To Advance AI Use in Education, Focus on Understanding Educators.

IF 4.7 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

International Journal of Artificial Intelligence in Education Pub Date : 2023-06-09 DOI:10.1007/s40593-023-00351-4

René F Kizilcec

引用次数: 1

Abstract

A better understanding of educators' perspectives of emerging education technology, specifically tools that incorporate AI, is essential to unlock the full potential benefits of these innovations. While prior research has primarily emphasized technological advancements, it has overlooked the profound influence of social, psychological, and cultural factors in shaping educators' perceptions, trust, and adoption of educational technology. As increasingly powerful AI tools emerge, their design must be rooted in a deep understanding of educators' needs and perspectives. It is only with the acceptance and trust of educators that these innovative solutions can elevate learning outcomes, academic achievements, and educational equity.

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为了推进人工智能在教育中的应用，关注理解教育者。

更好地理解教育工作者对新兴教育技术的看法，特别是包含人工智能的工具，对于释放这些创新的全部潜在好处至关重要。虽然先前的研究主要强调技术进步，但忽略了社会、心理和文化因素对教育工作者对教育技术的认知、信任和采用的深刻影响。随着越来越强大的人工智能工具的出现，它们的设计必须植根于对教育工作者需求和观点的深刻理解。只有在教育工作者的接受和信任下，这些创新解决方案才能提升学习成果、学术成就和教育公平。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Artificial Intelligence in Education COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

11.10

自引率

6.10%

发文量

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