Thomas Kindermann

Date of Award

Winter 3-21-2016

Document Type


Degree Name

Master of Science (M.S.) in Psychology



Physical Description

1 online resource (x, 265 pages)


Social networks -- Research -- Methodology, Interpersonal relations in children -- Research -- Methodology, Academic achievement -- Research




Too many students leave school without even the essential skills (ACT, 2011), and many others are so drained by the experience they lack a desire to continue on to a post-secondary education. Academic engagement has emerged as a construct representing students’ personal investment in school (Greenwood, Delquadri, & Hall, 1984), and may be a psychological variable which can be intervened on. However, interventions must occur as quickly as possible to maximize their efficiency (Heckman, 2007). Students’ peer groups may be a particularly potent venue of intervention, however several options exist for how to go about measuring their social networks.

In this thesis, social networking data of the only middle school of a small town in the north-eastern United States is analyzed to determine the properties of two collection methods (self-reported networks and participant observations) and four network identification methods (probability scores, reciprocal nominations, factor-analyses, and rule-based). Analyses overwhelmingly supported participant observations as a more inclusive, less biased data collection method than self-reports. Meanwhile, hypothesis tests were somewhat mixed on the most inclusive, least biased network identification method, but after a consideration of the findings and the structural properties of each network, the probability score method was deemed the most useful network. Implications, future research, strengths, and limitations are discussed.

Persistent Identifier