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THE EVOLUTION OF STUDENT RELATIONSHIPS OVER TIME IN A COHORT-BASED MSW PROGRAM
NOVEMBER 5, 2016
REBECCA L. MAULDIN, LMSW
LIZA BARROS-LANE, LMSW
SARAH C. NARENDORF, PHD
PEER RELATIONSHIPS IN GRADUATE SCHOOL
• Collaborative learning
• Academic success & persistence
• Professional socialization
• Cultural competency
• Well-being, coping with stress
(Casstevens et al. 2012; Collins et al., 2010*; Grady et al, 2014; Hunt et
al., 2012; Miller, 2010; Moore, 2011; Oliver 2013; Petrovich & Lowe,
2005; Rau & Heyl, 1990; Rizzuo et al., 2009; Thomas 2000)
COHORT-BASED EDUCATION
• Designed to promote student relationships
• Students placed into groups and take classes together as a group
• 10-26 students per cohort
Benefits
Strong social & academic support
High levels of academic collaboration
Sense of belonging
Better academic success and persistence
Development of empathy for classmates
Potential problems
Cliques
Personality conflicts
Insular learning environment
“Merging” with other cohorts (Lei et al., 2011; Maher, 2005,
Swayze & Jakeman, 2014)
COHORT-BASED EDUCATION
COHORTS AND RELATIONSHIP CHARACTERISTICS
Homophily
Tendency for people to form relationships with others who are similar
Most common types of homophily are racial/ethnic and age
Multiplexity
More than one type of interaction or role within relationship
Associated with ↑ trust and intimacy
Cohorts provide environment for:
Less homophily
(Leszczensky & Pink, 2015; Morimoto & Yang, 2013;
Windzio & Bicer, 2013)
More multiplexity (Kadushin, 2012)
RESEARCH AIMS
•Identify factors that influence the development of
peer relationships in an MSW program that uses
cohort-based learning
•Understand student perspectives of their
experiences with the cohort system and peer
relationships.
RESEARCH SETTING
2014 – 2016
MSW program in large public university in large
metropolitan area
Regular standing MSW students (n = 97 in 2014) placed in
cohorts for foundation semester
•After 1st semester, students are integrated into
traditionally-scheduled courses with rest of student
body
METHODS: SEQUENTIAL EXPLANATORY MIXED METHOD
4 waves of quantitative data collection
•Summer orientation (July/August 2014)•Middle of 1st semester (Fall 2014)•End of 1st semester (Fall 2014)
•End of 3rd semester (Fall 2015)
Multi-method qualitative data
Open-ended question on 4th surveyThree focus groups in September 2016
METHODS: SOCIAL NETWORK DATA
Time 1: “List the names of anyone you know who is
an incoming student”
Times 2-4: Roster with classmates’ names & check
boxes to indicate:
1. Academic (I have academic discussions with this person)
2. Friendship (I consider this person a personal friend)
3. Professional (This person has influenced my professional
development)
METHODS: SOCIAL NETWORK MEASURES
Observed networks: Academic, Friendship, Professional
Additional network variables:
a. General social ties – the existence of any of the three
types of observed ties, values = 0/1
b. Shared affiliation in student organizations
c. Same race/ethnicity
d. Age difference (absolute value)
METHODS: QUALITATIVE DATA
-All cohorts represented
-Data Collection
-Open ended question on survey
- Focus groups
-Analysis
-Semantic thematic analysis (Braun & Clark, 2008)
ENROLLMENT
ENROLLMENT
Total Eligible: 97
Enrolled: n = 95 (97.9%)
FOCUS GROUP PARTICIPATION
14 students/graduates in 3 focus groups
SAMPLE CHARACTERISTICS: FALL 2014
% (n)
Sex
Female 89.5 (85)
Male 10.5 (10)
Race/Ethnicity*
Black 30.5 (29)
Hispanic 18.9 (18)
White 43.2 (41)
Other 7.4 (7)
Cohort
FT, A 27.4 (26)
FT, B 25.3 (24)
FT, C 25.3 (24)
PT, D 22.1 (21)
Age, M (SD) 29.5 (9.0)
t1 peers “known”, M (SD) .22 (.51)
Note. *Race/Ethnicity
categories based on those
used in academic records
METHODS: SOCIAL NETWORK ANALYSIS
Analysis in UCINET (Borgatti et al., 2002)
Visualization using NetDraw (Borgatti et al., 2002)
Quadratic Assignment Procedures (QAP):
Multiple Regression
Logistic Regression
RANOVAs – Significant increases for all types
Academic: F(1.411, 135.434) = 28.507, p < .001; post hoc Bonferroni comparisons t3 sig. ↑ than t2 & t1
Friendship: F(1.018, 97.689) = 5.986, p = .016; post hoc Bonferroni comparisons t3 sig. ↑ than t2
Professional: F(2, 192) = 6.770, p = .001; post hoc Bonferroni comparisons t2 and t3 sig. ↑ than t1
AVERAGE NUMBER OF TIES PER STUDENT
GENERAL SOCIAL TIES: 1ST SEMSTER, MID-SEMESTER
GENERAL SOCIAL TIES: END OF 1ST SEMESTER
GENERAL SOCIAL TIES: END OF 3RD SEMESTER
Odds Ratios from QAP Logistic Regression Analyses Predicting Friendship Ties at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age 1.00 .98 .98
Same race/ethnicity 1.40** 2.03*** 1.62*
Same cohort 11.99*** 2.85***
Joint Affiliation in Student Orgs 1.95** 1.71*
1st semester Academic 2.36***
1st semester Friendship 9.36***
1st semester Professional 1.76***
Intercept -1.90 -3.41 -3.33
LL -3565.14 -1585.98 -1297.03
R2 .003** .18*** .36***
Odds Ratios from QAP Logistic Regression Analyses Predicting Friendship Ties at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age 1.00 .98 .98
Same race/ethnicity 1.40** 2.03*** 1.62*
Same cohort 11.99*** 2.85***
Joint Affiliation in Student Orgs 1.95** 1.71*
1st semester Academic 2.36***
1st semester Friendship 9.36***
1st semester Professional 1.76***
Intercept -1.90 -3.41 -3.33
LL -3565.14 -1585.98 -1297.03
R2 .003** .18*** .36***
Odds Ratios from QAP Logistic Regression Analyses Predicting Academic Ties at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age .99 .99 .99
Same race/ethnicity 1.17* 1.23* 1.07
Same cohort 8.71*** 4.85***
Joint Affiliation in Student Orgs 1.97*** 1.86***
1st semester Academic 1.78***
1st semester Friendship 2.20***
1st semester Professional 1.67**
Intercept -1.22 -2.08 -2.02
LL -4789.02 -2612.55 -2424.09
R2 .001* .20*** .25***
Odds Ratios from QAP Logistic Regression Analyses Predicting Academic Ties at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age .99 .99 .99
Same race/ethnicity 1.17* 1.23* 1.07
Same cohort 8.71*** 4.85***
Joint Affiliation in Student Orgs 1.97*** 1.86***
1st semester Academic 1.78***
1st semester Friendship 2.20***
1st semester Professional 1.67**
Intercept -1.22 -2.08 -2.02
LL -4789.02 -2612.55 -2424.09
R2 .001* .20*** .25***
Odds Ratios from QAP Logistic Regression Analyses Predicting Professional Ties at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age 1.02 1.02 1.02
Same race/ethnicity .98 1.02 .97
Same cohort 3.38*** 2.39***
Joint Affiliation in Student Orgs 1.16*** 1.11
1st semester Academic 1.04
1st semester Friendship 3.59***
1st semester Professional 1.27
Intercept -.72 -1.77 -1.91
LL -5840.52 -2968.85 -2613.95
R2 .006** .06*** .11***
Odds Ratios from QAP Logistic Regression Analyses Predicting Professional Ties at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age 1.02 1.02 1.02
Same race/ethnicity .98 1.02 .97
Same cohort 3.38*** 2.39***
Joint Affiliation in Student Orgs 1.16*** 1.11
1st semester Academic 1.04
1st semester Friendship 3.59***
1st semester Professional 1.27
Intercept -.72 -1.77 -1.91
LL -5840.52 -2968.85 -2613.95
R2 .006** .06*** .11***
Regression coefficients from Double Dekker Semi-Partialling QAP Multiple Regression Analyses Predicting Multiplex Relationships at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age -.005* -.005 -.003
Same race/ethnicity .11*** .13*** .06*
Same cohort .93*** .42***
Joint Affiliation -Student Organization .25*** .19***
1st semester Academic .34***
1st semester Friendship .99***
1st semester Professional .32***
Intercept .36*** .16*** .18***
R2 .007*** .25*** .39***
Regression coefficients from Double Dekker Semi-Partialling QAP Multiple Regression Analyses Predicting Multiplex Relationships at the end of the 3rd semester
(n = 97)
Note. *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Model 1 Model 2 Model 3
Difference in age -.005* -.005 -.003
Same race/ethnicity .11*** .13*** .06*
Same cohort .93*** .42***
Joint Affiliation -Student Organization .25*** .19***
1st semester Academic .34***
1st semester Friendship .99***
1st semester Professional .32***
Intercept .36*** .16*** .18***
R2 .007*** .25*** .39***
QUALITATIVE RESULTS
The cohort effect held because of friendships developed during
their time together.
“…My cohort created strong bonds, relationships. We all tend
to flock to one another in classes outside of foundation.”
“We really bonded. As foundation progressed, we felt more
comfortable sharing & discussing topics amongst each other.
Even into our second year, I still feel excited to see people from
my cohort in my foundation semester. There is a special bond
there. When people from my cohort are in my classes now, I
feel more at ease in those classes.”
QUALITATIVE RESULTS
Cohort effect held because it was difficult to “un-cohort”.
“It worked well during the semester, but in spring when we
"un-cohorted" it was difficult only knowing 20 other of the
150 students. Usually only knew 2-3 people per class.”
“I liked the community feel that I got from my cohort; but
once classes started mixing cohorts I felt like I didn't know
any of them. It would have been nice to have more
opportunities to meet all of our entering class.”
QUALITATIVE RESULTS
Personal relationships were the most important. Used those
to grow the other types of relationships
“All three types of networks helped me grow. However, without the
personal commitment, it would not have been as great”
“Personal relationships were most important because grad school
was just so hard. The encouragement from our peers kept us going.”
DISCUSSION
• Cohort Effects remained, even 2 semesters after
classes were no longer taken by cohort
• Students perceived cohort particularly important for
development of initial friendships.
• Friendships are an important foundation for other
types of relationships to form
• Initial cohort membership difficult to transcend in
developing new peer relationships
LIMITATIONS
• Generalizability
• No comparison program
• Focus groups smaller than the recommended 8-12
• Students who returned to participate in the focus groups
may have stronger ties to the school
IMPLICATIONS
• Our research supports the use of cohorts as a part of the
implicit curriculum to enhance peer relationships
• One semester was sufficient to produce lasting effects
• Student supports for transition from cohort-based to
traditional learning models are indicated
• Personal relationships should be acknowledged as
important to the development of academic and
professional support
• Network approach as assessment tool for MSW
programs
ACKNOWLEDGEMENTS
Special thanks to :
Zuniga y Rivero Foundation
University of Houston Graduate of Social Work
Graduate students who assisted with data entry
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