Abstract
Understanding how individuals collaborate with others is a complex undertaking, because collaborative problem-solving (CPS) is an interactive and dynamic process. We attempt to identify distinct collaborative problem-solver profiles of Chinese 15-year-old students on a computer-based CPS task using process data from the 2015 Program for International Student Assessment (PISA, N = 1,677), and further to examine how these profiles may relate to student demographics (i.e., gender, socioeconomic status) and motivational characteristics (i.e., achieving motivation, attitudes toward collaboration), as well as CPS performance. The process indicators we used include time-on-task, actions-on-task, and three specific CPS process skills (i.e., establish and maintain shared understanding, take appropriate action to solve the problem, establish and maintain team organization). The results of latent profile analysis indicate four collaborative problem-solver profiles: Disengaged, Struggling, Adaptive, and Excellent. Gender, socioeconomic status, attitudes toward collaboration and CPS performance are shown to be significantly associated with profile membership, yet achieving motivation was not a significant predictor. These findings may contribute to better understanding of the way students interact with computer-based CPS tasks and inform educators of individualized and adaptive instructions to support student collaborative problem-solving.
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This work was supported and sponsored by Shanghai Pujiang Program [Grant Number 22PJC059].
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Appendix PISA 2015 CPS sample unit: Xandar
OECD (2017), PISA 2015 Results (Volume V): Collaborative Problem Solving, PISA, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264285521-en
Appendix PISA 2015 CPS sample unit: Xandar
The detailed information of the PISA 2015 CPS sample unit, Xandar, can be found at https://www.oecd.org/pisa/test/CPS-Xandar-scoring-guide.pdf.
The unit consists of four independent parts; all parts and all items within each part are independent of one another. No matter which response a student selects for a particular item, the computer agents respond in a way so that the unit converges. All students are hence faced with an identical version of the next item.
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Ma, Y., Zhang, H., Ni, L. et al. Identifying collaborative problem-solver profiles based on collaborative processing time, actions and skills on a computer-based task. Intern. J. Comput.-Support. Collab. Learn 18, 465–488 (2023). https://doi.org/10.1007/s11412-023-09400-5
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DOI: https://doi.org/10.1007/s11412-023-09400-5