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Tell Me Your Prompts and I Will Make Them True: The Alchemy of Prompt Engineering and Generative AI Cover

Tell Me Your Prompts and I Will Make Them True: The Alchemy of Prompt Engineering and Generative AI

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Open Access
|Apr 2024

References

  1. Ansari, A. N., Ahmad, S., & Bhutta, S. M. (2023). Mapping the global evidence around the use of ChatGPT in higher education: A systematic scoping review. Education and Information Technologies, 141. DOI: 10.1007/s10639-023-12223-4
  2. Bozkurt, A. (2023a). Generative artificial intelligence (AI) powered conversational educational agents: The inevitable paradigm shift. Asian Journal of Distance Education, 18(1), 198204. DOI: 10.5281/zenodo.7716416
  3. Bozkurt, A. (2023b). Unleashing the potential of generative AI, conversational agents and chatbots in educational praxis: A systematic review and bibliometric analysis of GenAI in education. Open Praxis, 15(4), 261270. DOI: 10.55982/openpraxis.15.4.609
  4. Bozkurt, A. (2023c). Generative AI, synthetic contents, open educational resources (OER), and open educational practices (OEP): A new front in the openness landscape. Open Praxis, 15(3), 78184. DOI: 10.55982/openpraxis.15.3.579
  5. Bozkurt, A. (2024). GenAI et al.: Cocreation, authorship, ownership, academic ethics and integrity in a time of generative AI. Open Praxis, 16(1). DOI: 10.55982/openpraxis.16.1.654
  6. Bozkurt, A., & Sharma, R. C. (2023). Generative AI and prompt engineering: The art of whispering to let the genie out of the algorithmic world. Asian Journal of Distance Education, 18(2), ivii. DOI: 10.5281/zenodo.8174941
  7. Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C. M., Romero-Hall, E., Koutropoulos, A., Toquero, C. M., Singh, L., Tlili, A., Lee, K., Nichols, M., Ossiannilsson, E., Brown, M., Irvine, V., Raffaghelli, J. E., Santos-Hermosa, G., Farrell, O., Adam, T., Thong, Y. L., Sani-Bozkurt, S., Sharma, R. C., Hrastinski, S., & Jandrić, P. (2023). Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), 53130. DOI: 10.5281/zenodo.7636568
  8. Bsharat, S. M., Myrzakhan, A., & Shen, Z. (2023). Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4. arXiv. DOI: 10.48550/arXiv.2312.16171
  9. Chen, B., Zhang, Z., Langrené, N., & Zhu, S. (2023). Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review. arXiv. DOI: 10.48550/arXiv.2310.14735
  10. Dang, H., Mecke, L., Lehmann, F., Goller, S., & Buschek, D. (2022). How to prompt? Opportunities and challenges of zero-and few-shot learning for human-AI interaction in creative applications of generative models. arXiv. DOI: 10.48550/arXiv.2209.01390
  11. Descartes, R. (1637). Discourse on the Method of Rightly Conducting One’s Reason and of Seeking Truth in the Sciences. Project Gutenberg. https://www.gutenberg.org/files/59/59-h/59-h.htm
  12. Diao, S., Wang, P., Lin, Y., & Zhang, T. (2023). Active prompting with chain-of-thought for large language models. arXiv. DOI: 10.48550/arXiv.2302.12246
  13. 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. DOI: 10.1016/j.ijinfomgt.2023.102642
  14. Gates, B. (2023). The Age of AI has begun. Gates Notes. https://www.gatesnotes.com/The-Age-of-AI-Has-Begun
  15. Johnson, W. L. (2023). How to Harness Generative AI to Accelerate Human Learning. International Journal of Artificial Intelligence in Education, 15. DOI: 10.1007/s40593-023-00367-w
  16. Kakun, A., & Tytenko, S. (2023). Generative AI And Prompt Engineering in Education. Modern Engineering and Innovative Technologies, 1(29-01), 117121. DOI: 10.30890/2567-5273.2023-29-01-052
  17. Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Kuttler, H., Lewis, M., Yih, W., Rocktäschel, T., Riedel, S., & Kiela, D. (2020). Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems, 33, 94599474. https://dl.acm.org/doi/abs/10.5555/3495724.3496517
  18. Li, Z., Peng, B., He, P., Galley, M., Gao, J., & Yan, X. (2023). Guiding Large Language Models via Directional Stimulus Prompting. arXiv. DOI: 10.48550/arXiv.2302.11520
  19. Liu, Y., Deng, G., Xu, Z., Li, Y., Zheng, Y., Zhang, Y., Zhao, L., Zhang, T., & Liu, Y. (2023c). Jailbreaking chatGPT via prompt engineering: An empirical study. arXiv. DOI: 10.48550/arXiv.2305.13860
  20. Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2023a). Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. ACM Computing Surveys, 55(9), 135. DOI: 10.1145/3560815
  21. Liu, Z., Yu, X., Fang, Y., & Zhang, X. (2023b). Graphprompt: Unifying pre-training and downstream tasks for graph neural networks. In Proceedings of the ACM Web Conference 2023 (pp. 417428). 30 April 2023–4 May 2023, Austin, TX, USA. DOI: 10.1145/3543507.3583386
  22. Lo, L. S. (2023a). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720. DOI: 10.1016/j.acalib.2023.102720
  23. Lo, L. S. (2023b). The Art and Science of Prompt Engineering: A New Literacy in the Information Age. Internet Reference Services Quarterly, 27(4), 203210. DOI: 10.1080/10875301.2023.2227621
  24. McGuire, A. (2023). Leveraging ChatGPT for Rethinking Plagiarism, Digital Literacy, and the Ethics of Co-Authorship in Higher Education: A Position Paper and Comparative Critical Reflection of Composing Processes. Irish Journal of Technology Enhanced Learning, 7(2), 2131. DOI: 10.22554/ijtel.v7i2.131
  25. Merriam-Webster. (2024a). Art. Merriam-Webster.com dictionary. https://www.merriam-webster.com/dictionary/art
  26. Merriam-Webster. (2024b). Science. Merriam-Webster.com dictionary. https://www.merriam-webster.com/dictionary/science
  27. O’Connor, S., Peltonen, L.-M., Topaz, M., Chen, L.-Y. A., Michalowski, M., Ronquillo, C., Stiglic, G., Chu, C. H., Hui, V., & Denis-Lalonde, D. (2024). Prompt engineering when using generative AI in nursing education. Nurse Education in Practice, 74, 103825. DOI: 10.1016/j.nepr.2023.103825
  28. OpenAI. (2022). Introducing ChatGPT. https://openai.com/blog/chatgpt
  29. OpenAI. (2023a). ChatGPT can now see, hear, and speak. https://openai.com/blog/chatgpt-can-now-see-hear-and-speak
  30. OpenAI. (2023b). Prompt engineering. https://platform.openai.com/docs/guides/prompt-engineering
  31. Paranjape, B., Lundberg, S., Singh, S., Hajishirzi, H., Zettlemoyer, L., & Ribeiro, M. T. (2023). ART: Automatic multi-step reasoning and tool-use for large language models. arXiv. DOI: 10.48550/arXiv.2303.09014
  32. Sarı, T., Nayir, F., & Bozkurt, A. (2024). Reimagining education: Bridging artificial intelligence, transhumanism, and critical pedagogy. Journal of Educational Technology and Online Learning, 7(1), 102115. DOI: 10.31681/jetol.1308022
  33. Sharma, R. C., & Bozkurt, A. (2024). Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation. IGI Global. DOI: 10.4018/979-8-3693-1351-0
  34. Velásquez-Henao, J. D., Franco-Cardona, C. J., & Cadavid-Higuita, L. (2023). Prompt Engineering: a methodology for optimizing interactions with AI-Language Models in the field of engineering. DYNA, 90(230), 917. DOI: 10.15446/dyna.v90n230.111700
  35. Wei, J., Wang, X., Schuurmans, D., Bosma, M., Chi, E. H., Xia, F., Le, Q., & Zhou, D. (2022). Chain of Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems, 35, 2482424837. https://proceedings.neurips.cc/paper_files/paper/2022/hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html
  36. White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Gilbert, H., Elnashar, A., Spencer-Smith, J., & Schmidt, D. C. (2023). A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT. arXiv. DOI: 10.48550/arXiv.2302.11382
  37. Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T. L., Cao, Y., & Narasimhan, K. (2023). Tree of thoughts: Deliberate problem solving with large language models. arXiv. DOI: 10.48550/arXiv.2305.10601
  38. Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., & Cao, Y. (2022). React: Synergizing reasoning and acting in language models. arXiv. DOI: 10.48550/arXiv.2210.03629
  39. Yong, G., Jeon, K., Gil, D., & Lee, G. (2023). Prompt engineering for zero-shot and few-shot defect detection and classification using a visual-language pretrained model. Computer-Aided Civil and Infrastructure Engineering, 38(11), 15361554. DOI: 10.1111/mice.12954
  40. Zhang, Z., Zhang, A., Li, M., Zhao, H., Karypis, G., & Smola, A. (2023). Multimodal chain-of-thought reasoning in language models. arXiv. DOI: 10.48550/arXiv.2302.00923
  41. Zhou, D., Scharli, N., Hou, L., Wei, J., Scales, N., Wang, X., Schuurmans, D., Bousquet, O., Le, Q., & Chi, E. H. (2022). Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. arXiv. DOI: 10.48550/arXiv.2205.10625
Language: English
Page range: 111 - 118
Submitted on: Jan 30, 2024
Accepted on: Feb 27, 2024
Published on: Apr 3, 2024
Published by: International Council for Open and Distance Education (ICDE)
In partnership with: Paradigm Publishing Services

© 2024 Aras Bozkurt, published by International Council for Open and Distance Education (ICDE)
This work is licensed under the Creative Commons Attribution 4.0 License.