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ERIC Number: EJ1201222
Record Type: Journal
Publication Date: 2019
Pages: 9
Abstractor: As Provided
ISSN: ISSN-1134-3478
Designing for Deep Learning in the Context of Digital and Social Media
Gee, James-Paul; Esteban-Guitart, Moisés
Comunicar: Media Education Research Journal, v27 n58 p9-17 2019
There is today a great deal of controversy over digital and social media. Even leaders in the tech industry are beginning to decry the time young people spend on smartphones and social networks. Recently, the World Health Organization proposed adding "gaming disorder" to its official list of diseases, defining it as a pattern of gaming behavior so severe that it takes "precedence over other life interests". At the same time, many others have celebrated the positive properties of video games, social media, and social networks. This paper argues that a deeper understanding of human beings is needed to design for deep learning. For the purposes of this study "design for deep learning" means helping people matter and find meaning in ways that make them and others healthy in mind and body, while improving the state of the world for all living things, with due respect for truth, sensation, happiness, imagination, individuality, diversity, and the future. In particular, fifteen features related to human nature are suggested based on recent scientific developments to answer the question: What is a human being? Consequently, proposals that are linked to learning and transformation, as well as social improvement, should fit with the ways in which humans, as specific sorts of biological and social creatures, learn best (or can learn at all) and can change for the better.
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A