GENERATIVE AI AND PROMPT ENGINEERING IN EDUCATION
DOI:
https://doi.org/10.30890/2567-5273.2023-29-01-052Ключові слова:
Generative AI, education, ChatGPT, Prompt EngineeringАнотація
The development of generative AIs and the variability of their use are still at the level of research and active development simultaneously. However, it has already become clear that the emergence of generative AI significantly impacts many industries, inMetrics
Посилання
References: A. Tong, Routers (2023). Exclusive: ChatGPT traffic slips again for third month in a row.
OpenAI (2023). About ChatGPT.
Sahoo S, Kumar S, Abedin M, Lim WM, Jakhar SK (2022). Deep Learning Applications in Manufacturing Operations: A Review of Trends and Ways Forward. Journal of Enterprise Information Management ISSN: 1741-0398.
DOI: 10.1108/JEIM-01-2022-0025
Weng Marc Lim , Asanka Gunasekara, Jessica Leigh Pallant, Jason Ian Pallant, Ekaterina Pechenkina. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education Volume 21.
DOI: 10.1016/j.ijme.2023.100790
Weng Marc Lim, Satish Kumar, Sanjeev Verma, Rijul Chaturvedi (2022). Alexa, what do we know about conversational commerce? Insights from a systematic literature review March 2022 Psychology and Marketing 39.
DOI: 10.1002/mar.21654
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio (2014). Generative Adversarial Networks. Advances in Neural Information Processing Systems.
DOI: 10.1145/3422622
Diederik P Kingma, Max Welling (2014). Auto-Encoding Variational Bayes. Conference: ICLR.
Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova (October 2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
A. Radford, K.Narasimhan, T. Salimans, I. Sutskever (2018). Improving language understanding by generative pre-training.
Liu Kexin, Qu Yi, Song Xiaoou, Li Yan (202). Future Education Trend Learned From the Covid-19 Pandemic: Take ≪Artificial Intelligence≫ Online Course As an Example. Conference: 2020 International Conference on Artificial Intelligence and Education (ICAIE).
DOI: 10.1109/ICAIE50891.2020.00032
Olga Tapalova, Nadezhda Zhiyenbayeva, Dmitry Gura (2022). Artificial Intelligence in Education: AIEd for Personalised Learning Pathways December. The Electronic Journal of e-Learning 20(5):639-653.
DOI: 10.34190/ejel.20.5.2597
Wayne Holmes, Ilkka Tuomi (2022). State of the art and practice in AI in education. European Journal of Education 57(3).
DOI: 10.1111/ejed.12533
Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G (2021). Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing.
Liu, Y., Deng, G., Xu, Z., Li, Y., Zheng, Y., Zhang, Y., Zhao, L., Zhang, T., & Liu, Y. (2023). Jailbreaking chatGPT via prompt engineering: An empirical study.
DOI: 10.48550/arXiv.2305.13860
Leo S. Lo (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering.
DOI: 10.1016/j.acalib.2023.102720
Diab M., Herrera J., Chernow B (2022). Stable Diffusion Prompt Book.
Albert Ziegler, John Berryman (2023). A developer's guide to prompt engineering and LLMs.
Aras Bozkurt, Ramesh C Sharma (2023). Generative AI and Prompt Engineering: The Art of Whispering to Let the Genie Out of the Algorithmic World.
DOI: 10.5281/zenodo.8174941
Опубліковано
Як цитувати
Номер
Розділ
Ліцензія
Авторське право (c) 2023 Автори
Ця робота ліцензується відповідно до Creative Commons Attribution 4.0 International License.
