented, and assessed at a research university. The overall focus of the work is on
applied research – on turning current trends in research and literature into educational
initiatives that are not only rooted in theory and driven by data, but are also holistic,
strengths-based, and aligned to training curriculum, benchmarks, and assessments. This
study shows that while addressing skills and knowledge by developing and implementing
training curriculum is often the most accessible to practitioners, other factors such as
organizational systems and individual motivation may be equally important to investigate
when seeking to implement a cultural shift in practice. Additional research is needed on
the methodology employed in this study and the ability of skills and knowledge training
modules to instigate and sustain positive culture change within a system. In the end, this
study is a guide for educational researchers interested in the process of transforming
78

research and theories into an implementable training curriculum and assessing outcomes
that can be disseminated easily to stakeholders, practitioners, and other researchers. This
study also furthers the practical applications of positive psychology and strengths-based
perspectives within the realm of education and underscores the intersection of
sociological and psychological theories, and their connection to the future of educational
research.

79

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Winston, R., Miller, T., Ender, S., & Grites, T. (1984). Developmental academic
advising. San Francisco: Jossey Bass.

Wyckoff, S. C. (1999). The academic advising process in higher education: History,
research, and improvement. Recruitment & Retention in Higher Education, 13(1),
1-3.

Zis, S. L. (2002). Changing student characteristics: Implications for new student
orientation. Journal of College Orientation and Transition, 10(1), 64-68.

85

APPENDIX A
RESEARCHER-PROVIDED NOTES
FOR ACADEMIC ADVISOR TRAINING MODULE DEVELOPMENT

SLIDE 1: Low Mid-term Grade Training
Academic Advisor General Meeting
[Date]

SLIDE 2: Why have a low mid-term grade intervention?

NOTES

- Early intervention with students believed by faculty to be at-risk of failing a
course can impact and direct student progress in the course, and, ultimately,
towards graduation (Beck & Davidson, 2001).
- The theory is that when students are notified of course standing and offered
corrective action early in the semester, the number of students successfully
passing the course or withdrawing from the course in a timely fashion is
projected to increase, while the number of students failing the course, either due
to course grade or unofficial withdrawal, is projected to decrease. The low mid-
term grade notification spotlights an advising benchmark at a critical point of
contact with students.
- The mid-term grade intervention is, by design, an opportunity for advisors to
initiate contact with students who, in their estimation and that of the faculty,
would benefit from additional attention and support.
- A low mid-term grade notification does not indicate that the student will fail the
course, but that the faculty believe that the student is at-risk of failing if certain
conditions are not met before the end of the semester (e.g. if attendance does not
increase, if performance on graded work does not improve).
- The advisor’s role at this juncture is to recognize trends in student performance
and how best to guide the student.

SLIDE 3: Why have a low mid-term grade training?

NOTES

- The purpose of this training is to provide advisors with a way of thinking about
advising that can be molded/shaped (decontextualized) to fit their specific
advising style and departmental needs.
- It is not a template for practice, but a way of thinking about practice.

86

APPENDIX A CONTINUED
SLIDE 4: What are the main points of the training?

NOTES

- Students are holistic – they exist within numerous contexts – there is a lot going
on with any individual student and advisors are charged with seeing the “big
picture.”
- The rapport and relationships that develop between advisors and students
personalizes the system of advising and the broader institution of higher ed.
Personalization is important when talking about any kind of system – people and
relationships are at the heart of all systems and individuals, such as students,
relate to the people within any given system, not the systems themselves.
- There are certain ingredients that aid in the formation of the relationship between
advisor and student: empathy, compassion, trust, and positive regard – both in
contact between advisor and student, as well as in comments by the advisor
logged on to the advisement database system.

SLIDE 5: Here are some examples of low mid-term grade notifications and the resulting
action documented on the advisement database system:

NOTES

SHOW FIRST ROUND OF EXAMPLES:
EXAMPLE 1: Individualized student contact that addresses the personalized needs of
the student and contains specific student directives – where to go, with whom to
speak, what to do – regarding student academic performance and plans
EXAMPLE 2: Student contact that is depersonalized (e.g. a forward of a system
notification, a mass-mailing template)
EXAMPLE 3: No action documented on the system after the low mid-term grade
system notification.

SLIDE 6: What do you see in these examples?

NOTES

- Are the notes and contacts timely and informative?

- Do they highlight student strengths, risks, both, none?

87

APPENDIX A CONTINUED
- Do they focus on the whole student – such as academic performance - major
choice and work path direction - enrollment in classes and at the university - life
outside of the classroom and the university - comments from the advisor and/or
other university personnel regarding the student?

- Do they demonstrate empathy or compassionate understanding for the student’s
narrative - trust in the student to progress to graduation in a timely manner, to
follow through on any guidance, and to be self-directive - overall positive regard
for the student’s potential?

- Are referrals made? If they are, are they specific to individuals or just general? Is
there mention of follow-up, checking back in with the student?

- If there is no contact between advisor and student, did the advisor log a comment
on the system explaining why - not every student who receives low mid-term
grade notification will need to be contacted – check the whole notification (e.g.
only 10% of grade?) and whole student record (e.g. just a slip up from an high
GPA student early in a semester?). You – the advisors – know your students –
some you just need to keep an eye on, some you should bring in to the office, some
you don’t have to worry about – but you should document(?) your process of
advising on the system for others who share advisement of the student to see and
for good record-keeping on how you have advised the student towards
graduation.

SLIDE 7: After seeing the examples and thinking about questions related to the process
of advising, what do you think would make a “good” low mid-term grade intervention?

- When should the low-grade mid-term system notification prompt the advisor to
contact the student? When should the advisor just leave a comment on the system
and what should the comment say?
- What would the content of an initial low mid-term grade contact – for example,
the email telling the student about the advisor’s receipt of the grade – look like?
- How would you make referrals based on the low mid-term grade that are
beneficial to the student - particularly if they have no connection to the system to
which they are being referred?

SLIDE 8: This looks like a lot of work for a mid-term grade intervention!
- The main point is it is all about BUILDING RELATIONSHIPS WITH STUDENTS
– even within a system where there might be bureaucratic and organizational
constraints – RELATIONSHIPS are key.
88

APPENDIX A CONTINUED
SLIDE 9: How can advisors form and build relationships with students amidst resource
and time constraints? [IN GROUPS, COME UP WITH EXAMPLES.]

NOTES
Three ways to think about the building relationships with students are the three Ps –
PRESENT, POSITIVE, and PERSPECTIVE-SHARING:

- Strive for authenticity and genuineness in being present with the student – be real
and forthright.
- Demonstrate positive regard and care for the student, locating strengths, as much
as struggles, and strive to build on the positive.
- Show empathy for the student’s narrative and perspective, allowing the student to
be self-directive while still being present and offering guidance. Students can get
stuck – not know what to do – meet them in the moment and offer them a more
general map or more specific how-to’s depending on the situation.

SLIDE 10: What can I really take away from all of this?

NOTES

- When we take time to remember that students are holistic – they play many roles
and exist within numerous contexts – ones within and beyond school we can
provide better guidance because we making decisions based on the bigger
picture. When a student record gets flagged with a mid-term grade, it means the
faculty has some concerns and wants you to check-out what is going on with the
student. Check out the record, check-in with the student – the importance is the
“big picture.”
- When we help connect students to people rather than referring them to services or
other departments, we can help them demystify the institution and continue to
build relationships that will help them achieve success within the institution. And
referring students to see people is KEY. It’s all about BUILDING
RELATIONSHIPS!
- Relationships – those that are therapeutic –empathic and compassionate and
positive. It’s not about hand-holding but empowering the students to be self-
directive -to make choices, have success experiences, and make some mistakes
along the way. It’s about stressing the positive as a foundation students can build
on. And it’s about being present with students – trusting them to get the job done
and when needed offer guidance. It’s about believing in student potential and
fostering it!

89

APPENDIX B
CODING RUBRIC
Table B1: Benchmark 1 - Demonstrating a Holistic Review
BENCHMARK 1 POINTS ADVISOR DATA
Conditions A – E

Student
Record #
Holistic
Review

#
Conditions
Met
Benchmark
Met?
School
Attended
Training
1,2,3...
A. ACADEMIC PERF
B. MAJOR CHOICE &
WORK PATH
C. ENROLLMENT
D. LIFE OUTSIDE
E. OTHER
COMMENTS

Y/N C/P Y/N
1

2

3

4

5

90

APPENDIX B CONTINUED
Table B2: Benchmark 2 - Utilizing Strengths-Based, Person-Centered Guidance
BENCHMARK 2 POINTS ADVISOR DATA
Condition

A B

Student
Record #
Strengths /
Risks / Both
Rogers Total
(Comment &
Contact)
#
Conditions
Met
Benchmark
Met?
School
Attended
Training
1,2,3… S/R/B
1. EMPATHY &
COMP. / 2.
TRUST &
SELF-DIRECT
/ 3. POS.
REGARD

Y/N C/P Y/N
1

2

3

4

5

91

APPENDIX B CONTINUED
Table B3: Benchmark 3 - The Student Point of Contact
BENCHMARK 3 POINTS ADVISOR DATA
Condition

A B C

Student
Record #
Rationale?
P.O.C
Reason for
Contact
#
Conditions
Met
Benchmark
Met?
School
Attended
Training
1,2,3… Y/N E/P/I
MG /
MGAP /
MGCI

Y/N C/P Y/N
1

2

3

4

5

92

APPENDIX B CONTINUED
Table B4: Benchmark 4 - Documentation of Referrals and Follow-Up
BENCHMARK 4 POINTS ADVISOR DATA
Condition

A B C

Student
Record #
No. & Type
Referrals
Referral
Contact
Info.?
No. & Type
Follow-Up
#
Conditions
Met
Benchmark
Met?
School
Attended
Training
1,2,3…
ADV/FACTA/
SUPP/NN Y/N
CINT /
CIWT /
MC/NN

Y/N C/P Y/N
1

2

3

4

5

93

APPENDIX B CONTINUED
Table B5: Benchmark 5 - Time
BENCHMARK 5 POINTS ADVISOR DATA
Condition

A B

Student
Record #
Time
(Comment)
Time
(Contact)
#
Conditions
Met
Benchmark
Met?
School
Attended
Training
1,2,3… IN DAYS IN DAYS Y/N C/P Y/N
1

2

3

4

5

94

APPENDIX B CONTINUED
Table B6: Summary Data and Point Totals for Benchmarks 1-5

SUMMARY
DATA
POINT TOTALS FOR
BENCHMARKS 1 - 5 ADVISOR DATA

Student
Record #
# At-Risk
Grade System
Notifications
Form or
Individual
Contact
#
Conditions
Met
#
Benchmarks
Met
School
Attended
Training
1,2,3…

F/I

C/P Y/N
1

2

3

4

5

Abstract (if available)

Abstract This study examines if and how holistic, person-centered academic advising, based on an integrative framework of educational psychology (Bronfenbrenner), sociology (Weber), and counseling (Rogers) theories, can be fostered, implemented, and assessed at a research university. The study design uses the coding of qualitative data and its translation into numeric results to understand how training in the tenets of integrative theory would affect the quality and quantity of advising content at a key juncture for student retention, persistence, and graduation. The analysis of the data is based on benchmarks culled from the theoretical framework, incorporated into the training, and defined by criteria regarding holistic reviews of student records, evidence of strengths-based, person-centered guidance, personalized and individualized student contact, referrals, and follow-up, and the quantity and timing of advisor contacts. Results indicate that there is a relationship between training in ecological systems and person-centered theories and performance on a benchmarked assessment, particularly when assessing for the quality of advising content. The relationship was more pronounced within the sample of college student records than for those in the professional schools, leading to further research questions regarding the specific implications of organizational infrastructure and systems on performance outcomes. Additional questions regarding the link between advisor motivation, training, and performance also surfaced. Overall, the study provides a model for developing enrollment initiatives and educational programs that are not only rooted in theory and driven by data, but are also holistic, strengths-based, and aligned to training curriculum, benchmarked standards, and outcome-based assessments.

Linked assets

University of Southern California Dissertations and Theses

Asset Metadata

Creator Ferguson, Holly Brooke (author)

Core Title Injecting warm fuzzies into cold systems: defining, benchmarking, and assessing holistic, person-centered academic advising

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 09/13/2010

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

Tag advising,benchmarked assessment,Bronfenbrenner,counseling theory,educational programming,enrollment initiatives,holistic,OAI-PMH Harvest,person-centered,Rogers,strengths-based,student retention, persistence, graduation,systems,theory into practice,training curriculum,Weber

Place Name USA (countries)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hirabayashi, Kimberly (committee chair), Lucido, Jerry (committee member), Venegas, Kristan M. (committee member)

Creator Email hferguso@usc.edu,hferguson80@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3435

Unique identifier UC1279280

Identifier etd-Ferguson-4070 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-383151 (legacy record id),usctheses-m3435 (legacy record id)

Legacy Identifier etd-Ferguson-4070.pdf

Dmrecord 383151

Document Type Dissertation

Rights Ferguson, Holly Brooke

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