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Massively Scalable Learning: Principles of Serious Game Scalability

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Bibliographic Details
Title: Massively Scalable Learning: Principles of Serious Game Scalability
Authors: Tornqvist, Dominicus, Wen, Lian, Tichon, Jennifer, Bai, Guangdong
Source: Journal of Interactive Learning Research. 32:99-124
Publisher Information: Association for the Advancement of Computing in Education, 2021.
Publication Year: 2021
Subject Terms: augmented reality and games, Other Education, Graphics
Description: There is a healthy research community focused on individual differences to tailor serious games for maximum effect for each person. But there is a comparative lack of research on the scalability of serious games for maximising knowledge saturation in a population. Scalability is critical in many real applications. The authors detail this neglected set of priorities as a research paradigm: Massively Scalable Learning (MSL), and delineate what kinds of domains would benefit most from MSL, summarise its specific cognitive, motivational, and practical components, and detail the factors and mechanisms that determine if MSL is relevant and effective. Existing research is examined, evaluating common educational tools and game features such as virtual tutors for their applicability to MSL, to extract some initial guidelines and principles for MSL for practitioners of serious game design, and identify the key knowledge gaps where future research needs to focus in this neglected but important area.
Document Type: Article
ISSN: 1093-023X
DOI: 10.70725/842904tplcck
Accession Number: edsair.doi.dedup.....de81e91a5d68b29d0947d0a45162db24
Database: OpenAIRE
Description
Abstract:There is a healthy research community focused on individual differences to tailor serious games for maximum effect for each person. But there is a comparative lack of research on the scalability of serious games for maximising knowledge saturation in a population. Scalability is critical in many real applications. The authors detail this neglected set of priorities as a research paradigm: Massively Scalable Learning (MSL), and delineate what kinds of domains would benefit most from MSL, summarise its specific cognitive, motivational, and practical components, and detail the factors and mechanisms that determine if MSL is relevant and effective. Existing research is examined, evaluating common educational tools and game features such as virtual tutors for their applicability to MSL, to extract some initial guidelines and principles for MSL for practitioners of serious game design, and identify the key knowledge gaps where future research needs to focus in this neglected but important area.
ISSN:1093023X
DOI:10.70725/842904tplcck