The worked-example effect using ill-defined problems: Learning to recognise designers' styles

By A. Rourke, John Sweller. 2009

133 citations recorded by the source corpus.

Abstract This research uses cognitive load theory and theories of visual literacy to provide a theoretical underpinning for techniques to improve students' ability to recognise designers' styles in higher education. Using a lecture followed by tutorial format, students were required to learn the characteristics needed to identify a designer's work either by studying worked examples or by completing problem-solving tasks. The principle conclusion drawn from two experiments was that novice learners who have a moderate level of visual literacy skills are more successful at identifying a designer's work after studying worked examples compared to novice learners provided with problem-solving tasks.

Subfields: Developmental and Educational Psychology, Experimental and Cognitive Psychology, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/cf5eaf4a61f9fce167a47135cbc12a5ab414b9e6

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In Developmental and Educational Psychology

In Experimental and Cognitive Psychology

In Mechanical Engineering

Citations in the corpus

Differential effects of problem-solving demands on individual and collaborative learning outcomes. (2011, background): “This reasoning has led to the counterintuitive instructional guideline that for novices learning to solve problems, studying worked examples is a better strategy than solving the equivalent problems (Rourke & Sweller, 2009; Sweller, 1988; Sweller et al., 1998).”
The worked example and expertise reversal effect in less structured tasks : Learning to reason about legal cases (2013, background): “Nevertheless, the findings from this study clearly show that worked examples are also effective for learning less structured tasks as Rourke and Sweller (2009) suggested, despite the suggestion by Schmidt et al. (2007) that findings on instructional support on highly structured tasks might not…”
From Cognitive Load Theory to Collaborative Cognitive Load Theory (2018, methodology): “The use of cognitive load theory for these different types of tasks has also been well recorded, for example Van Merriënboer and Sweller (2010), Rourke and Sweller (2009), and Sweller et al. (2011a, 2011b).”
Example-Based Learning: Integrating Cognitive and Social-Cognitive Research Perspectives (2010, background): “…instructional design model (Hoogveld et al. 2005), learning argumentation skills (Schworm and Renkl 2007), learning to construct concept maps (Hilbert and Renkl 2009), learning to recognize designer styles (Rourke and Sweller 2009), or learning to reason about legal cases (Nievelstein et al. 2010).”
Worked example effects in individual and group work settings (2010, result): “Most of the studies have been conducted with well‐defined problems in areas such as mathematics and science; however, more recent research has found similar effects in more ill‐defined problem domains such as language learning (Diao & Sweller, 2007 ), music instruction (Owens & Sweller, 2008 ), fi”
Can Collaborative Learning Improve the Effectiveness of Worked Examples in Learning Mathematics? (2017, background): “…more contemporary research (for summaries, see Ayres & Sweller, 2013; Renkl, 2014a) has found the effect in nonscience domains such as visual arts (Rourke & Sweller, 2009) and English literature (Kyun, Kalyuga, & Sweller, 2013; Oksa, Kalyuga, & Chandler, 2010), as well as ongoing investigations…”
Effects of worked examples, example-problem, and problem-example pairs on novices learning (2011, background): “Several studies have shown that example-problem pairs were more effective for learning and transfer than problem solving only (Carroll, 1994; Cooper & Sweller, 1987; Kalyuga et al., 2001; Mwangi & Sweller, 1998; Rourke & Sweller, 2009; Sweller & Cooper, 1985).”
Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account (2009, background): “Until recently, however, the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics (see Rourke and Sweller 2008 ).”
Handbook of Research on Learning and Instruction (2011, background): “In the final section, we articulate the potential of conceptual change research to advance our understanding of motor skill learning in physical education.”