Article2024

AI learning intention, learning engagement and behavioral outcomes: an empirical study

21 citations0/0 files storedJournal of Management Development

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Technology Adoption and User Behaviour Human Resource Development and Performance Evaluation Online Learning and Analytics

Abstract

Purpose Research on training and/or L&D effectiveness is predominantly conducted in a traditional L&D context. Little research is conducted on training and/or L&D in the context of artificial intelligence (AI)-based learning. The present study aims to investigate the relationship between the adoption of AI-based learning systems and learners’ behavior. Drawing from the theory of planned behavior, the research examines the impact of attitude (ATT), subjective norm (SN) and perceived behavioral control (PBC) as AI-based learning intention (ALI) factors relate to changes in learners' behavior. Additionally, inspired by the self-determination theory by Deci and Ryan, the study further examines the mediating role of learner engagement between ALI and behavioral change. Design/methodology/approach Following a theoretical framework and using a systematic literature review method, the survey research has been planned by considering a sample from Indian industries. The collected data have been analyzed using SPSS-AMOS 27. While path analysis has been conducted to analyze the direct impact of ALI on learners' behavior, Hay’s PROCESS macro has been used to check the mediating impact of learner engagement between ALI and learners' behavior. Findings The results proved a significant and positive impact of all ALI factors such as ATT, SN and PBC on learners’ behavioral change. Further, the research found that learning engagement (LE) successfully mediates between AI learning intention and behavioral change. Originality/value In the absence of any empirical study in identifying the relationship among learning intention, LE and behavioral outcome, the result of this study may provide useful insights to researchers and practitioners.

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References

1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 2014Partial least squares structural equation modeling (PLS-SEM)1995Understanding Information Technology Usage: A Test of Competing Models 2006The Measurement of Work Engagement With a Short Questionnaire 1995Computer Self-Efficacy: Development of a Measure and Initial Test 2011The theory of planned behaviour: Reactions and reflections 2017An updated and expanded assessment of PLS-SEM in information systems research 2009Why Teachers Adopt a Controlling Motivating Style Toward Students and How They Can Become More Autonomy Supportive

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