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Investigating learning strategies in a dispositional learning analytics context: the case of worked examples

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Published:07 March 2018Publication History

ABSTRACT

This study aims to contribute to recent developments in empirical studies on students' learning strategies, whereby the use of trace data is combined with self-report data to distinguish profiles of learning strategy use [3--5]. We do so in the context of an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended learning. Building on our previous work which showed marked differences in how students used worked examples as a learning strategy [7, 11], this study compares different profiles of learning strategies with learning approaches, learning outcomes, and learning dispositions. One of our key findings is that deep learners were less dependent on worked examples as a resource for learning, and that students who only sporadically used worked examples achieved higher test scores.

References

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  1. Investigating learning strategies in a dispositional learning analytics context: the case of worked examples

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            cover image ACM Other conferences
            LAK '18: Proceedings of the 8th International Conference on Learning Analytics and Knowledge
            March 2018
            489 pages
            ISBN:9781450364003
            DOI:10.1145/3170358

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            New York, NY, United States

            Publication History

            • Published: 7 March 2018

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            LAK '18 Paper Acceptance Rate35of115submissions,30%Overall Acceptance Rate236of782submissions,30%

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