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Learning events and sequences

What do learners do in collaborative datadriven learning

Bibliographic Data

ID22299128
AuthorsJarvis Looi (0009-0008-7772-0555, ATILF (CNRS-University of Lorraine), corresponding author)
Year2026
Publication date2026-05-08
Open AccessYes
TypeARTICLE
VenueITL - International Journal of Applied Linguistics (JOURNAL)
Journal identifiersISSN: 0019-0829 • E-ISSN: 1783-1490
PublisherJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/itl.25011.loo
OpenAlexW7160653862
LanguageEN
References cited46

While frameworks like Illustration-Interaction-Intervention-Induction often guide data-driven learning (DDL), few studies examine whether they reflect actual learner behaviour or a prescriptive ideal. This paper analysed field recordings and worksheets from 61 participants using grounded theory, identifying ‘learning events’ (i.e., what learners do) and ‘learning sequences’ (i.e., when and why they do so), grounded in constructivism, sociocultural theory, and the Noticing Hypothesis. These macro- and micro-level insights reveal DDL as a non-linear, iterative process shaped by data observation, repeated rule extraction and testing. The findings inform DDL studies by highlighting the importance of considering non-linearity in task design and providing regular scaffolding. Beyond DDL, the paper contributes to a broader understanding of collaborative, inductive learning and offers implications for task design across educational contexts

Field (mathematics) · Grounded theory · Process (computing) · Set (abstract data type) · Sociocultural evolution · Task (project management) · Task Analysis · Evaluation of Teaching Practices · Innovative Teaching and Learning Methods · Science Education and Pedagogy

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