A Hybrid SEM-Artificial Neural Network Study on Students’ Usage and Perceptions of ChatGPT: Exploring Academic Work Engagement (85551)

Session Information:

Session: On Demand
Room: Virtual Video Presentation
Presentation Type: Virtual Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

The emergence of artificial intelligence (AI), particularly ChatGPT, became widely used to aid students in educational tasks. The current study investigated the student's usage and perceptions of ChatGPT in academic work engagement using a revised Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) to analyze the complex interplay of various latent variables, thus contributing to a deeper understanding of AI adoption in educational settings. An online questionnaire comprising 55 items was distributed, and 315 sample data were collected. Eleven latent variables were examined: technology readiness, user engagement, perceived ease of use, perceived usefulness, social influence, academic work engagement, attitude towards using ChatGPT, self-efficacy, response quality, intention to use, and actual use of ChatGPT. Structural Equation Modeling (SEM) results revealed that technology readiness was positively correlated with user engagement. Furthermore, user engagement had a significant direct relationship with social influence, directly affecting academic work engagement. Subsequently, intention to use was significantly influenced by attitude towards using, response quality, and considerably related to the actual use of ChatGPT. Furthermore, the integration of Artificial Neural Networks (ANN) indicated the intention to use it as the most influential factor. Moreover, it gives a more accurate model with an average RMSE of 0.0524 and 0.0552 for training and testing data sets. The findings of this study provide helpful insights into determining the factors that influenced the adoption of ChatGPT in academic environments and further enhance the platform's overall performance. Lastly, the study's model construct will benefit researchers and other sectors aiming to investigate

Authors:
Klint Allen Mariñas, Mapua University, Philippines
Charmine Sheena Saflor, De La Salle University, Philippines
Jasfer Von Chico, Occidental Mindoro State College, Philippines
Hannah Maureen Manzano, Occidental Mindoro State College, Philippines
Monica Shane Tanglao, Occidental Mindoro State College, Philippines


About the Presenter(s)
Klint Allen A. Mariñas, CIE, Ph.D. is currently an assistant professor and department chair of industrial engineering at the School of Industrial Engineering and Engineering Management, Mapua University in the Philippines.

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00