Search

Collaborative Problem Solving (CPS) has received increasing attention for its role in promoting learners' cognitive and social development in STEM education. However, little is known about how learners interact dynamically within a group at different time granularities. This gap mainly resulted from overlooking the time dimension of interactions, leading to a lack of nuanced understanding of moment-to-moment interaction in CPS. In this study, we demonstrated the potential of "temporal group interaction density" in modeling online CPS interactions and investigated the impact of temporal interaction density on CPS processes and outcomes. Specifically, we proposed using cumulative weighted density to measure the holistic state of group interactions and explained the differences in group interactions with different collaborative performance and interaction densities by modeling the transition and evolution of interaction sequences through Apriori and cumulative relative centrality. Results indicated that group interaction density cannot directly predict their collaborative performance, but notable differences in interaction patterns existed in the high-performance groups with different interaction densities, while low-performance groups showed interactive commonalities towards the completion of CPS. The findings of this study guided the design of CPS interventions and supported the process mining of CPS interactions, with vital practical implications for CPS assessment and skills development.

Blended learning, integrating online and in-person components, has been increasingly adopted in higher education to enhance students' learning experience and outcomes. While the advantages of blended learning are well-evidenced, research has primarily focused on the online pre-learning component, neglecting the significance of in-class activities. In-class activities play a crucial role in affording active learning opportunities (e.g., discussion, elaboration), necessitating a systemic understanding of their dynamics. The purpose of this study was thus to systemically investigate college students' learning behaviors during in-class activities in a blended course. In-class activities were video-recorded and labelled manually following a coding scheme. By establishing a linear regression model, the study identified listening to the instructor's lecture and taking notes as two predictors of students' learning gains. Additionally, sequential patterns of learning behaviors during in-class activities were examined. The reciprocal interactions between students' behavior of listening to the lecture and their note-taking actions were noted. The findings of this study contributed to a systemic view of blended learning by shedding light on students' learning behaviors and their implications for instructional practice.