Social capital leveraging knowledge-sharing ties and learning performance in higher education: evidence from social network analysis in an engineering classroom.

Seung-hyun Han, Eunjung Grace Oh, Sung “Pil” Kang

Research output: Contribution to journalArticlepeer-review

Abstract

With the growing attention to the effective use of social network analysis in explaining student learning in STEM (science, technology, engineering, and mathematics) education, the authors explore why college students share knowledge and how they achieve their learning in a laboratory class. In particular, the authors investigate how the social capital each student builds influences individual knowledge sharing and its related learning. The authors establish a research model derived from social capital theory that explains the relational, structural, and cognitive capital the class builds. Network data from 120 students in a lab class in a mechanical engineering department in the United States were collected and analyzed to test the research model and hypotheses using the multiple regression quadratic assignment procedure and UCINET. The findings show that the knowledge sharing mechanism and student learning outcomes can be explained in terms of their social capital within social networks. Last, the authors discuss the theoretical and practical implications for college student learning in a laboratory class in STEM education.

Original languageEnglish (US)
JournalAERA Open
Volume8
DOIs
StatePublished - Apr 2022

Keywords

  • knowledge sharing
  • learning performance
  • social capital
  • social network analysis

ASJC Scopus subject areas

  • Education
  • Social Sciences (miscellaneous)
  • Developmental and Educational Psychology

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