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

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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Institutions

Publication Details

Journal
Journal of Enterprise Information Management
Published
2025-06-06
DOI
https://doi.org/10.1108/jeim-08-2024-0433
Citations
5
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
12.40
Controls
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article

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

Mai Nguyen, Rudresh Pandey, Reeti Agarwal, Ashish Malik
5 citations
Journal of Enterprise Information Management
AI in Service Interactions
12.40
article

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

Mai Nguyen, Rudresh Pandey, Reeti Agarwal, Ashish Malik
article en
5 citations

Abstract

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.

Journal of Enterprise Information ManagementVol. 38(6)
Griffith University (AU), Institute of Management Technology (IN), University of Canberra (AU), Jaipuria Institute of Management (IN), IMS Unison University (IN), UNSW Sydney (AU), Hanoi University of Industry (VN)
Openalex Percentile: Top 2%
AI in Service Interactions
12.40
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