The Intelligent Technical Influence in Chat Generative Pre-Trained among Students for Modern Learning Traits

Authors

  • Kathiravan Ravichandran, B. Anita Virgin, Lucky Gupta, Aby John, Santiago Otero-Potosi, Álvaro Vargas-Chavarrea, Anurag Shrivastava

Keywords:

Pre-Trained, motivation, modifications, Chat GPT

Abstract

This paper explores the influence of Chat Generative Pre-Trained, which is an Artificial Intelligence tool which provides text-based responses to user queries, on students' learning motivation. The study involved 500 participants who were students in Medan, Indonesia. The research employed a quantitative approach, using surveys and questionnaires to gather data from the respondents. Previous research instruments were adapted with some modifications, which resulting in 10 items for the dependent and independent variables for each. Hypotheses were tested using linear regression, and classical assumption tests, such as multicollinearity, heteroscedasticity, and normality, were conducted. Descriptive statistics, like mean scores, were utilized to assess the extent of Chat GPT usage among students. The results showed that male students displayed a greater propensity for utilizing Chat GPT when compared to their female counterparts. Interestingly, younger students exhibited a higher degree of engagement with Chat GPT in contrast to their older peers. Additionally, the study uncovered a notable, positive, and statistically significant influence of Chat GPT usage on students' motivation to learn.

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References

Abdullayeva, M., & Musayeva, Z. M. (2023). The Impact of Chat GPT on Student’s Writing Skills: An Exploration of Ai-Assisted Writing Tools. International Conference of Education, Research and Innovation, 1(4), 61–66.

Ali, J. K. M., Shamsan, M. A. A., Hezam, T. A., & Mohammed, A. A. Q. (2023). Impact of ChatGPT on learning motivation: teachers and students’ voices. Journal of English Studies in Arabia Felix, 2(1), 41– 49.

Anders, B. A. (2023). Is using ChatGPT cheating, plagiarism, both, neither, or forward thinking? Patterns, 4(3).

Ausat, A. M. A., Massang, B., Efendi, M., Nofirman, N., & Riady, Y. (2023). Can chat GPT replace the role of the teacher in the classroom: A fundamental analysis. Journal on Education, 5(4), 16100–16106.

Black, W., & Babin, B. J. (2019). Multivariate data analysis: Its approach, evolution, and impact. In The great facilitator: Reflections on the contributions of Joseph F. Hair, Jr. to marketing and business research (pp. 121–130). Springer.

Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments, 1–17.

Crawford, J., Cowling, M., & Allen, K.-A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching & Learning Practice, (2023).

Nasim, S. F., Ali, M. R., & Kulsoom, U. (2022). Artificial intelligence incidents & ethics a narrative review. International Journal of Technology, Innovation and Management (IJTIM), 2(2), 52–64.

Sandu, N., & Gide, E. (2019). Adoption of AI-Chatbots to enhance student learning experience in higher education in India. 2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET), 1–5.

Shoufan, A. (2023). Exploring Students’ Perceptions of CHATGPT: Thematic Analysis and Follow-Up Survey. IEEE Access.

Bani Ahmad, A. Y. A. ., Kumari, D. K. ., Shukla, A. ., Deepak, A. ., Chandnani, M. ., Pundir, S. ., & Shrivastava, A. . (2023). Framework for Cloud Based Document Management System with Institutional Schema of Database. International Journal of Intelligent Systems and Applications in Engineering, 12(3s), 672–678.

P. William, Anurag Shrivastava, Upendra Singh Aswal, Indradeep Kumar, Framework for Implementation of Android Automation Tool in Agro Business Sector, 2023 4th International Conference on Intelligent Engineering and Management (ICIEM), 10.1109/ICIEM59379.2023.10167328

P. William, Anurag Shrivastava, Venkata Narasimha Rao Inukollu, Viswanathan Ramasamy, Parul Madan, Implementation of Machine Learning Classification Techniques for Intrusion Detection System, 2023 4th International Conference on Intelligent Engineering and Management (ICIEM), 10.1109/ICIEM59379.2023.10167390

N Sharma, M Soni, S Kumar, R Kumar, N Deb, A Shrivastava, Supervised Machine Learning Method for Ontology-based Financial Decisions in the Stock Market, ACM Transactions on Asian and Low-Resource Language Information Processing.

Ajay Reddy Yeruva, Esraa Saleh Alomari, S Rashmi, Anurag Shrivastava, Routing in Ad Hoc Networks for Classifying and Predicting Vulnerabilities, Cybernetics and Systems, Taylor & Francis, 2023

P William, OJ Oyebode, G Ramu, M Gupta, D Bordoloi, A Shrivastava, Artificial intelligence based models to support water quality prediction using machine learning approach, 2023 International Conference on Circuit Power and Computing Technologie

J Jose, A Shrivastava, PK Soni, N Hemalatha, S Alshahrani, CA Saleel, An analysis of the effects of nanofluid-based serpentine tube cooling enhancement in solar photovoltaic cells for green cities, Journal of Nanomaterials 2023

K Murali Krishna, Amit Jain, Hardeep Singh Kang, Mithra Venkatesan, Anurag Shrivastava, Sitesh Kumar Singh, Muhammad Arif, Deelopment of the Broadband Multilayer Absorption Materials with Genetic Algorithm up to 8 GHz Frequency, Security and Communication Networks

P Bagane, SG Joseph, A Singh, A Shrivastava, B Prabha, A Shrivastava, Classification of malware using Deep Learning Techniques, 2021 9th International Conference on Cyber and IT Service Management (CITSM).

A Shrivastava, SK Sharma,Various arbitration algorithm for onchip (AMBA) shared bus multi-processor SoC, 2016 IEEE Students' Conference on Electrical, Electronics and Computer Science, SCEECS 509330

Gandomi, M. Haider, “Beyond the hype: Big data concepts, methods, and analytics”, International Journal of Information Management, vol. 35, no. 2, pp. 137-144, 2015.

Shrivastava, A., Chakkaravarthy, M., Shah, M.A..A Novel Approach Using Learning Algorithm for Parkinson’s Disease Detection with Handwritten Sketches. In Cybernetics and Systems, 2022

Shrivastava, A., Chakkaravarthy, M., Shah, M.A., A new machine learning method for predicting systolic and diastolic blood pressure using clinical characteristics. In Healthcare Analytics, 2023, 4, 100219

Shrivastava, A., Chakkaravarthy, M., Shah, M.A.,Health Monitoring based Cognitive IoT using Fast Machine Learning Technique. In International Journal of Intelligent Systems and Applications in Engineering, 2023, 11(6s), pp. 720–729

Shrivastava, A., Rajput, N., Rajesh, P., Swarnalatha, S.R., IoT-Based Label Distribution Learning Mechanism for Autism Spectrum Disorder for Healthcare Application. In Practical Artificial Intelligence for Internet of Medical Things: Emerging Trends, Issues, and Challenges, 2023, pp. 305–321

Boina, R., Ganage, D., Chincholkar, Y.D., .Chinthamu, N., Shrivastava, A., Enhancing Intelligence Diagnostic Accuracy Based on Machine Learning Disease Classification. In International Journal of Intelligent Systems and Applications in Engineering, 2023, 11(6s), pp. 765–774

Shrivastava, A., Pundir, S., Sharma, A., ...Kumar, R., Khan, A.K. Control of A Virtual System with Hand Gestures. In Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, 2023, pp. 1716–1721

A. P. Srivastava, P. Choudhary, S. A. Yadav, A. Singh and S. Sharma, A System for Remote Monitoring of Patient Body Parameters, International Conference on Technological Advancements and Innovations (ICTAI), 2021, pp. 238-243,

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Published

26.03.2024

How to Cite

Kathiravan Ravichandran, B. Anita Virgin, Lucky Gupta, Aby John, Santiago Otero-Potosi, Álvaro Vargas-Chavarrea, Anurag Shrivastava. (2024). The Intelligent Technical Influence in Chat Generative Pre-Trained among Students for Modern Learning Traits. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 637–647. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5460

Issue

Vol. 12 No. 21s (2024)

Section

Research Article

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