@inproceedings{4a63586d8ce24c8cb33c5a97fe886e7e,
title = "Analysing the Use of Worked Examples and Tutored and Untutored Problem-Solving in a Dispositional Learning Analytics Context",
abstract = "The identification of students{\textquoteright} 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.",
keywords = "Blended Learning, Dispositional Learning Analytics, Learning Strategies, Multi-modal data, Prediction Models, Tutored Problem-Solving, Untutored Problem-Solving, Worked Examples",
author = "Dirk Tempelaar and Bart Rienties and Quan Nguyen",
note = "data source: SELF-COLLECTED PRIMARY DATA BASED ON TRACE AND SURVEY DATA ",
year = "2019",
month = apr,
language = "English",
isbn = "978-989-758-367-4",
volume = "2",
series = "Proceedings of the International Conference on Computer Supported Education, CSEDU",
publisher = "SCITEPRESS",
pages = "38--47",
editor = "H Lane and Susan Zvacek and James Uhomoibhi",
booktitle = "Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019)",
}