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Individual differences in the preference for worked examples: Lessons from an application of dispositional learning analytics
Author(s) -
Tempelaar Dirk T.,
Rienties Bart,
Nguyen Quan
Publication year - 2020
Publication title -
applied cognitive psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 100
eISSN - 1099-0720
pISSN - 0888-4080
DOI - 10.1002/acp.3652
Subject(s) - psychology , preference , learning analytics , mathematics education , process (computing) , cluster analysis , computer science , data science , artificial intelligence , microeconomics , operating system , economics
Summary Worked‐examples have been established as an effective instructional format in problem‐solving practices. However, less is known about variations in the use of worked examples across individuals at different stages in their learning process in student‐centred learning contexts. This study investigates different profiles of students' learning behaviours based on clustering learning dispositions, prior knowledge, and the choice of feedback strategies in a naturalistic setting. The study was conducted on 1,072 students over an 8‐week long introductory mathematics course in a blended instructional format. While practising exercises in a digital learning environment, students can opt for tutored problem solving, untutored problem solving, or call worked examples. The results indicated six distinct profiles of learners regarding their feedback preferences in different learning phases. Finally, we investigated antecedents and consequences of these profiles and investigated the adequacy of used feedback strategies concerning ‘help‐abuse’. This research indicates that the use of instructional scaffolds as worked‐examples or hints and the efficiency of that use differs from student to student, making the attempt to find patterns at an overall level a hazardous endeavour.