subject predicate object context
53925 Creator c9d52ef4a11ad1277436a89c20d0a5d4
53925 Creator 71122b7715e55a3f53d5c14540adcbbb
53925 Creator ext-b75cd7ad6e4578e06a485e7fe5a66076
53925 Date 2018-03-07
53925 Is Part Of repository
53925 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.
53925 authorList authors
53925 presentedAt ext-5e6feee07853af2e87f9953cf323404e
53925 status peerReviewed
53925 type AcademicArticle
53925 type Article
53925 label Tempelaar, Dirk; Rienties, Bart and Nguyen, Quan (2018). Investigating learning strategies in a dispositional learning analytics context: the case of worked examples. In: Proceedings of the 8th International Conference on Learning Analytics and Knowledge, ACM, New York, pp. 201–205.
53925 label Tempelaar, Dirk; Rienties, Bart and Nguyen, Quan (2018). Investigating learning strategies in a dispositional learning analytics context: the case of worked examples. In: Proceedings of the 8th International Conference on Learning Analytics and Knowledge, ACM, New York, pp. 201–205.
53925 Publisher ext-2af1883e4bbfa0356fcedb366171cb38
53925 Title Investigating learning strategies in a dispositional learning analytics context: the case of worked examples
53925 in dataset oro