The Sequence Matters in Learning - A Systematic Literature Review

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Abstract

Describing and analysing learner behaviour using sequential data and analysis is becoming more and more popular in Learning Analytics. Nevertheless, we found a variety of definitions of learning sequences, as well as choices regarding data aggregation and the methods implemented for analysis. Furthermore, sequences are used to study different educational settings and serve as a base for various interventions. In this literature review, the authors aim to generate an overview of these aspects to describe the current state of using sequence analysis in educational support and learning analytics. The 74 included articles were selected based on the criteria that they conduct empirical research on an educational environment using sequences of learning actions as the main focus of their analysis. The results enable us to highlight different learning tasks where sequences are analysed, identify data mapping strategies for different types of sequence actions, differentiate techniques based on purpose and scope, and identify educational interventions based on the outcomes of sequence analysis.
Original languageEnglish
Title of host publicationLAK 2024 Conference Proceedings - 14th International Conference on Learning Analytics and Knowledge
Subtitle of host publicationProceedings of the 14th Learning Analytics and Knowledge Conference
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages263–272
Number of pages10
ISBN (Print)979-8-4007-1618-8
DOIs
Publication statusPublished - 2024

Publication series

NameACM International Conference Proceeding Series

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