Premium
Example‐based learning: New theoretical perspectives and use‐inspired advances to a contemporary instructional approach
Author(s) -
Hoogerheide Vincent,
Roelle Julian
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.3706
Subject(s) - psychology , cognition , set (abstract data type) , focus (optics) , cognitive science , learning theory , social learning , learning sciences , extension (predicate logic) , field (mathematics) , mathematics education , experiential learning , computer science , pedagogy , physics , mathematics , neuroscience , pure mathematics , optics , programming language
Summary Decades of research has shown that example‐based learning is an effective instructional strategy for learning new skills. The field of learning from examples is seeing a shift in focus towards more innovative and use‐inspired research, in part because the use of examples for informal and formal learning purposes has mushroomed. This special issue comprises a set of eight papers in which students learned a procedural skill from worked examples or modeling examples. Each study characterizes a recent development towards more innovative example‐based learning research. These developments are: (a) the integration of social‐cognitive and cognitive example research, (b) the integration of example‐based learning and analogical reasoning research, (c) the extension of traditional Cognitive Load Theory effects, (d) a greater focus on learning from (productive) errors, and (e) more research on individual differences. This special issue concludes with insightful commentary articles written by Prof. Dr. Katharina Scheiter and Prof. Dr. Richard Mayer.