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Publication date: 16 July 2024

Tapas Sudan, Arjun Hans and Rashi Taggar

The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2…

Abstract

Purpose

The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). By assessing these factors, this study aims to unravel their impact on the behavioral intention to use ChatGPT.

Design/methodology/approach

While evaluating ChatGPT's adoption dynamics, this study analyses the UTAUT2 core factors and perceived benefits. Real-time data from 638 business and management students in India were collected through purposive sampling and a cross-sectional survey. An in-depth examination using IBM SPSS and AMOS revealed the patterns that regulate ChatGPT reception in educational settings.

Findings

Habit emerges as a powerful predictor, which aligns with the Habit Loop Theory's cues, routine and rewards. Perceived benefits significantly influence adoption, and traditional factors like performance expectancy and social influence exert no influence. The insignificance of effort expectancy challenges conventional understanding, unveiling novel aspects of student tech adoption.

Social implications

There is a need for guidelines to ensure fair and responsible use of ChatGPT among students. While ChatGPT presents advantages like task automation and personalized learning, integrating it into the existing education system requires careful planning to harness its benefits effectively.

Originality/value

With the recent introduction of Generative-AI tools, understanding student acceptance and application is essential. This research sheds light on this emerging technology, emphasizing the importance of analyzing technology acceptance for its successful adoption.

Details

Interactive Technology and Smart Education, vol. 21 no. 4
Type: Research Article
ISSN: 1741-5659

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