The Social Networks of College Students in Learning Communities: The Social Networks of College Students in Learning Communities Gale Stuart, Doctoral Candidate
UCLA Graduate School of Education & Information Studies
Social Research Methodology Division
Research Analyst
Texas A&M University-Corpus Christi
February 18, 2007
Learning Communities in Higher Education: Learning Communities in Higher Education Theoretical Rationale:
Social learning
Student involvement
Peer interactions
Small groups
Connected curricula
Goals of Learning Communities: Goals of Learning Communities Increase involvement
Develop a sense of belonging
Increase awareness of connections between courses or disciplines
Enhance critical thinking skills
Outcomes of Learning Communities: Outcomes of Learning Communities Higher retention
Higher GPAs
Higher satisfaction with college
Higher intellectual skills functioning
Greater gains in social and personal development
Focus of this study:: Focus of this study:
Do the social relationships that students may form in learning communities have any impact on college outcomes such as GPA, persistence, or satisfaction with the college experience?
Method: Social Network Analysis: Method: Social Network Analysis A technique that considers social relations, from families up to nations. Social networks have been found to play a critical role in determining the way problems are solved, how organizations are run, and the degree to which individuals achieve their goals
Attribute data versus Relational data
Applications of Social Network Analysis:: Applications of Social Network Analysis: Study the spread of HIV in a prison system
Understand terrorist networks
Identify key players in an organization
Improve the functioning of a project team
Expose financial flows to investigate criminal behavior
Map communities of expertise in medical fields
Study the adoption of contraceptive techniques in third world countries
Explore power relations between countries
Network Perspectives: Network Perspectives Ego-centric perspective
Socio-centric perspective
Ego-centric network: Ego-centric network ● ● ● ● ● Ego A B C D
Types of Network Measures for Ego-centric Networks: Types of Network Measures for Ego-centric Networks Number sent
Number received
Number reciprocated
Personal Network Density
Indegree centrality
Outdegree centrality
Betweenness centrality
Comparison of Ego-centric Measures : Comparison of Ego-centric Measures 22 2 8
Socio-centric Networks: Socio-centric Networks
Types of Network Measures for Socio-centric Networks: Types of Network Measures for Socio-centric Networks Number of links
Average number sent
Density
Percent reciprocated
Number of isolates
Average Path Length
Clustering Coefficient
Centralization
A Comparison of Friendship Networks from Two Classes:: A Comparison of Friendship Networks from Two Classes: Friends Network 1 Friends Network 2
Site of Study: Site of Study Texas A&M University-Corpus Christi, a regional university in south Texas
Enrollment approx. 8,500
38% Hispanic; 53% White
62% Female
65% Full-time
Fall 2006 first-year class = 1,699
First Year Learning Community Program Design: First Year Learning Community Program Design
Fall 2006 Design: Fall 2006 Design 7 Triads/Tetrads, approximately 150 students each
Approximately 6 Cohorts per Triad/Tetrad, 25 students each meeting in Freshman Seminar classes
52 total cohorts in Freshman Seminar with a total of 1,243 first-year students
The Data: The Data On-line survey administered in Freshman Seminar class in late October 2006
70% Response rate
Confidential not anonymous
Background variables matched from university student records
Items on the Instrument: Items on the Instrument How many hours per week do you study?
How many hours per week do you work? (on/off campus)
Pedagogical measures
Social Support items
Quality of Life items
Attitudes toward Freshman Seminar items
Sense of belongingness to the institution item
Satisfaction with college items
Three Network Items:: Three Network Items: Select up to 7 people from your Freshman Seminar Class who:
You consider to be friends
You study with
You would share a secret with
Dependent Variables: Dependent Variables Cumulative GPA in the Fall 2006 Semester (from matched university records)
Satisfaction with the College experience (from survey items)
Re-enrollment in the spring semester (not yet available)
Preliminary Results – Predicting GPA Ego-centric Network Measures (n=571, r-square = .229): Preliminary Results – Predicting GPA Ego-centric Network Measures (n=571, r-square = .229)
Preliminary Results – Predicting Mean GPA Socio-centric Measures (n=52, r-square = .318) : Preliminary Results – Predicting Mean GPA Socio-centric Measures (n=52, r-square = .318)
Once we control for High School Rank, the clustering coefficient becomes important in predicting average class GPA:: Once we control for High School Rank, the clustering coefficient becomes important in predicting average class GPA: Mean GPA = 3.05
N= 24
Clustering Coefficient = 34.63 Mean GPA = 2.59
N= 25
Clustering Coefficient = 11.29
Preliminary Results – Predicting Mean Global Satisfaction with the College Experience Socio-centric Measures n = 52, r-square = .429: Preliminary Results – Predicting Mean Global Satisfaction with the College Experience Socio-centric Measures n = 52, r-square = .429
Interpretation: Interpretation Once we control for social support and the number of hours students spend socializing with their friends, having at least one person in their freshman seminar class who they can trust is strongly related to higher satisfaction with their college experience.
Early Conclusions: Early Conclusions Aspects of the bonds that students make in their Freshman Seminar classes do predict academic achievement
Analysis of satisfaction with the overall college experience outcome indicates that having a close bond with someone in their learning community class has a positive influence
Retention to the next term is an important outcome that is not available for analysis at this time
Research Implications of the Method: Research Implications of the Method Social network analysis can be used to investigate the relationships between pedagogy and outcomes
The importance of students’ relationships with each other in the context of academic success can be measured
Can aid in early recognition of situations that may require intervention
Thank you!: Thank you! Contact Information:
Gale Stuart
Research Analyst
Texas A&M University-Corpus Christi
Gale.Stuart@tamucc.edu
UCLA Doctoral Candidate
gstuart@ucla.edu