Optimal clustering of five-channel CPS sequences detected three types of collaborative patterns among graduate student groups¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Multichannel sequence analysis with Ward's clustering identified three distinct collaborative pattern types (5, 14, and 5 CPS activities for Types 1–3), with the four groups distributed relatively equally across the three types. → Fan Ouyang 2023

Evidence¶

Fan Ouyang 2023¶

Fan Ouyang, Weiqi Xu, Mutlu Cukurova. (2023). An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems perspective. Intern. J. Comput.-Support. Collab. Learn (2023) 18:39–66. https://doi.org/10.1007/s11412-023-09387-z

q2 · i? · associational · r1

Application of the MCSA pipeline (optimal matching plus Ward's clustering) to 24 five-channel sequences from 24 CPS datasets (11,477 coded units; Mean = 478.21, SD = 79.18). "The optimal clustering results generated from Layer 2 revealed three types of collaborative patterns", and group distribution across types was relatively equal.

"The optimal clustering results generated from Layer 2 revealed three types of collaborative patterns, consisting of 5, 14, and 5 CPS activities for Type 1, Type 2, and Type 3, respectively"

Discussion¶

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