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Evolutionary Clustering of Apprentices' Self-Regulated Learning Behavior in Learning Journals

Paola Mejia-Domenzain, Mirko Marras, Christian Giang, Alberto Cattáneo, Tanja Käser

IEEE Transactions on Learning Technologies · 2022

Pipeline from raw learning-journal event sequences through feature engineering and similarity computation, to evolutionary clustering with temporal smoothing and spectral clustering, ending in k-modes profile clustering.
Pipeline from raw learning-journal event sequences through feature engineering and similarity computation, to evolutionary clustering with temporal smoothing and spectral clustering, ending in k-modes profile clustering. · Figure from the paper.

FindingAcross 183 chef apprentices and more than 121,000 learning-journal entries, the method tracked how learning patterns changed over time and produced interpretable profiles.

Abstract

Learning journals are increasingly used in vocational education to foster self-regulated learning and reflective learning practices. However, for many apprentices, documenting working experiences is a difficult task. In this article, we profile apprentices' learning behavior in an online learning journal. Based on a pedagogical framework, we propose a novel multistep clustering pipeline that integrates different learning dimensions into a combined profile. Specifically, the profiles are described in terms of effort, consistency, regularity, help-seeking behavior, and quality of the written entries. Our results on two populations of chef apprentices (183 apprentices) interacting with an online learning journal (over 121K entries) show that our pipeline captures changes in learning patterns over time and yields interpretable profiles that can be related to academic performance. The obtained profiles can be used as a basis for personalized interventions, with the ultimate goal of improving the apprentices' learning experience.

Venue
IEEE Transactions on Learning Technologies
Year
2022
DOI
10.1109/tlt.2022.3195881
Licence
CC-BY-NC-ND
Topics
Online Learning and Analytics, Innovative Teaching and Learning Methods, Knowledge Management and Sharing

Cite this paper

Paola Mejia-Domenzain, Mirko Marras, Christian Giang, Alberto Cattáneo & Tanja Käser (2022) Evolutionary Clustering of Apprentices' Self-Regulated Learning Behavior in Learning Journals. IEEE Transactions on Learning Technologies. https://doi.org/10.1109/tlt.2022.3195881

BibTeX
@article{mejiadomenzain2022evolutiona,
  title         = {{Evolutionary Clustering of Apprentices' Self-Regulated Learning Behavior in Learning Journals}},
  author        = {Paola Mejia-Domenzain and Mirko Marras and Christian Giang and Alberto Cattáneo and Tanja Käser},
  year          = {2022},
  journal       = {IEEE Transactions on Learning Technologies},
  publisher     = {Institute of Electrical and Electronics Engineers},
  doi           = {10.1109/tlt.2022.3195881},
  url           = {https://paola-md.github.io/papers/evolutionary-clustering-of-apprentices-self-regulated-learning-behavior-.html}
}