Effectiveness of Artificial Intelligent Independent Learning (AIIL) with physics chatbot of global warming concept
Abstract
This research aims to analyze the effectiveness of Artificial Intelligent Independent Learning (AIIL) with physics chatbot of global warming concept. Method of research uses the Research & Development method referring to the ADDIE development model. This research was conducted with 64 students at Senior High School in Indonesia who were divided into chatbot-based experimental groups and control groups. The results of this study were obtained by conducting the normalized gain <g> test of 0.60 (medium category) for the control group and 0.87 (high category) in the experimental group. As for the results of the Cohen's D effect-size test, the result was 0.93 with high category AAIL for increasing learning outcome. Thus, the developed AAIL chatbot has high effectiveness in increasing learning outcome.
References
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Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI chatbots for content and language integrated learning. Applied Sciences, 12(7), 3239.
Mahroof, A., Gamage, V., Rajendran, K., Rajkumar, S., Rajapaksha, S., & Wijendra, D. (2020). An AI based Chatbot to Self-Learn and Self-Assess Performance in Ordinary Level Chemistry. 2020 2nd International Conference on Advancements in Computing (ICAC), 216–221. https://doi.org/10.1109/ICAC51239.2020.9357131
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Nirala, K. K., Singh, N. K., & Purani, V. S. (2022). A survey on providing customer and public administration based services using AI: chatbot. Multimedia Tools and Applications, 81(16), 22215-22246.
Ong, R. J. et al. (2021). A Review of Chatbot development for Dynamic Web-based Knowledge Management System (KMS) in Small Scale Agriculture. Journal of Physics: Conference Series 1755. doi:10.1088/1742-6596/1755/1/012051
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Shaturaev, J. (2022). Economies and management as a result of the fourth industrial revolution: An education perspective. Indonesian Journal of Educational Research and Technology, 3(1), 51-58.
Sinha, S., Basak, S., Dey, Y., et al. (2020). An Educational Chatbot for Answering Queries. Advances in Intelligent Systems and Computing, 937, 55-60. https://doi.org/10.1007/978981-13-7403-6_7
Spatioti, A. G., Kazanidis, I., & Pange, J. (2022). A comparative study of the ADDIE instructional design model in distance education. Information, 13(9), 402.
Suhel, S. F., Shukla, V. K., Vyas, S., & Mishra, V. P. (2020, June). Conversation to automation in banking through chatbot using artificial machine intelligence language. In 2020 8th international conference on reliability, infocom technologies and optimization (trends and future directions) (ICRITO) (pp. 611-618). IEEE.
Vanichvasin, P. (2021). Chatbot Development as a Digital Learning Tool to Increase Students’ Research Knowledge. International Education Studies, 14(2), 44. https://doi.org/10.5539/ies.v14n2p44
Wong, A. (2022). The Design of an Intelligent Chatbot with Natural Language Processing Capabilities to Support Learners. Journal of Physics: Conference Series 2251. DOI 10.1088/1742-6596/2251/1/012005
Yin, J., Goh, T.-T., Yang, B., & Xiaobin, Y. (2021). Conversation Technology 46 With Micro-Learning: The Impact of Chatbot-Based Learning on Students’ Learning Motivation and Performance. Journal of Educational Computing Research, 59(1), 154–177. https://doi.org/10.1177/0735633120952067
Zhang, Z., Wen, F., Sun, Z., Guo, X., He, T., & Lee, C. (2022). Artificial intelligence‐enabled sensing technologies in the 5G/internet of things era: from virtual reality/augmented reality to the digital twin. Advanced Intelligent Systems, 4(7), 2100228
Ashrafi, A., Zareravasan, A., Rabiee Savoji, S., & Amani, M. (2022). Exploring factors influencing students’ continuance intention to use the learning management system (LMS): a multi-perspective framework. Interactive Learning Environments, 30(8), 1475-1497.
Chakrabortty, R. K., Abdel-Basset, M., & Ali, A. M. (2023). A multi-criteria decision analysis model for selecting an optimum customer service chatbot under uncertainty. Decision Analytics Journal, 6, 100168.
Chander, B., Pal, S., De, D., & Buyya, R. (2022). Artificial intelligence-based internet of things for industry 5.0. Artificial intelligence-based internet of things systems, 3-45.
Choudhury, M. D., Lee, M. K., Zhu, H., & Shamma, D. A. (2020). Introduction to this special issue on unifying human computer interaction and artificial intelligence. Human–Computer Interaction, 35(5-6), 355-361.
Cîmpeanu, I. A. (2021). Business Activities Using Chatbots. Informatica economica, 25(3).
Dahlkemper, M. N., Lahme, S. Z., & Klein, P. (2023). How do physics students evaluate artificial intelligence responses on comprehension questions? A study on the perceived scientific accuracy and linguistic quality of ChatGPT. Physical Review Physics Education Research, 19(1), 010142.
David, B., Chalon, R., & Zhang, X. (2022). Virtual Assistants (Chatbots) as help to teachers in Collaborative Learning Environment. In International Conference on Interactive Collaborative Learning (pp. 135-146). Cham: Springer International Publishing.
English, L. M., & Carlsen, A. (2019). Lifelong learning and the Sustainable Development Goals (SDGs): Probing the implications and the effects. International Review of Education, 65, 205-211.
Geng, S., Law, K. M., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16(1), 1-22.
Gnewuch, U., Morana, S., Adam, M. T., & Maedche, A. (2022). Opposing Effects of Response Time in Human–Chatbot Interaction: The Moderating Role of Prior Experience. Business & Information Systems Engineering, 64(6), 773-791.
Gonda, D. E., & Chu, B. (2019). Chatbot as a learning resource? Creating conversational bots as a supplement for teaching assistant training course. 2019 IEEE International Conference on Engineering, Technology and Education (TALE), 1-5, doi:10.1109/TALE48000.2019.9225974
Goulet-Pelletier, J. C., & Cousineau, D. (2018). A review of effect sizes and their confidence intervals, Part I: The Cohen’sd family. The Quantitative Methods for Psychology, 14(4), 242-265.
Gudala, M., Ross, M. E. T., Mogalla, S., Lyons, M., Ramaswamy, P., & Roberts, K. (2022). Benefits of, barriers to, and needs for an artificial intelligence–powered medication information voice chatbot for older adults: interview study with geriatrics experts. JMIR aging, 5(2), e32169.
Hake, R. R. (2002). Relationship of individual student normalized learning gains in mechanics with gender, high-school physics, and pretest scores on mathematics and spatial visualization. In Physics education research conference. 8(1), 1-14).
Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275-285.
Handayani, R. D., & Putra, P. D. (2019). Student cognition in the context of a climate system: Global warming and greenhouse effect. Momentum: Physics Education Journal, 69-77.
Haristiani, N. (2019). Artificial Intelligence (AI) chatbot as language learning medium: An inquiry. In Journal of Physics: Conference Series (Vol. 1387, No. 1, p. 012020). IOP Publishing.
Huang, Duen., & Chueh, Hao-En. (2021). Chatbot Usage Intention Analysis: Veterinary Consultation. Journal of Innovation & Knowledge, 6(3), 135-144. https://doi.org/10.1016/j.jik.2020.09.002
Krishnan, C., Gupta, A., Gupta, A., & Singh, G. (2022). Impact of artificial intelligence-based chatbots on customer engagement and business growth. In Deep Learning for Social Media Data Analytics (pp. 195-210). Cham: Springer International Publishing.
Küchemann, S., Steinert, S., Revenga, N., Schweinberger, M., Dinc, Y., Avila, K. E., & Kuhn, J. (2023). Physics task development of prospective physics teachers using ChatGPT. arXiv preprint arXiv:2304.10014.
Kurt, S. (2019). An introduction to the addie model: Instructional design: The Addie approach. Independently published.
Lee, D., & Yeo, S. (2022). Developing an AI-based chatbot for practicing responsive teaching in mathematics. Computers & Education, 191, 104646.
MacIsaac, D. (2023). Chatbots Attempt Physics Homework—ChatGPT: Chat Generative Pre-Trained Transformer. The Physics Teacher, 61(4), 318-318.
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI chatbots for content and language integrated learning. Applied Sciences, 12(7), 3239.
Mahroof, A., Gamage, V., Rajendran, K., Rajkumar, S., Rajapaksha, S., & Wijendra, D. (2020). An AI based Chatbot to Self-Learn and Self-Assess Performance in Ordinary Level Chemistry. 2020 2nd International Conference on Advancements in Computing (ICAC), 216–221. https://doi.org/10.1109/ICAC51239.2020.9357131
Mai, N. E. O. (2022). The Merlin Project: Malaysian Students’acceptance Of An Ai Chatbot In Their Learning Process. Turkish Online Journal of Distance Education, 23(3), 31-48.
Manson, E. N., Hasford, F., Trauernicht, C., Ige, T. A., Inkoom, S., Inyang, S., ... & Stoeva, M. (2023). Africa’s readiness for artificial intelligence in clinical radiotherapy delivery: Medical physicists to lead the way. Physica Medica, 113, 102653.
Mufadhol, M., Wibowo, A., & Santoso, J. T. (2020). Digital marketing techniques for business intelligence systems use automated chatbot machine learning. PalArch's Journal of Archaeology of Egypt/Egyptology, 17(7), 6895-6906.
Nguyen, H. D., Pham, V. T., Tran, D. A., & Le, T. T. (2019). Intelligent tutoring chatbot for solving mathematical problems in High-school. 2019 11th International Conference on Knowledge and Systems Engineering (KSE), 1–6. https://doi.org/10.1109/KSE.2019.8919396
Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., ... & Sandison, C. (2023). ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 1-56.
Nirala, K. K., Singh, N. K., & Purani, V. S. (2022). A survey on providing customer and public administration based services using AI: chatbot. Multimedia Tools and Applications, 81(16), 22215-22246.
Ong, R. J. et al. (2021). A Review of Chatbot development for Dynamic Web-based Knowledge Management System (KMS) in Small Scale Agriculture. Journal of Physics: Conference Series 1755. doi:10.1088/1742-6596/1755/1/012051
P dos Santos, R. (2023). Enhancing Physics Learning with ChatGPT, Bing Chat, and Bard as Agents-to-Think-With: A Comparative Case Study. Enhancing Physics Learning with ChatGPT, Bing Chat, and Bard as Agents-to-Think-With: A Comparative Case Study (June 01, 2023).
Rakhra, M., Gopinadh, G., Addepalli, N. S., Singh, G., Aliraja, S., Reddy, V. S. G., & Reddy, M. N. (2021). E-Commerce Assistance with a Smart Chatbot using Artificial Intelligence. 2021 2nd International Conference on Intelligent Engineering and Management (ICIEM), 144–148. https://doi.org/10.1109/ICIEM51511.2021.9445316
Shaturaev, J. (2022). Economies and management as a result of the fourth industrial revolution: An education perspective. Indonesian Journal of Educational Research and Technology, 3(1), 51-58.
Sinha, S., Basak, S., Dey, Y., et al. (2020). An Educational Chatbot for Answering Queries. Advances in Intelligent Systems and Computing, 937, 55-60. https://doi.org/10.1007/978981-13-7403-6_7
Spatioti, A. G., Kazanidis, I., & Pange, J. (2022). A comparative study of the ADDIE instructional design model in distance education. Information, 13(9), 402.
Suhel, S. F., Shukla, V. K., Vyas, S., & Mishra, V. P. (2020, June). Conversation to automation in banking through chatbot using artificial machine intelligence language. In 2020 8th international conference on reliability, infocom technologies and optimization (trends and future directions) (ICRITO) (pp. 611-618). IEEE.
Vanichvasin, P. (2021). Chatbot Development as a Digital Learning Tool to Increase Students’ Research Knowledge. International Education Studies, 14(2), 44. https://doi.org/10.5539/ies.v14n2p44
Wong, A. (2022). The Design of an Intelligent Chatbot with Natural Language Processing Capabilities to Support Learners. Journal of Physics: Conference Series 2251. DOI 10.1088/1742-6596/2251/1/012005
Yin, J., Goh, T.-T., Yang, B., & Xiaobin, Y. (2021). Conversation Technology 46 With Micro-Learning: The Impact of Chatbot-Based Learning on Students’ Learning Motivation and Performance. Journal of Educational Computing Research, 59(1), 154–177. https://doi.org/10.1177/0735633120952067
Zhang, Z., Wen, F., Sun, Z., Guo, X., He, T., & Lee, C. (2022). Artificial intelligence‐enabled sensing technologies in the 5G/internet of things era: from virtual reality/augmented reality to the digital twin. Advanced Intelligent Systems, 4(7), 2100228
Authors
Kusuma, A. A. K., Maharani, W. A. D., Wibowo, F. C., Nasbey, H., & Costu, B. (2024). Effectiveness of Artificial Intelligent Independent Learning (AIIL) with physics chatbot of global warming concept. Momentum: Physics Education Journal, 8(1), 42–54. https://doi.org/10.21067/mpej.v8i1.8942
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