Analysis and Development Direction of Education Content on AI speakers Based on Gagné’s Instructional Theory: Focused on Amazon Alexa Skills

Jun Seo Park; Yujin Kim; Kim, Min Young; Lim， Keol

doi:10.34163/jkits.2019.14.4.004

The artificial intelligence (AI) speaker, as an intelligent personal assistant, interacts with users and delivers content under voice user interfaces. Amazon is leading the market by running open the AI Speaker “skills” ecosystem. Accordingly, educational content skills on AI speakers are increasing and the future of learning could use some features of AI speakers. This research was conducted to analyze major educational content in terms of Gagné’s instructional theory of nine events including “gaining attention (reception),” “informing learners of the objective (expectancy),” “stimulating recall of prior learning (retrieval),” “presenting the stimulus (selective perception),” “providing learning guidance (semantic encoding),” “eliciting performance (responding),” “providing feedback (reinforcement),” “assessing performance (retrieval),” and “enhancing retention and transfer (generalization)” and to suggest future directions. A total of 30 representative educational skills from Amazon “Echo” were investigated to check the effective applications of nine instructional events. As a result, “gaining attention,” “informing learners of objectives,” and “eliciting performance” were applied to many of the skills. However, “stimulating recall of prior learning” and “enhance retention and transfer” were not. Based on the findings, design based on structural understandings and technical properties of the AI speaker, design applied to constructivist learning paradigm, and design for effective instructional strategies were suggested.

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* 2022년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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