Mapping out the structural relationship of middle school students’ use of talk and gestures and group outcomes’ quality in collaborative science problem-solving activities

ABSTRACT

The current study explores the connection and affordances of talk and gesture in collaborative science problem-solving activities using an emerging analytical approach. A total of 15 three to five-member groups of middle school students participated in a set of clinical collaborative science problem-solving activities. Six groups (three low- and three high-performing groups) were selected for further analyses. The data consisted of successive statements in student conversations that were coded as different types of talk and gestures. Pearson Phi correlation test and Epistemic Network Analysis were used to analyze the data. We found that certain types of gesture were moderately associated with certain types of talk. In addition, we found high-performing groups were significantly different from low-performing groups in the use of higher cognitive engagement and collaborative regulation talks. We did not find a significant difference in the use of gestures on their own. However, we found that when talk and gestures were combined, high-performing groups tended to use higher cognitive engagement and collaborative regulation talks with representing and pointing gestures. These findings support previous studies on the affordances of talk and gesture in collaborative science activities and provide more evidence for how multimodality is important in science learning.

KEYWORDS:

• Collaboration
• gesture
• talk

Acknowledgment

We would like to thank our participants and to everyone who has been supporting the data collection process and the video annotation work for this project. We would also like to thank Jessica Vandenberg who helped with the analysis and Ron Fried, and Mindy Hsiao who supported the instruments, data collection, and coding. This material is based upon work supported by the National Science Foundation through Engineering Education, Cyberlearning & Future Learning Technology program grant # 2016849 and an internal SRI International research and development grant. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the aforementioned funders.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Science Foundation (NSF) through Engineering Education, Cyberlearning & Future Learning Technology program [grant Number 2016849] and internally by SRI International.