Revealing deep interaction patterns of team learning processes through video-based interactive analysis

Lei Xie, Michael Beyerlein, Soo Jeoung Han

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


New tools provide new lenses for a better understanding of how learning occurs within the team setting. A better understanding of team learning will enable human resource development (HRD) professionals to more effectively develop an enhanced level of performance in the workplace. Since teams represent complex learning systems, traditional questionnaires that take a static ‘snapshot’ of the reality and interviews that capture retrospective member memories fail to reflect the dynamics or the holistic nature of teamwork. Deeper patterns of the dynamics of team learning will provide the foundation for more generalisable theories. We argue that a better understanding of team learning in HRD will grow when scholars generate new models of team learning systems based on new ways of measuring team behaviour that capture the complex interactions among members. In this paper, we propose that video-based interaction analysis can offer more opportunities. We discuss the current research methods issues, profile the current state of the scholarship of team learning, and recommended a new data collection/analysis approach: video-based interactive analysis (VIA).

Original languageEnglish
Pages (from-to)267-287
Number of pages21
JournalInternational Journal of Human Resources Development and Management
Issue number4
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
Copyright © 2021 Inderscience Enterprises Ltd.

All Science Journal Classification (ASJC) codes

  • Organizational Behavior and Human Resource Management


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