Detection of Learning Strategies: A Comparison of Process, Sequence and Network Analytic Approaches

Wannisa Matcha, Dragan Gašević, N. Ahmad Uzir, Jelena Jovanović, Abelardo Pardo, Jorge Maldonado-Mahauad, Mar Pérez-Sanagustín

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

43 Citas (Scopus)

Resumen

Research in learning analytics proposed different computational techniques to detect learning tactics and strategies adopted by learners in digital environments through the analysis of students’ trace data. While many promising insights have been produced, there has been much less understanding about how and to what extent different data analytic approaches influence results. This paper presents a comparison of three analytic approaches including process, sequence, and network approaches for detection of learning tactics and strategies. The analysis was performed on a dataset collected in a massive open online course on software programming. All three approaches produced four tactics and three strategy groups. The tactics detected by using the sequence analysis approach differed from those identified by the other two methods. The process and network analytic approaches had more than 66% of similarity in the detected tactics. Learning strategies detected by the three approaches proved to be highly similar.

Idioma originalInglés
Título de la publicación alojadaTransforming Learning with Meaningful Technologies - 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Proceedings
EditoresMaren Scheffel, Julien Broisin, Viktoria Pammer-Schindler, Andri Ioannou, Jan Schneider
EditorialSpringer Verlag
Páginas525-540
Número de páginas16
ISBN (versión impresa)9783030297350
DOI
EstadoPublicada - 2019
Evento14th European Conference on Technology Enhanced Learning, EC-TEL 2019 - Delft, Países Bajos
Duración: 16 sep. 201919 sep. 2019

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen11722 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia14th European Conference on Technology Enhanced Learning, EC-TEL 2019
País/TerritorioPaíses Bajos
CiudadDelft
Período16/09/1919/09/19

Huella

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