Authors:
Dirk Tempelaar
1
;
Anikó Bátori
2
and
Bas Giesbers
2
Affiliations:
1
School of Business and Economics, Department of Quantitative Economics, Maastricht University, Maastricht, The Netherlands
;
2
School of Business and Economics, Department of Educational Research and Development, Maastricht University, Maastricht, The Netherlands
Keyword(s):
Dispositional Learning Analytics, Learning Strategies, Self-Regulated Learning, Problem-Based Learning, Higher Education.
Abstract:
What can we learn from dispositional learning analytics about how first-year business and economics students approach their introductory math and stats course? This study aims to understand how students engage with learning tasks, tools, and materials in their academic pursuits. It uses trace data, initial assessments of students’ learning attitudes, and survey responses from the Study of Learning Questionnaire (SLQ) to analyse their preferred learning strategies. An innovative aspect of this research is its focus on clarifying how learning attitudes influence and potentially predict the adoption of specific learning strategies. The data is examined to detect clusters that represent typical patterns of preferred strategies, and relate these profiles to students’ learning dispositions. Information is collected from two cohorts of students, totalling 2400 first-year students. A pivotal conclusion drawn from our research underscores the importance of adaptability, which involves the cap
acity to modify preferred learning strategies based on the learning context. While it is crucial to educate our students in deep learning strategies and foster adaptive learning mindsets and autonomous regulation of learning, it is equally important to acknowledge scenarios where surface strategies and controlled regulation may offer greater effectiveness.
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