Abstract
AbstractSocial network structures have an additional effect on success other than individual factors. Whether this is true for failure, the opposite of success, still remains unclear. This paper focuses on the associations between academic failures, that defined by not passing course exams, and campus social networks based on students’ co-location occurrences. A novel method with statistical validation is first established to infer co-location social networks reliably from campus behaviors recorded by smart cards. It is found that network structures indicated by degree and clustering are indeed significantly associated with academic failures and failed students usually locate in small, dense but heterogeneous clusters. While their connections are more stable over time, failed students seem to be not positively influenced by those non-failed ones and even demonstrate a failure momentum. In fact, further exploitations imply that failed students have less incentives to adjust their social structures when compared to the non-failed ones. Additionally, we show that messages reflected in co-location social networks and behavioral activities indeed help predict failures and the network snapshot at mid-term offers competent prediction power on individual academic failure such that interventions in pursuit of avoiding failures can be applied within a substantial time window. Our findings underline the importance of understanding co-location social networks beyond failure in educational settings.
Funder
national natural science foundation of china
the emerging interdisciplinary project of cufe
educational reform project of School of Economics and Management, Beihang University
disciplinary funding of Central University of Finance and Economics
program for innovation research in central university of finance and economics
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computer Science Applications,Modeling and Simulation
Cited by
5 articles.
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