Page 244 - Izobraževanje v dobi generativne umetne inteligence
P. 244

Alenka Lipovec in Barbara Arcet

                  Rane, N. (2023, 20. avgust). Enhancing mathematical capabilities through ChatGPT and
                      similar generative artificial intelligence: Roles and challenges in solving mathemat-
                      ical problems. Social Science Research Network. http://dx.doi.org/10.2139/ssrn
                      .4603237
                  Sancenon, V., Wijaya, K., Wen, X. Y. S., Utama, D. A., Ashworth, M., Ng, K. H. ,Cheong,
                      A., in Neo, Z. (2022). A new web-based personalized learning system improves
                      student learning outcomes. International Journal of Virtual and Personal Learning
                      Environments, 12(1). https://doi.org/10.4018/IJVPLE.295306
                  Shukla, A. K., Terziyan, V., in Tiihonen, T. (2024). AI as a user of AI: Towards responsible
                      autonomy. Heliyon, 10(11), e31397.
                  Tao, T.  (2024, 16. september).  In https://chatgpt.com/share/94152e76-7511-4943-9d99
                      -1118267f4b2b I gave the new model a challenging complex analysis problem [Ob-
                      java na decentraliziranem družabnem mediju]. Mastodon. https://mathstodon
                      .xyz/@tao/113132503432772494
                  Thomas, D. R., Gatz, E., Gupta, S., Aleven, V., in Koedinger, K. R. (2024). The neglected
                      15%: Positive effects of hybrid human-AI tutoring among students with disabil-
                      ities. V A. M. Olney, I. A. Chounta, Z. Liu Zitao, O. C. Santos in I. Bittencourt (ur.),
                      Artificial intelligence in education (AIED 2024): Lecture notes in computer science
                      (str. 409–423). Springer.
                  Thomas, D. R., Lin, J., Gatz, E., Gurung, A., Gupta, S., Norberg, K., Fancsali, S. E., Aleven,
                      V., Branstetter, L., Brunskill, E., in Koedinger, K. R. (2024). Improving student
                      learning with hybrid human-AI tutoring: A three-study quasi-experimental
                      investigation. V Proceedings of the 14th Learning Analytics and Knowledge Confer-
                      ence (str. 404–415). Association for Computing Machinery.
                  Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., in Zhou, D. (2022,
                      10. oktober). Chain-of-thought prompting elicits reasoning in large language
                      models. ArXiv. https://doi.org/10.48550/arXiv.2201.11903
                  Ye, Q., Axmed, M., Pryzant, R., in Khani, F. (2023). Prompt engineering a prompt
                      engineer. V Findings of the Association for Computational Linguistics 2024 (str.
                      355–385). Association for Computational Linguistics.
                  Zamfirescu-Pereira, J. D., Wong, R. J., Hartmann, B., in Yang, Q. (2023). Why Johnny can‘t
                      prompt: How non-AI experts try (and fail) to design LLM prompts. V A. Schmidt,
                      K. Väänänen, T. Goyal, P. O. Kristensson, S. Mueller, J. R. Williamson in M. L. Wilson
                      (ur.), Proceedings of the 2023 CHI Conference on Human Factors in Computing
                      Systems (str. 1–21). Association for Computing Machinery.
                  Zhang, Y., Yuan, Y., in Yao, A. C.-C. (2023, 20. november). Meta prompting for AI systems.
                      Arxiv. https://doi.org/10.48550/arXiv.2311.11482
                  Žerovnik, A., in Zapušek, M. (2024). Uporaba generativne umetne inteligence v izo-
                      braževanju. Pedagoška fakulteta.







                  244
   239   240   241   242   243   244   245   246   247   248   249