Raghu Raman, Santanu Mandal, Payel Das, Tavleen Kaur, J. P. Sanjanasri, Prema Nedungadi
{"title":"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","authors":"Raghu Raman, Santanu Mandal, Payel Das, Tavleen Kaur, J. P. Sanjanasri, Prema Nedungadi","doi":"10.1155/2024/3085910","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2024 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/3085910","citationCount":"0","resultStr":"{\"title\":\"Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis With Gender Dimension\",\"authors\":\"Raghu Raman, Santanu Mandal, Payel Das, Tavleen Kaur, J. P. Sanjanasri, Prema Nedungadi\",\"doi\":\"10.1155/2024/3085910\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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. 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Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis With Gender Dimension
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.
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.