Linguistic coherence predicts productive collaboration, strengthened by joint visual attention data¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2025 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? In one reviewed study, linguistic coordination and coherence by which students build on each other's ideas indicated productive collaborative learning, and adding joint visual attention data strengthened the predictive power. → Rachelle Esterhazy 2025

Evidence¶

Rachelle Esterhazy 2025¶

Rachelle Esterhazy, Rogers Kaliisa, Daniel Sanchez, Malcolm Langford and Crina Damsa. (2025). Advancing Multimodal Collaboration Analytics: A Scoping Review. Journal of Learning Analytics 12(2). https://doi.org/10.18608/jla.2025.8625

q2 · i? · review · r2

The review reports, citing Schneider and Pea (2015), a methodological study combining NLP with joint visual gaze analysis to predict productive collaborative learning markers during problem-solving. "linguistic coordination and coherence by which students build on each other's ideas is indicative of productive collaborative learning". No effect sizes are printed.

"The authors find that the linguistic coordination and coherence by which students build on each other's ideas is indicative of productive collaborative learning, as rated by an external observer. The predictive power of linguistic coherence is further strengthened by including data on joint visual attention."

Discussion¶

Learner Variables¶

• Visual Processing — moderator: an instructional effect differs with it

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