Autors: Ivanova S., Dimitrov, L. V., Ivanov V., Volkova M.
Title: The Ability of Artificial Intelligence to Create Mind Maps with the Effect of Insight
Keywords: Artificial Intelligence Hallucinations, Enhance Creativity, Gauss’s Theorem, Herringbone Gear

Abstract: The well-known advantages of using mind maps in education are increased interest, systematization of knowledge and better memorization. Also, the use of mind maps increases the creative potential of students. Artificial intelligence can help students create intelligence maps to systematize knowledge. The most interesting thing is whether artificial intelligence can cope with issues of creativity? In order to answer this question, with the help of artificial intelligence a well-known task was solved - formula for the sum of the terms of an arithmetic progression. Free versions of artificial intelligence ChatGPT and You.com were used. We received two versions of the mind map, illustrating the proof of Gauss’s formula. A search on the Internet did not find any matches between these maps and existing ones, that is, they are original. These mind maps fulfil, to a certain extent, the task assigned to artificial intelligence to create mind maps with an insight effect and can be used in the educational process. The application of artificial intelligence in a narrower field – mechanical engineering – is considered. The task was to create a mind map that would allow students to invent a herringbone gear. ChatGPT turned out to be perfect in terms of systematization of knowledge and helpless in terms of creativity. You.com Research, after additional questions and permission not to adhere to the Procrustean lodge, the definition of a mind map, suggested the right idea. It has been established that the limited capabilities of artificial intelligence to create mind maps in the field of machine science are not only related to the limited “creative” capabilities of free services, but also to the insufficient knowledge base in machine science that they can use.

References

  1. Lozano R Barreiro-Gen M Lozano FJ Sammalisto K Teaching sustainability in European higher education institutions: assessing the connections between competences and pedagogical approaches Sustainability 2019 11 6 1602 2019Sust..11.1602L 10.3390/su11061602
  2. Evans T Jeong I Concept maps as assessment for learning in university mathematics Educ. Stud. Math. 2023 113 3 475 498 10.1007/s10649-023-10209-0
  3. Fu QK Lin CJ Hwang GJ Zhang L Impacts of a mind mapping-based contextual gaming approach on EFL students’ writing performance, learning perceptions and generative uses in an English course Comput. Educ. 2019 137 59 77 10.1016/j.compedu.2019.04.005
  4. Kefalis C Skordoulis C Drigas A A systematic review of mind maps, STEM education algorithmic and procedural learning Computers 2025 14 6 204 10.3390/computers14060204
  5. Wei X Wang L Lee LK The effects of generative AI on collaborative problem-solving and team creativity performance in digital story creation: an experimental study Int. J. Educ. Technol. High. Educ. 2025 22 23 10.1186/s41239-025-00526-0
  6. Crowe M Sheppard L Mind mapping research methods Qual. Quant. 2012 46 5 1493 1504 10.1007/s11135-011-9463-8
  7. Sun M Wang M Wegerif R Peng J How do students generate ideas together in scientific creativity tasks through computer-based mind mapping? Comput. Educ. 2022 176 104359 10.1016/j.compedu.2021.104359
  8. Fung D Liang T The effectiveness of collaborative mind mapping in Hong Kong primary science classrooms Int. J. Sci. Math. Educ. 2022 21 3 899 922 10.1007/s10763-022-10279-1
  9. Musniah M Implementasi Metode Mind Map untuk Meningkatkan Hasil Belajar Matematika Materi Bangun Ruang bagi Siswa Kelas V SDN 29 Mataram Jurnal Paedagogy 2022 9 2 294 301 10.33394/jp.v9i2.4913
  10. Buzan T Mind Map Mastery: The Complete Guide to Learning and Using the Most Powerful Thinking Tool in the Universe 2018 London Watkins Media Limited
  11. Buzan T Buzan B The Mind Map Book 2006 London Pearson Education
  12. Asyraf MR Ishak MRM Sapuan SM Yidris N Ilyas R Razman MR Integration of TRIZ, morphological chart and ANP method for development of FRP composite portable fire extinguisher Polym. Compos. 2020 41 7 2917 2932 1:CAS:528:DC%2BB3cXot1Wlurc%3D 10.1002/pc.25587
  13. Tran, T.T.: Using Mind-mapping as a transition from receptive to productive skills for second-degree learners. VNU J. Foreign Stud. 35(1) (2019). https://doi.org/10.25073/2525-2445/vnufs.4344
  14. Guerrero JM Ramos P Introduction to the Applications of Mind Mapping in Medicine 2015 London Imedpub
  15. Eppler MJ A comparison between concept maps, mind maps, conceptual diagrams, and visual metaphors as complementary tools for knowledge construction and sharing Inf. Vis. 2006 5 3 202 210 10.1057/palgrave.ivs.9500131
  16. Ivanov, V., Ivanova, S., Dimitrov, L., Olefir, O.: Heuristic techniques as part of heuristic methods and interaction of personality types in their application. Adv. Sci., Technol. Eng. Syst. J. 6(1), 208–217 (2021). https://doi.org/10.25046/aj060123
  17. Sivaloganathan, S., Al-Marzouqi, A.H., Zaneldin, E.K.: Teaching conceptual design to a heterogeneous group: a workshop method. In: 2020 ASEE Virtual Annual Conference Content Access, pp. 1–10. ASEE, Virtual (2020)
  18. Kasim, U., Erdiana, N., Aulia, D.: The use of fishbone diagram technique to improve students’ writing ability. In: Proceedings of AICS-Social Sciences, vol. 11, 191–197 (2021)
  19. Iranmanesh H Madadi M An intelligent system framework for generating activity list of a project using WBS mind map and semantic network Int. J. Comput. Inf. Eng. 2008 2 4 1020 1027
  20. Vázquez-Cano E Mengual-Andrés S López-Meneses E Chatbot to improve learning punctuation in Spanish and to enhance open and flexible learning environments Int. J. Educ. Technol. High. Educ. 2021 18 1 1 20 10.1186/s41239-021-00269-8
  21. Hwang, A.H.C., Won, A.S.: AI in your mind: Counterbalancing perceived agency and experience in Human-AI interaction. In: CHI Conference on Human Factors in Computing Systems Extended Abstracts, pp. 1–10. ACM, New York (2022).https://doi.org/10.1145/3491101.3519833
  22. Lin, C.J., Mubarok, H.: Learning analytics for investigating the mind map-guided AI chatbot approach in an EFL flipped speaking classroom. Educ. Technol. Soc. 24(4), 16–35 (2021). https://www.jstor.org/stable/48629242
  23. Koć-Januchta MM Schönborn KJ Tibell LA Chaudhri VK Heller HC Engaging with biology by asking questions: investigating students’ interaction and learning with an artificial intelligence-enriched textbook J. Educ. Comput. Res. 2020 58 6 1190 1224 10.1177/0735633120921581
  24. Liu, R., et al.: From knowledge map to mind map: artificial imagination. In: 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), pp. 496–501. IEEE, San Jose (2019). https://doi.org/10.1109/MIPR.2019.00100
  25. Ivanova, S., Dimitrov, L., Ivanov, V., Urum, G., Olefir, O.: Mind maps for key points of a reverse engineering project. In: International Conference “New Technologies, Development and Applications”, pp. 170–181. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-31066-9_18
  26. Chen, X., Xie, H., Zou, D., Wang, F.L.: ChatGPT for generating stories and mind-maps in storytelling. In: 2023 10th International Conference on Behavioural and Social Computing (BESC), Larnaca, Cyprus, pp. 1–8. IEEE, Larnaca (2023). https://doi.org/10.1109/BESC59560.2023.10386441
  27. Murugesan S Cherukuri AK The rise of generative artificial intelligence and its impact on education: the promises and perils Computer 2023 56 5 116 121 2023Compr.56E.116M 10.1109/MC.2023.1234567
  28. Tachibana, M., Shimizu, T., Tomiura, Y.: Generating surprising and diverse ideas using ChatGPT. In: International Conference on Asian Digital Libraries. Springer, Singapore, pp. 222−228 (2025). https://doi.org/10.1007/978-981-96-0865-2_18
  29. Busuttil, L., Calleja, J.: Teachers’ beliefs and practices about the potential of ChatGPT in teaching mathematics in secondary schools. Digital Experiences Math. Educ., 1–27 (2025). https://doi.org/10.1007/s40751-024-00168-3
  30. Chaka, C.: Generative AI chatbots - ChatGPT versus YouChat versus Chatsonic: use cases of selected areas of applied English language studies. Int. J. Learn., Teach. Educ. Res. 22(6), 1–19 (2023). https://doi.org/10.26803/ijlter.22.6.1
  31. Karaivanov, D.P., Troha, S.: Optimal selection of the structural scheme of compound two-carrier planetary gear trains and their parameters. In: Recent Advances in Gearing: Scientific Theory and Applications, pp. 339–403. Springer International, Cham (2021). https://doi.org/10.1007/978-3-030-64638-7\_8
  32. Ivanov, V., Dimitrov, L., Ivanova, S., Urum, G.: Industry 4.0 approaches to the standardization of spur bevel gears. In: International Conference “New Technologies, Development and Applications”, pp. 443–451. Springer Nature Switzerland, Cham (2024). https://doi.org/10.1007/978-3-031-66268-3\_45
  33. Nitchot A Gilbert L Comparison of Mytelemap and MindMeister in using competence maps for self-learning Technol. Pedagog. Educ. 2025 34 1 69 89 10.1080/1475939X.2024.2394677
  34. Andrae, S.: Critical thinking in the age of algorithms. In: Fostering Teacher Skills and Critical Thinking in Modern Education, pp. 221–258. IGI Global Scientific Publishing (2025). https://doi.org/10.4018/979-8-3373-1692-5.ch010
  35. Abdullah, I.H., Wahyudi, D., Tonra, W.S., Hasbi, M.: Development of digital teaching materials based on differentiated learning using Canva for mathematics subjects. EduMatSains: Jurnal Pendidikan, Matematika dan Sains 9(2), 244–255 (2025)
  36. Novak, J.D., Cañas, A.J.: The theory underlying concept maps and how to construct and use them. Technical Report IHMC CmapTools 2006–01 Rev 01–2008, 1−36 (2008)
  37. Schroeder NL Nesbit JC Anguiano CJ Adesope OO Studying and constructing concept maps: a meta-analysis Educ. Psychol. Rev. 2018 30 2 431 455 10.1007/s10648-017-9403-9
  38. Chiu, M.‑C., Hwang, G.‑J.: Enhancing student creative and critical thinking in generative AI‑empowered creation: a mind‑mapping approach. Interact. Learn. Environ. (2025). https://doi.org/10.1080/10494820.2025.2511244
  39. Kim, S.S.Y., Liao, Q.V., Vorvoreanu, M., Ballard, S., Vaughan, J.W.: “I’m Not Sure, But…”: examining the impact of large language models’ uncertainty expression on user reliance and trust. In: Proceedings of FAccT 2024, pp. 1–14 (2024). https://doi.org/10.48550/arXiv.2405.00623

Issue

Lecture Notes in Mechanical Engineering, pp. 585-599, 2026, Albania, https://doi.org/10.1007/978-3-032-14926-8_48

Вид: книга/глава(и) от книга, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus