THE EVOLUTION OF STUDENT RELATIONSHIPS OVER TIME IN A COHORT-BASED MSW PROGRAM NOVEMBER 5, 2016 R EBECCA L. M AULDIN , LMSW L IZA B ARROS -L ANE , LMSW S ARAH C . N ARENDORF , 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
COHORT-BASED EDUCATION 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)
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 1 st 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 1 st semester (Fall 2014) • End of 1 st semester (Fall 2014) • End of 3 rd semester (Fall 2015) Multi-method qualitative data Open-ended question on 4 th survey Three 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) Note. *Race/Ethnicity Hispanic 18.9 (18) categories based on those White 43.2 (41) used in academic records 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)
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
AVERAGE NUMBER OF TIES PER STUDENT 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
GENERAL SOCIAL TIES: 1 ST SEMSTER, MID-SEMESTER
GENERAL SOCIAL TIES: END OF 1 ST SEMESTER
GENERAL SOCIAL TIES: END OF 3 RD SEMESTER
Odds Ratios from QAP Logistic Regression Analyses Predicting Friendship Ties at the end of the 3rd semester (n = 97) 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 R 2 .003 ** .18 *** .36 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Odds Ratios from QAP Logistic Regression Analyses Predicting Friendship Ties at the end of the 3rd semester (n = 97) 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 R 2 .003 ** .18 *** .36 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Odds Ratios from QAP Logistic Regression Analyses Predicting Academic Ties at the end of the 3rd semester (n = 97) 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 R 2 .001 * .20 *** .25 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Odds Ratios from QAP Logistic Regression Analyses Predicting Academic Ties at the end of the 3rd semester (n = 97) 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 R 2 .001 * .20 *** .25 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Odds Ratios from QAP Logistic Regression Analyses Predicting Professional Ties at the end of the 3rd semester (n = 97) 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 R 2 .006 ** .06 *** .11 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Odds Ratios from QAP Logistic Regression Analyses Predicting Professional Ties at the end of the 3rd semester (n = 97) 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 R 2 .006 ** .06 *** .11 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Regression coefficients from Double Dekker Semi- Partialling QAP Multiple Regression Analyses Predicting Multiplex Relationships at the end of the 3rd semester (n = 97) 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 *** .36 *** .16 *** .18 *** Intercept R 2 .007 *** .25 *** .39 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
Regression coefficients from Double Dekker Semi- Partialling QAP Multiple Regression Analyses Predicting Multiplex Relationships at the end of the 3rd semester (n = 97) 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 *** .36 *** .16 *** .18 *** Intercept R 2 .007 *** .25 *** .39 *** Note . *p ≤ .05, ***p ≤ .001. p-values were determined by 10,000 permutations
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