Effects Of Worked Examples Research Articles

Effects of worked examples, example-problem, and problem-example pairs on novices’ learning

Research has demonstrated that instruction that relies more heavily on example study is more effective for novices’ learning than instruction consisting of problem solving. However, ‘a heavier reliance on example study’ has been implemented in different ways. For example, worked examples only (WE), example-problem pairs (WE-PS), or problem-example pairs (PS-WE) have been used. This study investigated the effectiveness of all three strategies compared to problem solving only (PS), using electrical circuits troubleshooting tasks; participants were secondary education students who were novices concerning those tasks. Based on prior research, it was hypothesized and confirmed that WE and WE-PS would lead to lower cognitive load during learning and higher learning outcomes than PS. In addition, the open questions of whether there would be any differences between WE and WE-PS, and whether there would be any differences between PS-WE and PS were explored. Results showed no differences between WE and WE-PS or between PS-WE and PS. This study can inform instructional designers on which example-based learning strategies to implement: it does not seem necessary to alternate example study and problem solving, but when doing so, example-problem pairs should be used rather than problem-example pairs.

How Effective are Instructional Explanations in Example-Based Learning? A Meta-Analytic Review

The worked example effect within cognitive load theory is a very well-established finding. The concrete effectiveness of worked examples in a learning situation, however, heavily depends on further moderating factors. For example, if learners improve their processing of worked examples by actively explaining the worked examples to themselves, they are usually better able to solve transfer problems. Another way to enhance example processing is to present learners with instructional explanations instead of prompting them to produce these explanations on their own. In this article, we review 21 experimental studies to address the issue whether instructional explanations support example-based learning. Meta-analytic results lead to three important conclusions: First, the benefits of instructional explanations for example-based learning per se are minimal. Second, instructional explanations are more helpful for acquiring conceptual knowledge than for acquiring procedural knowledge. Third, instructional explanations are not necessarily more effective than other methods supporting example processing such as self-explaining.

The effects of worked examples in computer-based instruction: focus on the presentation format of worked examples and prior knowledge of learners

The aim of this study is to investigate the effects of presentation formats of worked examples and the interaction effects between the presentation formats of worked examples and the prior knowledge of learners. An investigation with 97 middle school students working in four conditions (CPWE, CWE, PWE, and the control group) was conducted. The results indicate that CPWE was the most effective condition in retention and transfer. In addition, a partial expertise reversal effect was revealed in the element transfer test. High prior knowledge learners in both CPWE and PWE were superior to those who were in CWE and the control group, while low prior knowledge learners in CPWE were superior to those who were in other conditions.

Learning how to use a computer-based concept-mapping tool: Self-explaining examples helps

In initial skill acquisition in well-structured domains, example-based learning typically leads to better learning outcomes than learning by doing. Cognitive Load Theory explains this result by the worked-example effect: Example-based learning prevents learners from using load-intensive strategies and focuses their attention on the principles to-be-learned. In two experiments, we investigated the use of examples for acquiring a new learning strategy, namely computer-based concept mapping. Experiment 1 compared learners who studied two examples on how to construct a concept map with learners who practiced concept mapping by constructing two concept maps on their own. We did not find significant differences in learning outcomes. Therefore, in Experiment 2, we introduced a third group of learners who studied examples with the additional support of self-explanation prompts. Self-explaining examples led to better learning outcomes than learning with examples without prompts or practicing. With respect to cognitive load, we found that examples without prompts released learners’ working memory compared to practicing, whereas self-explaining examples led to a higher cognitive load compared to examples without self-explanation.

The worked-example effect: Not an artefact of lousy control conditions

Recently it has been argued that the worked-example effect, as postulated by Cognitive Load Theory, might only occur when compared to unsupported problem-solving, but not when compared to well-supported or tutored problem-solving as instantiated, for example, in Cognitive Tutors. In two experiments, we compared a standard Cognitive Tutor with a version that was enriched with faded worked examples. In Experiment 1, students in the example condition needed less learning time to acquire a comparable amount of procedural skills and conceptual understanding. In Experiment 2, the efficiency advantage was replicated. In addition, students in the example condition acquired a deeper conceptual understanding. The present findings demonstrate that the worked-example effect is indeed robust and can be found even when compared to well-supported learning by problem-solving.

Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account

One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies can be taught (e.g., troubleshooting, mathematical proving). Is learning by such examples also effective, and do the same instructional design principles apply? We discuss the main findings of an own research program and of related studies that addressed such questions. We found that CLT’s basic design principles also hold true for heuristic domains: Reduce extraneous load by employing examples, maximize germane load by fostering self-explanations, prevent cognitive overload by pretraining in the case of difficult learning materials, and by focusing attention on the most relevant aspects. Other typical CLT assumptions (e.g., better provide information for novice learners) were not confirmed in its generality. The present findings extend the applicability of CLT but also identify some potentially too simplistic assumptions.

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

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.

Cognitive load theory and aging: effects of worked examples on training efficiency

Cognitive load theory (CLT) is aimed at developing training material that efficiently makes use of the available cognitive processing capacity and stimulates the learner's ability to use acquired knowledge and skills in new situations. It is claimed that CLT-based training formats meet the cognitive abilities of elderly learners particularly well. That is, cognitive aging brings about several declines of working memory, which impede the acquisition of complex cognitive skills. By making an optimal use of the ‘remaining’ cognitive resources, learning can be enhanced. For that purpose, CLT provides a promising range of training formats that have proven their effectiveness relative to conventional formats in young adults. This article presents an experimental study ( N=54) aimed at the efficiency of worked examples as a substitute for conventional practice problems in training both elderly and young adults. According to CLT, studying worked examples is a more efficient means of training complex skills than solving conventional problems. As predicted, the results show that — with respect to the elderly — the efficiency of studying worked examples is higher than the efficiency of solving conventional problems in that less training time and cognitive load leads to a comparable level of performance.