Detection of learning strategies: a comparison of process, sequence and network analytic approaches

Autor: Jorge Maldonado-Mahauad, Wannisa Matcha, Dragan Gašević, Abelardo Pardo, Jelena Jovanovic, Mar Pérez-Sanagustín, Nora'ayu Ahmad Uzir
Přispěvatelé: Matcha, Wannisa, Gasevic, Dragan, Ahmad Uzir, N., Jovanovic, Jelena, Pardo, Abelardo, Maldonado-Mahauad, Jorge, Pérez-Sanagustín, Mar, 14th European Conference on Technology Enhanced Learning, EC-TEL 2019 Delft, Netherlands 16-19 September 2019
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Lecture Notes in Computer Science ISBN: 9783030297350
EC-TEL
Popis: 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.
Databáze: OpenAIRE