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Conceptual Customization for Learning with Multimedia: Developing Individual Instructional Experiences to Support Science Understanding

Conceptual Customization for Learning with Multimedia: Developing Individual Instructional Experiences to Support Science Understanding

Kirsten R. Butcher, Sebastian de la Chica, Faisal Ahmad, Qianyi Gu, Tamara Sumner, James H. Martin
Copyright: © 2009 |Pages: 28
ISBN13: 9781605661582|ISBN10: 1605661589|ISBN13 Softcover: 9781616925895|EISBN13: 9781605661599
DOI: 10.4018/978-1-60566-158-2.ch014
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MLA

Butcher, Kirsten R., et al. "Conceptual Customization for Learning with Multimedia: Developing Individual Instructional Experiences to Support Science Understanding." Cognitive Effects of Multimedia Learning, edited by Robert Z. Zheng, IGI Global, 2009, pp. 260-287. https://doi.org/10.4018/978-1-60566-158-2.ch014

APA

Butcher, K. R., de la Chica, S., Ahmad, F., Gu, Q., Sumner, T., & Martin, J. H. (2009). Conceptual Customization for Learning with Multimedia: Developing Individual Instructional Experiences to Support Science Understanding. In R. Zheng (Ed.), Cognitive Effects of Multimedia Learning (pp. 260-287). IGI Global. https://doi.org/10.4018/978-1-60566-158-2.ch014

Chicago

Butcher, Kirsten R., et al. "Conceptual Customization for Learning with Multimedia: Developing Individual Instructional Experiences to Support Science Understanding." In Cognitive Effects of Multimedia Learning, edited by Robert Z. Zheng, 260-287. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-158-2.ch014

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Abstract

This chapter discusses an emerging theme in supporting effective multimedia learning: developing scalable, cognitively-grounded tools that customize learning interactions for individual students. We discuss the theoretical foundation for expected benefits of customization and current approaches in educational technology that leverage a learner’s prior knowledge. We then describe the development of a customized tool for science learning, called CliCk, that uses automatic techniques to create knowledge models that can be fed into cognitively-informed pedagogical tools. CliCk leverages existing multimedia resources in educational digital libraries for two purposes: (a) to generate rich representations of domain content relevant for learner modeling that are easily scaled to new domains and disciplines, and (b) to serve as a repository of instructional resources that support customized pedagogical interactions. The potential of the CliCk system is discussed, along with initial comparisons of knowledge models created by CliCk and human experts. Finally, the chapter discusses the remaining challenges and relevant future extensions for effective customization tools in educational technology.

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