More than Just Data: The Importance of Motivation, Examples, and Feedback in Comprehending and Retaining Digital Information

More than Just Data: The Importance of Motivation, Examples, and Feedback in Comprehending and Retaining Digital Information

Brent A. Anders
DOI: 10.4018/978-1-4666-4462-5.ch002
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Abstract

Increasing amounts of information are being generated and distributed to students and the public in general without regards for how this data will be processed, integrated, and recalled. This chapter seeks to present how, through the use of motivation, salient and multimodal examples, and properly created/regulated feedback, information presented can be much better learned and experienced so as to aid in overall comprehension and learning. The Attention, Relevance, Confidence, and Satisfaction (ARCS) model is highlighted when discussing how to motivate student and content viewers (Keller, 1987). Additional research findings with regards to the use of multimodalities, the use of examples, and proper implementation of feedback is also presented. Examples are provided as to how an educational facilitator might use this information in presentations and digital content distribution.
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The Importance Of Motivation

Motivation is a key component in virtually any human behavior, especially with regards to edification in that one can’t learn/comprehend if one doesn’t at first desire it or have a willingness to focus and pay attention to the information in the first place. In reviewing the literature dealing with learning/comprehension as applied to motivation, a plethora of theories and explanations are made available. One model that conglomerates multiple theories is that of the ARCS model which stands for Attention, Relevance, Confidence, and Satisfaction (Keller, 1987). Originally developed in 1979 and fully presented in 1987, Keller’s ARCS model conglomerates and organizes Keller’s macro theory of motivation and instructional design as well as expectancy-value theory and motivational ideas from education, psychology, and industry (see Figure 1).

Figure 1.

Graphical example/representation of the ARCS model

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