Elemental Learning and the Pyramid of Fidelity

Elemental Learning and the Pyramid of Fidelity

J. V. Dempsey (University of South Alabama, USA)
DOI: 10.4018/978-1-61520-717-6.ch004
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Abstract

One of the emerging issues for educators who recognize the importance of digital games and virtual worlds is fidelity to learning outcomes, both intentional and incidental. In this chapter, from the perspective of an educator, the author introduces an integrated framework that emphasizes elemental learning. The model, based on learning analysis and direct measurement of learning is iterative, as opposed to a front-end-only approach, and includes five major cognitive learning outcomes: actual elements, simulated elements, procedural understanding, conceptual understanding, and related knowledge. For each of the learning outcomes, the author provides design propositions and an example.
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Learning Outcomes And Fidelity

Learning taxonomies such as the classics of Bloom (1956) and Gagné (1985) are important because they give us a structure for learning analysis, i.e., figuring out the rational intended learning outcomes in a particular situation or for a particular learning process. There are many other versions of learning taxonomies useful in specific situations for analyzing learning outcomes. We might want to conduct learning analysis for assessment purposes or to plan or just understand learning. Because learning outcomes are essentially a way to analyze content, it really does not matter how an individual acquires content or, in the case of intentional learning, how the content is taught. Additionally, taxonomies are important to identify the nature of incidental, or unintended, learning outcomes. Likewise, taxonomies can be very useful in the assessment of learning outcomes. Without defining learning outcomes, it is a difficult task to accurately assess for either formative or summative purposes. As S. J. Gould (1981) famously said, “Taxonomy is always a contentious issue because the world does not come to us in neat little packages” (p. 158). Even so, there is a common sense aspect to using learning taxonomies. Human beings are born classifiers. It helps us think through problems. It helps us analyze content. It helps us understand what content is learned.

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