A Multi-Method Approach to Capture Quality of Collaborative Group Engagement

EasyChair Preprint no. 9889

Abstract

Multi-method approaches are an emerging trend in CSCL research as they allow to paint a more comprehensive picture of complex group learning processes than using a single method. In this contribution, we combined measures from different data sources to capture the quality of collaborative group engagement (QCGE) in CSCL-groups: QCGE-self-assessments, QCGE-ratings of verbal group communication, and video recorded nonverbal group behaviors. Using different methods of analysis, we visualized, described, and analyzed the data and related the measures to each other. Here, we present results suggesting that measures from different data sources are interrelated: For instance, nonverbal behavior (like nodding the head) is related to high QCGE-ratings of verbal communications. Results are preliminary and show disparities, too. Yet, we conclude that the multi-method approach results in a more comprehensive understanding of QCGE. Feasibility and suitability of the multi-method approach are discussed and conclusions for future research are drawn.

Keyphrases: Computer Supported Collaborative Learning, multi-method approach, nonverbal group behavior, quality of collaborative group engagement

@Booklet{EasyChair:9889,
  author = {Lisa Paneth and Loris Jeitziner and Oliver Rack and Carmen Zahn},
  title = {A Multi-Method Approach to Capture Quality of Collaborative Group Engagement},
  howpublished = {EasyChair Preprint no. 9889},

  year = {EasyChair, 2023}}