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Personalization With Digital Technology: A Deep Cognitive Processing Perspective

Personalization With Digital Technology: A Deep Cognitive Processing Perspective

Robert Z. Zheng
Copyright: © 2018 |Pages: 27
ISBN13: 9781522539407|ISBN10: 1522539409|EISBN13: 9781522539414
DOI: 10.4018/978-1-5225-3940-7.ch001
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MLA

Zheng, Robert Z. "Personalization With Digital Technology: A Deep Cognitive Processing Perspective." Digital Technologies and Instructional Design for Personalized Learning, edited by Robert Zheng, IGI Global, 2018, pp. 1-27. https://doi.org/10.4018/978-1-5225-3940-7.ch001

APA

Zheng, R. Z. (2018). Personalization With Digital Technology: A Deep Cognitive Processing Perspective. In R. Zheng (Ed.), Digital Technologies and Instructional Design for Personalized Learning (pp. 1-27). IGI Global. https://doi.org/10.4018/978-1-5225-3940-7.ch001

Chicago

Zheng, Robert Z. "Personalization With Digital Technology: A Deep Cognitive Processing Perspective." In Digital Technologies and Instructional Design for Personalized Learning, edited by Robert Zheng, 1-27. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-3940-7.ch001

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Abstract

How to personalize learners' learning with digital technology so that learners derive optimal experiences in learning is a key question facing learning scientists, cognitive psychologists, teachers, and professional instructional designers. One of the challenges surrounding personalization and digital technology is how to promote learners' cognitive processes at a deeper level so that they become optimally engaged in critical and creative thinking, making inferences in learning, transferring knowledge to new learning situations, and constructing new knowledge during innovative learning process. This chapter examines the literature relating to deep cognitive processes and the idiosyncratic features of digital technology that support learners' deep cognitive processes in learning. Guidelines pertaining to personalization with digital technology in regard to deep cognitive processing are proposed, followed by the discussions on future research with a focus on verifying the theoretical constructs proposed in the guidelines.

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