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Multilayered temporal analysis of collaborative-learning roles

Research Method · All research methods
Evidence · 2 claims (2 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 2 claims rest on one study

Description

This analytical pattern combines several learning-analytics methods into layers to capture role dynamics over time: latent class analysis converts CoI-coded discourse into role states, epistemic network analysis maps code co-occurrence within roles, sequence mining orders roles across weeks, and Markov process mining estimates transition probabilities within trajectories. The authors motivate the layering with Reimann et al.'s warning that "relying on a single sequential approach can hide in details due to the ontological flatness of educational data", so that "such a combination yields a much better understanding of the temporal aspects of students' roles".

Accounts

  • Multilayered temporal analysis pattern for collaborative learning: roles as states, sequences, and trajectories: This analytical pattern combines several learning-analytics methods into layers to capture role dynamics over time: latent class analysis converts CoI-coded discourse into role states, epistemic network analysis maps code co-occurrence within roles, sequence mining orders roles across weeks, and Markov process mining estimates transition probabilities within trajectories. The authors motivate the layering with Reimann et al.'s warning that "relying on a single sequential approach can hide in details due to the ontological flatness of educational data", so that "such a combination yields a much better understanding of the temporal aspects of students' roles". (Ramy Elmoazen et al. (2025))
  • CPS circles: visualizations of the temporal interchange of social and cognitive states and state changes during CPS sessions: CPS circles are visualizations developed for this study that display, clockwise, social and cognitive state changes and their intensity during the sessions, alongside the periods when macro-script cards were discussed. "The intensity of the appearance, reflecting the number of social or cognitive sub-elements activated at a specific point, is visualized by the height of the 'ray.'" Dark gray marks social states and light gray cognitive states, giving an overview of "the alignment of CPS actions over time" across each group and task. (Johanna Pöysä-Tarhonen et al. (2022))

Claims

Key Sources

  • Ramy Elmoazen, Mohammed Saqr, Laura Hirsto, Matti Tedre. (2025). Capturing temporal pathways of collaborative roles: A multilayered analytical approach using community of inquiry. Intern. J. Comput.-Support. Collab. Learn. https://doi.org/10.1007/s11412-024-09431-6
  • Johanna Pöysä-Tarhonen, Päivi Häkkinen, Pasi Tarhonen, Piia Näykki, Sanna Järvelä. (2022). “Anything taking shape?” Capturing various layers of small group collaborative problem solving in an experiential geometry course in initial teacher education. Instructional Science. https://doi.org/10.1007/s11251-021-09562-5
Page metadata
Field Value
type research-method
id multilayered-temporal-analysis-of-collaborative-learning-roles
title Multilayered temporal analysis of collaborative-learning roles
description This analytical pattern combines several learning-analytics methods into layers to capture role dynamics over time: latent class analysis converts CoI-coded discourse into role states, epistemic network analysis maps code co-occurrence within roles, sequence mining orders roles across weeks, and Mar
status review
generated by process:settle-candidates on 2026-10-18
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