Transitioning From Studying Examples to Solving Problems: Effects of Self-Explanation Prompts and Fading Worked-Out Steps.

Although research has demonstrated that successively fading or successively removing more and more worked-out solution steps as learners transition from relying on examples to independent problem solving reliably fosters performance on near-transfer tasks—relative to example–problem pairs—this effect is not reliable on far-transfer tasks. To address this, the authors combined fading with the introduction of prompts designed to encourage learners to identify the underlying principle illustrated in each worked-out solution step. Across 2 experiments, this combination produced medium to large effects on near and far transfer without requiring additional time on task. Thus, the instructional procedure is highly recommendable because it (a) is relatively straightforward to implement, (b) does not prolong learning time, and (c) fosters both near- and far-transfer performance. Worked-out examples typically consist of a problem formulation, solution steps, and the final answer itself. Research indicates that exposure to worked-out examples is critical when learners are in the initial stages of learning a new cognitive skill in wellstructured domains such as mathematics, physics, and computer programming (Anderson, Fincham, & Douglass, 1997). Moreover, studies performed by Sweller and his colleagues (e.g., Sweller &

[1]  L. S. Vygotksy Mind in society: the development of higher psychological processes , 1978 .

[2]  J. Sweller,et al.  The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra , 1985 .

[3]  Susan E. Newman,et al.  Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics. Technical Report No. 403. , 1987 .

[4]  Michelene T. H. Chi,et al.  Self-Explanations: How Students Study and Use Examples in Learning To Solve Problems. Technical Report No. 9. , 1987 .

[5]  Nigel H. Goddard,et al.  Proceedings of the 15th Annual Conference of the Cognitive Science Society , 1993 .

[6]  Margaret M. Recker,et al.  Learning Strategies and Transfer in the Domain of Programming , 1994 .

[7]  R. Catrambone Generalizing Solution Procedures Learned From Examples , 1996 .

[8]  Alexander Renkl,et al.  Learning from Worked-Out-Examples: A Study on Individual Differences , 1997, Cogn. Sci..

[9]  John R. Anderson,et al.  The role of examples and rules in the acquisition of a cognitive skill. , 1997, Journal of experimental psychology. Learning, memory, and cognition.

[10]  R. Catrambone The subgoal learning model: Creating better examples so that students can solve novel problems. , 1998 .

[11]  H. Mandl,et al.  Learning from Worked-Out Examples: The Effects of Example Variability and Elicited Self-Explanations , 1998, Contemporary educational psychology.

[12]  F. Paas,et al.  Cognitive Architecture and Instructional Design , 1998 .

[13]  Teaching metacognitive skills : implementation and evaluation of a tutoring system to guide self-explanation while learning from examples , 1999 .

[14]  Cristina Conati,et al.  Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation , 2000 .

[15]  Alexander Renkl,et al.  From Studying Examples to Solving Problem: Fading Worked-Out Solution Steps Helps Learning , 2000 .

[16]  S. Derry,et al.  Learning from Examples: Instructional Principles from the Worked Examples Research , 2000 .

[17]  Vincent Aleven,et al.  An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor , 2002, Cogn. Sci..

[18]  Richard K. Staley,et al.  From Example Study to Problem Solving: Smooth Transitions Help Learning , 2002 .

[19]  Silke Schworm,et al.  Learning by Solved Example Problems: Instructional Explanations Reduce Self-Explanation Activity , 2002 .