Abstract
AbstractBeing aware of the progress towards one’s goals is considered one of the main characteristics of the self-regulation process. This is also the case for collaborative problem solving, which invites group members to metacognitively monitor the progress with their goals and externalize it in social interactions while solving a problem. Monitoring challenges can activate group members to control the situation together, which can be seen as adjustments on different systemic levels (physiological, psychological, and interpersonal) of a collaborative group. This study examines how the pivotal role of monitoring for collaborative problem solving is reflected in interactions, performance, and interpersonal physiology. The study has foci in two central characteristics of monitoring interactions that facilitate groups’ regulation in reaching their goals. First is valence of monitoring, indicating whether the group members think they are progressing towards their goal or not. Second is equality of participation in monitoring interactions between group members. Participants of the study were volunteering higher education students (N = 57), randomly assigned to groups of three members whose collaborative task was to learn to run a business simulation. The collaborative task was video recorded, and the physiological arousal of each participant was recorded from their electrodermal activity. The results of the study suggest that both the valence and equality of participation are identifiable in monitoring interactions and they both positively predict groups’ performance in the task. Equality of participation to monitoring was not related to the interpersonal physiology. However, valence of monitoring was related to interpersonal physiology in terms of physiological synchrony and arousal. The findings support the view that characteristics of monitoring interactions make a difference to task performance in collaborative problem solving and that interpersonal physiology relates to these characteristics.
Funder
University of Oulu including Oulu University Hospital
Publisher
Springer Science and Business Media LLC
Reference109 articles.
1. Ackerman, R., & Thompson, V. A. (2017). Meta-reasoning: Monitoring and control of thinking and reasoning. Trends in Cognitive Sciences, 21(8), 607–617. https://doi.org/10.1016/j.tics.2017.05.004
2. Ahonen, L., Cowley, B. U., Hellas, A., & Puolamäki, K. (2018). Biosignals reflect pair-dynamics in collaborative work: EDA and ECG study of pair-programming in a classroom environment. Scientific Reports, 8(1), 3138. https://doi.org/10.1038/s41598-018-21518-3
3. Amon, M. J., Vrzakova, H., & D’Mello, S. K. (2019). Beyond dyadic coordination: Multimodal behavioral irregularity in triads predicts facets of collaborative problem solving. Cognitive Science, 43(10), 1–22. https://doi.org/10.1111/cogs.12787
4. Azevedo, R. (2014). Issues in dealing with sequential and temporal characteristics of self- and socially-regulated learning. Metacognition and Learning, 9(2), 217–228. https://doi.org/10.1007/s11409-014-9123-1
5. Azevedo, R., & Witherspoon, A. M. (2009). Self-regulated learning with hypermedia. In Hacker, D. J., Dunlosky, J., & Graesser, A. C. (Eds.), Handbook of metacognition in education (pp. 319–339). Routledge
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献