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

Dirk Tempelaar, Bart Rienties, Quan Nguyen

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

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.
Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Computer Supported Education (CSEDU 2018)
PublisherSCITEPRESS
Pages294-301
Number of pages8
Volume1
ISBN (Print)978-989-758-291-2
DOIs
Publication statusPublished - 2018

Cite this

Tempelaar, D., Rienties, B., & Nguyen, Q. (2018). Analysing the Use of Worked Examples and Tutored and Untutored Problem-Solving in a Dispositional Learning Analytics Context. In Proceedings of the 10th International Conference on Computer Supported Education (CSEDU 2018) (Vol. 1, pp. 294-301). SCITEPRESS. https://doi.org/10.5220/0006760202940301