Background: The rapid adoption of ChatGPT in academic settings has raised concerns about its impact on learning, research, and academic integrity. This study aimed to develop and validate a comprehensive ChatGPT Usage Scale specifically tailored to postgraduate students, addressing the need for a psychometrically sound instrument to assess the multidimensional nature of ChatGPT usage in higher education.
Methods: A cross-sectional survey design was employed, involving 443 postgraduate students from two Egyptian universities. The initial 39-item scale underwent Exploratory Factor Analysis (EFA) using principal component analysis with Varimax rotation. Confirmatory Factor Analysis (CFA) was conducted to assess the model fit and psychometric properties of the final 15-item measure. Internal consistency reliability was evaluated using Cronbach's alpha and McDonald's omega.
Results: EFA revealed a three-factor structure explaining 49.186% of the total variance: Academic Writing Aid (20.438%), Academic Task Support (14.410%), and Reliance and Trust (14.338%). CFA confirmed the three-factor structure with acceptable fit indices (χ2(87) = 223.604, p < .001; CMIN/DF = 2.570; CFI = 0.917; TLI = 0.900; RMSEA = 0.060). All standardized factor loadings were statistically significant (p < .001), ranging from 0.434 to 0.728. The scale demonstrated good internal consistency (Cronbach's α = 0.848, McDonald's ω = 0.849) and composite reliability (CR = 0.855). The average variance extracted (AVE) was 0.664, supporting convergent validity.
Conclusions: The validated ChatGPT Usage Scale provides a reliable and valid instrument for assessing postgraduate students' engagement with ChatGPT across multiple dimensions. This tool offers valuable insights into AI-assisted academic practices, enabling more nuanced investigations into the effects of ChatGPT on postgraduate education.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423513 | PMC |
http://dx.doi.org/10.1186/s40359-024-01983-4 | DOI Listing |
Sci Rep
January 2025
Key Laboratory of Ministry of Industrial Design and Ergonomics, Northwestern Polytechnical University, Xi'an, 710072, China.
Online reviews significantly influence consumer purchasing decisions and serve as a vital reference for product improvement. With the surge of generative artificial intelligence (AI) technologies such as ChatGPT, some merchants might exploit them to fabricate deceptive positive reviews, and competitors may also fabricate negative reviews to influence the opinions of consumers and designers. Attention must be paid to the trustworthiness of online reviews.
View Article and Find Full Text PDFNurse Educ Today
January 2025
Department of Industrial Engineering and Management, Chaoyang University of Technology, No. 168, Jifeng E. Rd., Wufeng District, Taichung 413310, Taiwan. Electronic address:
Background: Nursing education increasingly emphasizes academic writing and communication, critical for delivering quality patient care and professional advancement. Rapidly emerging artificial intelligence (AI) tools such as ChatGPT and Copilot are transforming educational methodologies, and a focus is being placed on embedding AI literacy to effectively bridge the gap between theoretical knowledge and clinical practice. These technologies have the potential to reshape nursing education in a technology-driven health-care landscape.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer and Information Science, Konstanz University, Konstanz, Baden-Württemberg, Germany.
A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N = 1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022).
View Article and Find Full Text PDFAdv Physiol Educ
January 2025
Department of Kinesiology and Outdoor Recreation, Southern Utah University, Cedar City, UT, USA.
Learning Objectives (LOs) are a pillar of course design and execution, and thus a focus of curricular reforms. This study explored the extent to which the creation and usage of LOs might be facilitated by three leading chatbots: ChatGPT-4o, Claude 3.5 Sonnet, and Google Gemini Advanced.
View Article and Find Full Text PDFAdv Physiol Educ
March 2025
Department of PhysiologyAll India Institute of Medical Sciences, Deoghar, Jharkhand, India.
The integration of large language models (LLMs) in medical education offers both opportunities and challenges. While these artificial intelligence (AI)-driven tools can enhance access to information and support critical thinking, they also pose risks like potential overreliance and ethical concerns. To ensure ethical use, students and instructors must recognize the limitations of LLMs, maintain academic integrity, and handle data cautiously, and instructors should prioritize content quality over AI detection methods.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!