Learning Transformation in the Human and Natural Resources Economics course through the GPT Chat: A Review”

Authors

Paulus L Wairisal

DOI:

10.29303/jppipa.v9i8.4944

Published:

2023-08-25

Issue:

Vol. 9 No. 8 (2023): August

Keywords:

Artificial Intelligence, GPT chat, science learning media

Review

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Wairisal, P. L. (2023). Learning Transformation in the Human and Natural Resources Economics course through the GPT Chat: A Review”. Jurnal Penelitian Pendidikan IPA, 9(8), 451–457. https://doi.org/10.29303/jppipa.v9i8.4944
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Abstract

In the world of education, we are led to carry out learning that is easy to understand and carried out by many developments in the field of technology. Where the purpose of the research is to explain Learning Transformation in the Human and Natural Resources Economics course through the GPT Chat. In the Human and Natural Resources Economics course, the use of GPT Chat can provide convenience for students in carrying out the learning transformation process. A review is conducted on the state-of-the-art methods using the preferred reporting items for reviews and meta-analyses (PRISMA) guidelines. In the world of education, we are led to carry out learning that is easy to understand and carried out by many developments in the field of technology. One of the learning transformations is to use AI as a technology that can help humans achieve greater progress and open up new opportunities for innovation and success in various fields. Especially in human resource and natural resource economics courses, digital-based learning transformation using GPT chat can simplify and access the information needed in the learning process.

References

Abbass, K., Qasim, M. Z., Song, H., Murshed, M., Mahmood, H., & Younis, I. (2022). A review of the global climate change impacts, adaptation, and sustainable mitigation measures. Environmental Science and Pollution Research, 29(28), 42539–42559. https://doi.org/10.1007/s11356-022-19718-6

Akour, M., & Alenezi, M. (2022). Higher Education Future in the Era of Digital Transformation. Education Sciences, 12(11), 784. https://doi.org/10.3390/educsci12110784

Andersen, A. D., Marìn, A., & Simensen, E. O. (2018). Innovation in natural resource-based industries: A development pathway? Introduction to the special issue. Innovation and Development, 8(1), 1–27. https://doi.org/10.1080/2157930X.2018.1439293

Baker, M., Domanski, A., Hollweg, T., Murray, J., Lane, D., Skrabis, K., Taylor, R., Moore, T., & DiPinto, L. (2020). Restoration Scaling Approaches to Addressing Ecological Injury: The Habitat-Based Resource Equivalency Method. Environmental Management, 65(2), 161–177. https://doi.org/10.1007/s00267-019-01245-9

Brottrager, M., Crespo Cuaresma, J., Kniveton, D., & Ali, S. H. (2023). Natural resources modulate the nexus between environmental shocks and human mobility. Nature Communications, 14(1), 1393. https://doi.org/10.1038/s41467-023-37074-y

Burger, B., Kanbach, D. K., Kraus, S., Breier, M., & Corvello, V. (2023). On the use of AI-based tools like ChatGPT to support management research. European Journal of Innovation Management, 26(7), 233–241. https://doi.org/10.1108/EJIM-02-2023-0156

Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., & De Felice, F. (2020). Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions. Sustainability, 12(2), 492. https://doi.org/10.3390/su12020492

Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383

Cook-Patton, S. C., Drever, C. R., Griscom, B. W., Hamrick, K., Hardman, H., Kroeger, T., Pacheco, P., Raghav, S., Stevenson, M., Webb, C., Yeo, S., & Ellis, P. W. (2021). Protect, manage, and then restore lands for climate mitigation. Nature Climate Change, 11(12), 1027–1034. https://doi.org/10.1038/s41558-021-01198-0

Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1–12. https://doi.org/10.1080/14703297.2023.2190148

Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., & Osher, D. (2020). Implications for educational practice of the science of learning and development. Applied Developmental Science, 24(2), 97–140. https://doi.org/10.1080/10888691.2018.1537791

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?†Multidisciplinary perspectives on opportunities, challenges, and implications of generative conversational AI for research, practice, and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: The new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 15(1), 3. https://doi.org/10.1186/s41239-017-0087-5

Elkhodr, M., Gide, E., Wu, R., & Darwish, O. (2023). ICT students’ perceptions towards ChatGPT: An experimental reflective lab analysis. STEM Education, 3(2), 70–88. https://doi.org/10.3934/steme.2023006

Fischer, G., Lundin, J., & Lindberg, O. J. (2023). The challenge for the digital age: Making learning a part of life. The International Journal of Information and Learning Technology, 40(1), 1–16. https://doi.org/10.1108/IJILT-04-2022-0079

Flake, J. K., & Fried, E. I. (2020). Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them. Advances in Methods and Practices in Psychological Science, 3(4), 456–465. https://doi.org/10.1177/2515245920952393

Flanagin, A., Bibbins-Domingo, K., Berkwits, M., & Christiansen, S. L. (2023). Nonhuman “Authors†and Implications for the Integrity of Scientific Publication and Medical Knowledge. JAMA, 329(8), 637. https://doi.org/10.1001/jama.2023.1344

G. Harkut, D., & Kasat, K. (2019). Introductory Chapter: Artificial Intelligence - Challenges and Applications. In Artificial Intelligence—Scope and Limitations. IntechOpen. https://doi.org/10.5772/intechopen.84624

Gümplová, P. (2021). Normative View of Natural Resources—Global Redistribution or Human Rights–Based Approach? Human Rights Review, 22(2), 155–172. https://doi.org/10.1007/s12142-021-00615-3

Haleem, A., Javaid, M., & Singh, R. P. (2022). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards, and Evaluations, 2(4), 100089. https://doi.org/10.1016/j.tbench.2023.100089

Hanna, N. (2018). A role for the state in the digital age. Journal of Innovation and Entrepreneurship, 7(1), 5. https://doi.org/10.1186/s13731-018-0086-3

Kakani, V., Nguyen, V. H., Kumar, B. P., Kim, H., & Pasupuleti, V. R. (2020). A critical review on computer vision and artificial intelligence in the food industry. Journal of Agriculture and Food Research, 2, 100033. https://doi.org/10.1016/j.jafr.2020.100033

Kaputa, V., LouÄanová, E., & Tejerina-Gaite, F. A. (2022). Digital Transformation in Higher Education Institutions as a Driver of Social Oriented Innovations. In Social Innovation in Higher Education, 61–85. https://doi.org/10.1007/978-3-030-84044-0_4

Kılınç, S. (2023). Embracing the Future of Distance Science Education: Opportunities and Challenges of ChatGPT Integration. Asian Journal Of Distance Education, 18(1), 205-237. https://hdl.handle.net/11511/103929.

Kooli, C. (2023). Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions. Sustainability, 15(7), 5614. https://doi.org/10.3390/su15075614

Mah, P. M., Skalna, I., & Muzam, J. (2022). Natural Language Processing and Artificial Intelligence for Enterprise Management in the Era of Industry 4.0. Applied Sciences, 12(18), 9207. https://doi.org/10.3390/app12189207

Mekuria, W., Haileslassie, A., Tengberg, A., & Zazu, C. (2021). Stakeholders' interest and influence and their interactions in managing natural resources in Lake Hawassa catchment, Ethiopia. Ecosystems and People, 17(1), 87–107. https://doi.org/10.1080/26395916.2021.1894238

Mikalef, P., & Gupta, M. (2021a). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434

Mikalef, P., & Gupta, M. (2021b). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434

Mohamad, N. A., & Mohamad, M. (2022). Confirmatory Factor Analysis on Technology Leadership Measurement. Journal of Positive School Psychology, 6125-6137. Retrieved from https://journalppw.com/index.php/jpsp/article/view/4463

Muche, M., Yemata, G., Molla, E., Muasya, A. M., & Tsegay, B. A. (2022). COVID-19 lockdown and natural resources: A global assessment on the challenges, opportunities, and the way forward. Bulletin of the National Research Centre, 46(1), 20. https://doi.org/10.1186/s42269-022-00706-2

Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., Lyden, S., Neal, P., & 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, 48(4), 559–614. https://doi.org/10.1080/03043797.2023.2213169

Oh, W. S., & Muneepeerakul, R. (2019). How do substitutability and effort asymmetry change resource management in coupled natural-human systems? Palgrave Communications, 5(1), 80. https://doi.org/10.1057/s41599-019-0289-7

Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia Journal of Mathematics, Science and Technology Education, 19(8), em2307. https://doi.org/10.29333/ejmste/13428

Partridge, D. (1987). The scope and limitations of first-generation expert systems. Future Generation Computer Systems, 3(1), 1–10. https://doi.org/10.1016/0167-739X(87)90038-0

Sallam, M. (2023). ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887

Samala, N., Katkam, B. S., Bellamkonda, R. S., & Rodriguez, R. V. (2022). Impact of AI and robotics in the tourism sector: A critical insight. Journal of Tourism Futures, 8(1), 73–87. https://doi.org/10.1108/JTF-07-2019-0065

Sanmarchi, F., Bucci, A., Nuzzolese, A. G., Carullo, G., Toscano, F., Nante, N., & Golinelli, D. (2023). A step-by-step researcher’s guide to the use of an AI-based transformer in epidemiology: An exploratory analysis of ChatGPT using the STROBE checklist for observational studies. Journal of Public Health, 1-36. https://doi.org/10.1007/s10389-023-01936-y

Sarker, I. H. (2022). AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems. SN Computer Science, 3(2), 158. https://doi.org/10.1007/s42979-022-01043-x

Schellens, M. K., & Gisladottir, J. (2018). Critical Natural Resources: Challenging the Current Discourse and Proposal for a Holistic Definition. Resources, 7(4), 79. https://doi.org/10.3390/resources7040079

Schuurman, G. W., Cole, D. N., Cravens, A. E., Covington, S., Crausbay, S. D., Hoffman, C. H., Lawrence, D. J., Magness, D. R., Morton, J. M., Nelson, E. A., & O’Malley, R. (2022). Navigating Ecological Transformation: Resist–Accept–Direct as a Path to a New Resource Management Paradigm. BioScience, 72(1), 16–29. https://doi.org/10.1093/biosci/biab067

Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(1), 54. https://doi.org/10.1186/s41239-021-00292-9

Shah, Z., Zaman, K., Khan, H. U. R., & Rashid, A. (2022). The Economic Value of Natural Resources and Its Implications for Pakistan’s Economic Growth. Commodities, 1(2), 65–97. https://doi.org/10.3390/commodities1020006

Taecharungroj, V. (2023). “What Can ChatGPT Do?†Analyzing Early Reactions to the Innovative AI Chatbot on Twitter. Big Data and Cognitive Computing, 7(1), 35. https://doi.org/10.3390/bdcc7010035

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT is a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x

Tyagi, N., & Bhushan, B. (2023). Demystifying the Role of Natural Language Processing (NLP) in Smart City Applications: Background, Motivation, Recent Advances, and Future Research Directions. Wireless Personal Communications, 130(2), 857–908. https://doi.org/10.1007/s11277-023-10312-8

Wulansari, T. P., Sudiyanto, S., & Sumaryati, S. (2023). Chances and Challenges of Digital-Based Education: A Literature Review. In Proceedings of the Tegal International Conference on Applied Social Science & Humanities (TICASSH 2022), 508–517. https://doi.org/10.2991/978-2-494069-09-1_59

Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., Liu, X., Wu, Y., Dong, F., Qiu, C.-W., Qiu, J., Hua, K., Su, W., Wu, J., Xu, H., Han, Y., Fu, C., Yin, Z., Liu, M., … Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4), 100179. https://doi.org/10.1016/j.xinn.2021.100179

Author Biography

Paulus L Wairisal, Universitas Pattimura

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