Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis With Gender Dimension

IF 4.3 Q1 PSYCHOLOGY, MULTIDISCIPLINARY Human Behavior and Emerging Technologies Pub Date : 2024-06-10 DOI:10.1155/2024/3085910
Raghu Raman, Santanu Mandal, Payel Das, Tavleen Kaur, J. P. Sanjanasri, Prema Nedungadi
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Abstract

This study explores the adoption and societal implications of an emerging technology such as Chat Generative Pre-Trained Transformer (ChatGPT) in higher education students. By utilizing a mixed-method framework, this research combines Rogers’ diffusion of innovation theory with sentiment analysis, offering an innovative methodological approach for examining technology adoption in higher educational settings. It explores five attributes—relative advantage, compatibility, ease of use, observability, and trialability—shaping students’ behavioral intentions toward ChatGPT. Sentiment analysis offers qualitative depth, revealing emotional and perceptual aspects, and introduces a gender-based perspective. The results suggest that five innovation attributes significantly impact the adoption rates and perceptions of ChatGPT, indicating its potential for transformative social change within the educational sector. Gen Zs viewed ChatGPT as innovative, compatible, and user-friendly, enabling the independent pursuit of educational goals. Consequently, the benefits provided by ChatGPT in education motivate students to use the tool. Gender differences were observed in the prioritization of innovation attributes, with male students favoring compatibility, ease of use, and observability, while female students emphasized ease of use, compatibility, relative advantage, and trialability. The findings have implications for understanding how technological innovations such as ChatGPT could be strategically diffused across different societal segments, especially in the academic context where ethical considerations such as academic integrity are paramount. This study underscores the need for a demographic-sensitive, user-centric design in generative artificial intelligence (AI) technologies.

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利用创新扩散理论和带有性别维度的情感分析探索大学生对聊天软件的采用情况
本研究探讨了高等院校学生采用聊天生成预训练转换器(ChatGPT)这一新兴技术的情况及其社会影响。通过采用混合方法框架,本研究将罗杰斯的创新扩散理论与情感分析相结合,为研究高等教育环境中的技术采用情况提供了一种创新的方法论。研究探讨了影响学生对 ChatGPT 的行为意向的五个属性--相对优势、兼容性、易用性、可观察性和可试用性。情感分析提供了定性深度,揭示了情感和感知方面的问题,并引入了基于性别的视角。研究结果表明,五种创新属性对 ChatGPT 的采用率和认知度产生了重大影响,这表明 ChatGPT 在教育领域具有变革社会的潜力。Z 世代认为 ChatGPT 具有创新性、兼容性和用户友好性,使他们能够独立追求教育目标。因此,ChatGPT 为教育带来的益处促使学生使用该工具。在创新属性的优先排序上,观察到了性别差异,男生偏爱兼容性、易用性和可观察性,而女生则强调易用性、兼容性、相对优势和可试用性。研究结果对于理解如何在不同的社会群体中战略性地推广 ChatGPT 等技术创新具有重要意义,尤其是在学术背景下,因为学术诚信等道德因素是最重要的。本研究强调了在设计人工智能(AI)生成技术时,需要对人口统计学敏感、以用户为中心。
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来源期刊
Human Behavior and Emerging Technologies
Human Behavior and Emerging Technologies Social Sciences-Social Sciences (all)
CiteScore
17.20
自引率
8.70%
发文量
73
期刊介绍: Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.
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