Generative AI: elevating knowledge acquisition and retention and recall through autonomy, interactivity and engagement

互动性 召回 自治 生成语法 知识管理 计算机科学 心理学 人机交互 人工智能 多媒体 认知心理学 政治学 法学
作者
Mai Nguyen,Reeti Agarwal,Ashish Malik,Rudresh Pandey
出处
期刊:Journal of Enterprise Information Management [Emerald Publishing Limited]
卷期号:38 (6): 1692-1719 被引量:21
标识
DOI:10.1108/jeim-08-2024-0433
摘要

Purpose Generative AI (GenAI) in education promises remarkable development changes that can enhance learner experience through the personalised and responsive learning process. In this paper, we investigate how the different features of GenAI – autonomy, interactivity and usability – contribute to student engagement and learning outcomes. Design/methodology/approach From the lens of the self-determination theory, the study seeks to articulate how these GenAI features influence student engagement and their ability to achieve specific goals through interactive learning experiences delivered by GenAI. Qualtrics, a well-known online data collection tool, was employed in the study to collect data from 488 respondents in the UK region who had been exposed to generative AI-based platforms. The sampling approach used was representative, wherein the platform was asked to randomly share the survey with respondents in the UK region who had some experience interacting with Gen AI platforms. Findings The paper’s findings show that increased autonomy and interactivity encourage students to engage more in GenAI platforms. Usability functions as a critical mediator with respect to how autonomy and interactivity are incorporated into engagement and skill acquisition. Skill development emerged as a key mediator of the direct effect between GenAI features and student engagement, confirming that it is an important determinant in engaging with educational content. Further, results reveal a significant positive moderation effect of personalisation between autonomy and engagement. Originality/value The results extend the self-determination theory and offer theoretical suggestions for improving learning through AI-driven educational tools. For educators, the study provides practical insights to motivate the effective integration of GenAI platforms that can provide autonomy, interactivity, usability and personalisation to increase student engagement.
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