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Updated: Jan 22, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
Published on: September 27, 2020
Triangulating multimodal data: Data of interaction logs, learning achievement, and motivation of L2 learners in a
Mihwa Lee1,2, Björn Rudzewitz1,2, Yushan Ye3
1Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Walter-Simon-Straße 12, Tübingen, 72072, Germany.
Abstract:
This dataset comprises detailed interaction log data from 201 learners engaged in second language (L2) English reading assignments with an intelligent computer-assisted language learning (ICALL) system over a six-week period. After preprocessing, a total of 116,168 clickstream data points were generated, capturing learners' behaviours, such as navigation patterns and task engagement within the system. In addition to the interaction logs, the dataset includes learners' L2 reading proficiency test scores collected before and after the learning period and self-reported measures of motivation toward the subject. These multimodal data provide valuable insights into how learners engage with online learning materials, how person-level factors such as motivation interact with digital reading behaviours, and how digital traces can be used to predict learning achievement.
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