Research output

Analysing the Use of Worked Examples and Tutored and Untutored Problem-Solving in a Dispositional Learning Analytics Context

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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Abstract

The identification of students’ learning strategies by using multi-modal data that combine trace data with self-report data is the prime aim of this study. Our context is an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended learning. Building on previous studies in which we found marked differences in how students use worked examples as a learning strategy, we compare different profiles of learning strategies on learning dispositions and learning outcome. Our results cast a new light on the issue of efficiency of learning by worked examples, tutored and untutored problem-solving: in contexts where students can apply their own preferred learning strategy, we find that learning strategies depend on learning dispositions. As a result, learning dispositions will have a confounding effect when studying the efficiency of worked examples as a learning strategy in an ecologically valid context.

    Research areas

  • Blended Learning, Dispositional Learning Analytics, Learning Strategies, Multi-modal data, Prediction Models, Tutored Problem-Solving, Untutored Problem-Solving, Worked Examples
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Details

Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019)
EditorsH Lane, Susan Zvacek, James Uhomoibhi
Place of PublicationLisbon, Portugal
PublisherSCITEPRESS
Pages38-47
Number of pages10
Volume2
ISBN (Print)978-989-758-367-4
Publication statusPublished - Apr 2019

Publication series

NameProceedings of the International Conference on Computer Supported Education, CSEDU
PublisherSCITEPRESS – Science and Technology Publications, Lda
ISSN (Print)2184-5026