Testing the instructional fit hypothesis: the case of self-explanation prompts

Nokes, Timothy J.; Hausmann, Robert G. M.; VanLehn, Kurt; Gershman, Sophia

doi:10.1007/s11251-010-9151-4

Cited by 52 publications

(33 citation statements)

References 19 publications

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“…WEs are usually incomplete, especially with respect to the solution rationale (Chi et al, 1989). Hence, learners need to self-explain the solution to gain profound understanding (Nokes, Hausmann, VanLehn, & Gershman, 2011). In addition, part of the self-explanation effect seems to be due to the fact that learners actively generate these explanations (Hausmann & VanLehn, 2007).…”

Section: Learning Processesmentioning

confidence: 99%

Toward an Instructionally Oriented Theory of Example‐Based Learning

2013

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Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from worked examples, observational learning, and analogical reasoning. This theory has descriptive and prescriptive elements. The descriptive subtheory deals with (a) the relevance and effectiveness of examples, (b) phases of skill acquisition, and (c) learning processes. The prescriptive subtheory proposes instructional principles that make full exploitation of the potential of example-based learning possible.

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Section: Learning Processesmentioning

confidence: 99%

Toward an Instructionally Oriented Theory of Example‐Based Learning

2013

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“…High-school students were prompted to explain worked-out examples to physics problems (Nokes, Hausmann, VanLehn, & Gershman, 2011). How-explanation-prompts focused learners on generating inferences for missing information in the example steps (e.g., BCould you restate or summarize that step in your own words?^).…”

Section: Constraint On Explanation Promptsmentioning

confidence: 99%

Eliciting explanations: Constraints on when self-explanation aids learning

Rittle‐Johnson

Loehr

2016

Psychon Bull Rev

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Generating explanations for oneself in an attempt to make sense of new information (i.e., self-explanation) is often a powerful learning technique. Despite its general effectiveness, in a growing number of studies, prompting for selfexplanation improved some aspects of learning, but reduced learning of other aspects. Drawing on this recent research, as well as on research comparing self-explanation under different conditions, we propose four constraints on the effectiveness of self-explanation. First, self-explanation promotes attention to particular types of information, so it is better suited to promote particular learning outcomes in particular types of domains, such as transfer in domains guided by general principles or heuristics. Second, self-explaining a variety of types of information can improve learning, but explaining one's own solution methods or choices may reduce learning under certain conditions. Third, explanation prompts focus effort on particular aspects of the to-be-learned material, potentially drawing effort away from other important information. Explanation prompts must be carefully designed to align with target learning outcomes. Fourth, prompted self-explanation often promotes learning better than unguided studying, but alternative instructional techniques may be more effective under some conditions. Attention to these constraints should optimize the effectiveness of self-explanation as an instructional technique in future research and practice.

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“…The use of prompts, which are specific instructions that require learners to process the example or the content in a specific way, has been shown to enhance the effect of SE on learning ‘Justification prompts’ require students to generate the principal justification and to focus on the underlying concepts. Examples of this type of prompt are: What principle is being applied here?…”

Section: Introductionmentioning

confidence: 99%