How Personalization Affects Motivation in Gamified Review Assessments.

IF 4.7 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal of Artificial Intelligence in Education Pub Date : 2023-01-10 DOI:10.1007/s40593-022-00326-x
Luiz Rodrigues, Paula T Palomino, Armando M Toda, Ana C T Klock, Marcela Pessoa, Filipe D Pereira, Elaine H T Oliveira, David F Oliveira, Alexandra I Cristea, Isabela Gasparini, Seiji Isotani
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Abstract

Personalized gamification aims to address shortcomings of the one-size-fits-all (OSFA) approach in improving students' motivations throughout the learning process. However, studies still focus on personalizing to a single user dimension, ignoring multiple individual and contextual factors that affect user motivation. Unlike prior research, we address this issue by exploring multidimensional personalization compared to OSFA based on a multi-institution sample. Thus, we conducted a controlled experiment in three institutions, comparing gamification designs (OSFA and Personalized to the learning task and users' gaming habits/preferences and demographics) in terms of 58 students' motivations to complete assessments for learning. Our results suggest no significant differences among OSFA and Personalized designs, despite suggesting user motivation depended on fewer user characteristics when using personalization. Additionally, exploratory analyses suggest personalization was positive for females and those holding a technical degree, but negative for those who prefer adventure games and those who prefer single-playing. Our contribution benefits designers, suggesting how personalization works; practitioners, demonstrating to whom the personalization strategy was more or less suitable; and researchers, providing future research directions.

Supplementary information: The online version contains supplementary material available at 10.1007/s40593-022-00326-x.

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游戏化复习评估中的个性化如何影响学习动机?
个性化游戏化旨在解决 "一刀切"(OSFA)方法的不足,在整个学习过程中提高学生的学习动机。然而,目前的研究仍然只关注单一用户维度的个性化,而忽略了影响用户学习动机的多种个体因素和情境因素。与之前的研究不同,我们在多机构样本的基础上,探讨了多维度个性化与 OSFA 的比较,从而解决了这一问题。因此,我们在三所院校进行了一项对照实验,比较了游戏化设计(OSFA 和根据学习任务、用户的游戏习惯/偏好和人口统计学特征进行的个性化)对 58 名学生完成学习评估的激励作用。我们的研究结果表明,OSFA 和个性化设计之间没有明显差异,尽管在使用个性化设计时,用户动机取决于较少的用户特征。此外,探索性分析表明,个性化设计对女性和拥有技术学位的人来说是积极的,但对喜欢冒险游戏的人和喜欢单机游戏的人来说是消极的。我们的贡献对设计者、实践者和研究者都有益处,设计者提出了个性化是如何发挥作用的;实践者说明了个性化策略对哪些人更适合或不太适合;研究者提供了未来的研究方向:在线版本包含补充材料,可查阅 10.1007/s40593-022-00326-x。
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来源期刊
International Journal of Artificial Intelligence in Education
International Journal of Artificial Intelligence in Education COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
11.10
自引率
6.10%
发文量
32
期刊介绍: IJAIED publishes papers concerned with the application of AI to education. It aims to help the development of principles for the design of computer-based learning systems. Its premise is that such principles involve the modelling and representation of relevant aspects of knowledge, before implementation or during execution, and hence require the application of AI techniques and concepts. IJAIED has a very broad notion of the scope of AI and of a ''computer-based learning system'', as indicated by the following list of topics considered to be within the scope of IJAIED: adaptive and intelligent multimedia and hypermedia systemsagent-based learning environmentsAIED and teacher educationarchitectures for AIED systemsassessment and testing of learning outcomesauthoring systems and shells for AIED systemsbayesian and statistical methodscase-based systemscognitive developmentcognitive models of problem-solvingcognitive tools for learningcomputer-assisted language learningcomputer-supported collaborative learningdialogue (argumentation, explanation, negotiation, etc.) discovery environments and microworldsdistributed learning environmentseducational roboticsembedded training systemsempirical studies to inform the design of learning environmentsenvironments to support the learning of programmingevaluation of AIED systemsformal models of components of AIED systemshelp and advice systemshuman factors and interface designinstructional design principlesinstructional planningintelligent agents on the internetintelligent courseware for computer-based trainingintelligent tutoring systemsknowledge and skill acquisitionknowledge representation for instructionmodelling metacognitive skillsmodelling pedagogical interactionsmotivationnatural language interfaces for instructional systemsnetworked learning and teaching systemsneural models applied to AIED systemsperformance support systemspractical, real-world applications of AIED systemsqualitative reasoning in simulationssituated learning and cognitive apprenticeshipsocial and cultural aspects of learningstudent modelling and cognitive diagnosissupport for knowledge building communitiessupport for networked communicationtheories of learning and conceptual changetools for administration and curriculum integrationtools for the guided exploration of information resources
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