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Exploring the Potential of Cognitive Flexibility and Elaboration in Support of Curiosity, Interest, and Engagement in Designing AI-Rich Learning Spaces, Extensible to Urban Environments

  • Conference paper
  • First Online:
Distributed, Ambient and Pervasive Interactions (HCII 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14719))

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Abstract

The aim of this paper is to explore cognitive flexibility and elaborative interrogation in relation to AI (artificial intelligence) chatbots in terms of the potential to support the curiosity, interest, and engagement (CIE) dynamic in urban learning environments. AI chatbots such as ChatGPT by OpenAI appear to be improving in conversational and other capabilities and this paper explores such advances using version 4. Based on a review of the research literature, a conceptual framework is formulated for cognitive flexibility and elaborative interrogation in support of curiosity, interest, and engagement in AI-rich urban learning environments. The framework is then operationalized for use in this paper in an effort to explore the potential of cognitive flexibility and elaborative interrogation in support of curiosity, interest, and engagement as an approach to the application and use of AI chatbots in the designing of urban learning spaces and services. This paper extends earlier foundational work on cognitive flexibility and AI chatbots, cognitive flexibility in support of AI chatbots in urban civic spaces, and the ethical and responsible use of AI chatbots to support teaching and learning.

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References

  1. Arnone, M.P., Small, R.V., Chauncey, S.A., McKenna, H.P.: Curiosity, interest and engagement in technology-pervasive learning environments: a new research agenda. Educ. Technol. Res. Dev. 59(2), 181–198 (2011). https://doi.org/10.1007/s11423-011-9190-9

    Article  Google Scholar 

  2. Marr, B.: What is GPT-3 and why is it revolutionizing artificial intelligence? BM Blog (2023). https://bernardmarr.com/what-is-gpt-3-and-why-is-it-revolutionizing-artificial-intelligence/#:~:text=Starting%20with%20the%20very%20basics,to%20carry%20out%20their%20task. Accessed 1 Mar 2023

  3. Roth, E.: Meet the companies trying to keep up with ChatGPT / From Google’s Bard to Microsoft’s new Bing, here are all the major contenders in the AI chatbot space. TheVerge (2023). https://www.theverge.com/2023/3/5/23599209/companies-keep-up-chatgpt-ai-chatbots. Accessed 7 Mar 2023

  4. Ghaffray, S.: Silicon Valley’s AI frenzy isn’t just another crypto craze: It isn’t theoretical. Millions of people are already using apps like ChatGPT to write books, create art, and develop code. Vox (2023). https://www.vox.com/technology/2023/3/6/23624015/silicon-valley-generative-ai-chat-gpt-crypto-hype-trend. Accessed 7 Mar 2023

  5. Hamilton, R.: Elaboration effects on learning. In: Seel, N.M. (eds.) Encyclopedia of the Sciences of Learning. Springer, Boston (2012). https://doi.org/10.1007/978-1-4419-1428-6_170

  6. Farooq, O., Maher, M.: Synthesis and generativity: elaborative interrogation prompts for graduate information literacy instruction. J. Acad. Librariansh. 47(5), 102398 (2021). https://doi.org/10.1016/j.acalib.2021.102398

    Article  Google Scholar 

  7. Learning Scientists Digest. Digest #145: Elaborative Interrogation. The Learning Scientists Blog (2020). https://www.learningscientists.org/blog/2020/7/3/digest-145-1. Accessed 19 Nov 2023

  8. Minigan, A.P.: The importance of curiosity and questions in 21st-century learning. Educ. Week 36(32) (2017). https://www.edweek.org/teaching-learning/opinion-the-importance-of-curiosity-and-questions-in-21st-century-learning/2017/05

  9. Dunlosky, J., Rawson, K.A., Marsh, E.J., Nathan, M.J., Willingham, D.T.: Improving students’ learning with effective learning techniques: promising directions from cognitive and educational psychology. Psychol. Sci. Public Interest 14, 4–58 (2013). https://doi.org/10.1177/1529100612453266

    Article  Google Scholar 

  10. Lang, J.M.: Small changes in teaching: Making connections. The Chronicle of Higher Education (2016). https://www.chronicle.com/article/small-changes-in-teaching-making-connections/?sra=true

  11. Farooq, O.: The effect of elaborative interrogation on the synthesis of ideas from multiple sources of information. Open Inf. Sci. 3(1), 76–87 (2019). https://doi.org/10.1515/opis-2019-0006

    Article  Google Scholar 

  12. National Academies of Sciences, Engineering, and Medicine. How People Learn II: Learners, Contexts, and Cultures. Washington, DC: The National Academies Press (2018). https://doi.org/10.17226/24783. https://nap.nationalacademies.org/read/24783/chapter/7

  13. Loewenstein, G.: The psychology of curiosity: a review and reinterpretation. Psychol. Bull. 116(1), 75–98 (1994). https://doi.org/10.1037/0033-2909.116.1.75

    Article  Google Scholar 

  14. OpenAI. Introducing GPTs. OpenAI Blog (2023). https://openai.com/blog/introducing-gpts. Accessed 19 Nov 2023

  15. Hudson, E.: A proposed AI strategy for 2024: Agency, not agents. Or, what inquiry-based learning can teach us about how to approach AI. Learning on Purpose Blog (2023). https://erichudson.substack.com/p/a-proposed-ai-strategy-for-2024-agency?utm_source=profile&utm_medium=reader2. Accessed 19 Nov 2023

  16. Creamer, E.: ‘Hallucinate’ chosen as Cambridge dictionary word of the year. The Guardian (2023). https://www.theguardian.com/books/2023/nov/15/hallucinate-cambridge-dictionary-word-of-the-year. Accessed 25 Nov 2023

  17. Cambridge Dictionary: Hallucinate (2023). https://dictionary.cambridge.org/dictionary/english/hallucinate. Accessed 25 Nov 2023

  18. Kayed, S., Ghoz, L., Elbehairy, F., Ghonim, A., Hendawy, M.: Setting an agenda for urban AI adaptivity in urban planning and architecture e-learning. J. Eng. Res. 6(4), 88–96 (2022). https://doi.org/10.21608/erjeng.2022.265385

    Article  Google Scholar 

  19. Burry, M.: A new agenda for AI-based urban design and planning. In: As, I., Basu, P., Talwar, P. (eds.) Artificial Intelligence in Urban Planning and Design: Technologies, Implementation, and Impacts, pp. 3–20. Elsevier (2022). https://doi.org/10.1016/B978-0-12-823941-4.00005-6

  20. Cugurullo, F., Caprotti, F., Cook, M., Karvonen, A., McGuirk, P., Marvin, S.: The rise of AI urbanism in post-smart cities: a critical commentary on urban artificial intelligence. Urban Stud (2023). https://doi.org/10.1177/00420980231203386

  21. Aciang, I-S., Hwang, G-J., Chen, C-H.: Decision-guided chatbots and cognitive styles in interdisciplinary learning. Comput. Educ., 104812 (2023). https://doi.org/10.1016/j.compedu.2023.104812

  22. Shneiderman, B.: Human-Centered AI. Oxford University Press, Oxford (2022)

    Book  Google Scholar 

  23. Jones, W.: AI doesn't have to be this way > MIT economist sounds warning against unregulated tech innovation. IEEE Spect. (2023). https://spectrum.ieee.org/ai-skeptics. Accessed 23 Mar 2023

  24. Dalgali, A.: Framing, Emotions, Salience: The Future of Artificial Intelligence as Seen by Redditors. Doctoral Dissertation, Syracuse University (2023)

    Google Scholar 

  25. Johnson, S.: The glass box and the commonplace book. SearchMedium Blog (2010). https://stevenberlinjohnson.com/the-glass-box-and-the-commonplace-book-639b16c4f3bb. Accessed 22 Mar 2023

  26. Wiggers, K.: OpenAI connects ChatGPT to the Internet. TechCrunch (2023). https://techcrunch.com/2023/03/23/openai-connects-chatgpt-to-the-internet/. Accessed 23 Mar 2023

  27. Hoffman R.: Impromptu: Amplifying our humanity through ai. Dallepedia LLC (2023). https://public.ebookcentral.proquest.com/choice/PublicFullRecord.aspx?p=7214737. Accessed 14 May 2023

  28. Engelbart, D.C.: Augmenting human intellect: A conceptual framework. AFOSR-3233 Summary Report. Director of Information Sciences, Air Force Office of Scientific Research, Washington 25, DC, USA (1962). http://csis.pace.edu/~marchese/CS835/Lec3/DougEnglebart.pdf. Accessed 13 May 2023

  29. Kutar, M., Fletcher, G.: We asked ChatGPT to write a company HR policy - and the results were promising. The Conversation (2023). https://theconversation.com/we-asked-chatgpt-to-write-a-company-hr-policy-and-the-results-were-promising-207072. Accessed 27 Sept 2023

  30. Olenick, M., Zemsky, P.: Can GenAI do strategy? Harvard Business Review (2023). https://hbr.org/2023/11/can-genai-do-strategy. Accessed 25 Nov 2023

  31. Allchin, D.: Hooks, lines, & sinkers. Am. Biol. Teach. 77(9), 718–720 (2015). https://doi.org/10.1525/abt.2015.77.9.14

    Article  Google Scholar 

  32. Barkley, E.F., Major, C.H.: 7 ways to use “The Hook” to grab students’ attention. In: Barkley, E.F., Major, C.H. (eds.) The Wiley Network. Excerpted and adapted from Interactive Lecturing: A Handbook for College Faculty. John Wiley & Sons, Hoboken (2018). https://www.wiley.com/en-us/network/education/instructors/teaching-strategies/7-ways-to-use-the-hook-to-grab-students-attention. Accessed 13 Dec 2023

  33. Smith, K.: Stimulating curiosity using hooks. Noba Blog (2017). https://nobaproject.com/blog/2017-06-07-stimulating-curiosity-using-hooks. Accessed 13 Dec 2023

  34. Radil, A.I., Goegan, L.D., Daniels, L.M.: Teachers’ authentic strategies to support student motivation. Front. Educ. 8, 1040996 (2023). https://doi.org/10.3389/feduc.2023.1040996

    Article  Google Scholar 

  35. Valerio, K.: Intrinsic motivation in the classroom. J. Stud. Engag. Educ. Matt. 2(1), 30–35 (2012). https://ro.uow.edu.au/jseem/vol2/iss1/6

  36. Adamma, O.N., Ekwutosim, O.P., Unamba, E.C.: Influence of extrinsic and intrinsic motivation on pupils academic performance in mathematics. SJME (Supremum J. Math. Educ.) 2(2), 52–59 (2018). https://doi.org/10.5281/zenodo.1405857

    Article  Google Scholar 

  37. Deci, E.L., Ryan, R.M.: Intrinsic motivation and self-determination in human behavior. Springer, Heidelberg (1985). https://doi.org/10.1007/978-1-4899-2271-7

  38. Baranek, L.K.: The effect of rewards and motivation on student achievement (Masters Theses, 285, Grand Valley State University) (1996). https://scholarworks.gvsu.edu/theses/285. Accessed 22 Nov 2023

  39. Ilegbusi, M.I.: An analysis of the role of rewards and punishment in motivating school learning. Comput. Inf. Syst. Dev. Inf. 4(1), 35–38 (2013). https://core.ac.uk/download/pdf/234697251.pdf

  40. Kusumawati, M.D., Fauziddin, M., Ananda, R.: The impact of reward and punishment on the extrinsic motivation of elementary school students. AL-ISHLAH: Jurnal Pendidikan 15(1), 183–192 (2023). https://journal.staihubbulwathan.id/index.php/alishlah/article/view/2856

  41. Cameron, J., Pierce, W.D.: Reinforcement, reward, and intrinsic motivation: a meta-analysis. Rev. Educ. Res. 64(3), 363–423 (1994). https://doi.org/10.2307/1170677

    Article  Google Scholar 

  42. Calvo, R.A., Peters, D., Vold, K., Ryan, R.M.: Supporting human autonomy in ai systems: a framework for ethical enquiry. In: Burr, C., Floridi, L. (eds.) Ethics of Digital Well-Being. PSS, vol. 140, pp. 31–54. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50585-1_2

    Chapter  Google Scholar 

  43. Silitonga, L.M., et al.: The impact of AI chatbot-based learning on students’ motivation in english writing classroom. In: Huang, YM., Rocha, T. (eds.) ICITL 2023. LNCS, vol. 14099. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-40113-8_53

  44. Chiu, T.K., Moorhouse, B.L., Chai, C.S., Ismailov, M.: Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interact. Learn. Environ. 1–17 (2023). https://doi.org/10.1080/10494820.2023.2172044

  45. Ransbotham, S., Kiron, D., Candelon, F., Khodabandeh, S., Chu, M.: Achieving individual—and organizational—value with AI. MIT Sloan Management Review (2022). https://sloanreview.mit.edu/projects/achieving-individual-and-organizational-value-with-ai/

  46. Labadze, L., Grigolia, M., Machaidze, L.: Role of AI chatbots in education: Systematic literature review. Int. J. Educ. Technol. High. Educ. 20(1), 56 (2023). https://doi.org/10.1186/s41239-023-00426-1

    Article  Google Scholar 

  47. Weinstein, C.E.: Cognitive Elaboration Learning Strategies. ED144953. Austin: Texas University, Dept. of Educational Technology (1977). https://eric.ed.gov/?id=ED144953. Accessed 24 Nov 2023

  48. Elen, J., Stahl, E., Bromme, R., Clarabout, G.: Links Between Beliefs and Cognitive Flexibility: Lessons Learned. Springer (2011). https://doi.org/10.1007/978-94-007-1793-0

    Article  Google Scholar 

  49. Darling-Hammond, L., et al.: Powerful Learning: What We Know About Teaching for Learning. Jossey-Bass, San Francisco (2008)

    Google Scholar 

  50. Smith, M., Weinstein, Y.: Learn how to study using … elaboration: For students, for researchers, for teachers, learning scientists posts. The Learning Scientists Blog (2016). https://www.learningscientists.org/blog/2016/7/7-1. Accessed 8 Oct 2023

  51. National Council of Social Studies. Silver Spring, Md (2023). https://www.socialstudies.org/media-information/definition-social-studies-nov2023

  52. Zeitlhofer, I., Hörmann, S., Mann, B., Hallinger, K., Zumbach, J.: Effects of cognitive and metacognitive prompts on learning performance in digital learning environments. Knowledge 3(2), 277–292 (2023). https://www.mdpi.com/2673-9585/3/2/19

  53. Hofhues, S.: Inquiry-based learning with digital media. In: Mieg, H.A. (eds.) Inquiry-Based Learning – Undergraduate Research. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14223-0_35

  54. Murphy, V.L., Coiro, J., Kiili, C.: Exploring patterns in student dialogue while using a digital platform designed to support online inquiry. J. Interact. Media Educ. 1 (2019). https://doi.org/10.5334/jime.518

  55. Google Custom Search. Examples (2021). https://sites.google.com/view/createcustomsearch/examples. Accessed 28 Sept 2023

  56. Kidtopia. Search for kids (2023). https://kidtopia.info/. Accessed 29 Sept 2023

  57. Kids Search. Kid’s search engine (2023). https://kidssearch.com. Accessed 29 Sept 2023

  58. FCC. Children’s Internet Protection Act (CIPA). Federal Communications Commission (2019). https://www.fcc.gov/consumers/guides/childrens-internet-protection-act. Accessed 29 Sept 2023

  59. Markey, E.J., Cassidy, W.M.: Fact Sheet – COPPA 2.0: Children and Teens’ Online Privacy Protection Act: Legislation to Strengthen Protections for Minors Online (2022). https://www.commonsensemedia.org/sites/default/files/featured-content/files/coppa_2.0_one_pager_2021.pdf. Accessed 29 Sept 2023

  60. Frechtling, D.: Will the U.S. update laws for children’s digital privacy? Forbes Technology Council. Forbes (2023). https://www.forbes.com/sites/forbestechcouncil/2023/03/07/will-the-us-update-laws-for-childrens-digital-privacy/?sh=1e561d233f17. Accessed 29 Sept 2023

  61. EdLaw 2D. Unauthorized release of personally identifiable information. In Consolidated Laws of New York, New York State Senate, Chapter 16 (2015). https://www.nysenate.gov/legislation/laws/EDN/2-D. Accessed 29 Sept 2023

  62. Holmes, W., Porayska-Pomsta, K. (eds.): The Ethics of Artificial Intelligence in education: Practices, challenges, and debates. Taylor & Francis (2022). https://www.google.com/books/edition/The_Ethics_of_Artificial_Intelligence_in/bqh2EAAAQBAJ?hl=en&gbpv=1. Accessed 29 Sept 2023

  63. DW. EU lawmakers lay groundwork for ‘historic’ AI regulation. Deutsche Wells (DW) (2023). https://www.dw.com/en/eu-lawmakers-lay-groundwork-for-historic-ai-regulation/a-65909881. Accessed 29 Sept 2023

  64. Chauncey, S.A., McKenna, H.P.: A framework and exemplars for ethical and responsible use of AI Chatbot technology to support teaching and learning. Comput. Educ. Artif. Intell. 5, 100182 (2023). https://doi.org/10.1016/j.caeai.2023.100182

    Article  Google Scholar 

  65. Hannum, E.: What authors know about the power of words. The Atlantic (2023). https://www.theatlantic.com/books/archive/2023/05/the-books-briefing-han-kang-ngugi-wa-thiongo/673938/. Accessed 27 Sept 2023

  66. Rosenshine, B., Meister, C., Chapman, S.: Teaching students to generate questions: a review of the intervention studies. Rev. Educ. Res. 66(2), 181–221 (1996). https://doi.org/10.3102/00346543066002181

    Article  Google Scholar 

  67. Graesser, A.C., Person, N.K.: Question asking during tutoring. Am. Educ. Res. J. 31(1), 104–137 (1994). https://doi.org/10.3102/00028312031001104

    Article  Google Scholar 

  68. Mollick, E.: The future of education in a world of AI: A positive vision for the transformation to come. One Useful Thing (2023). https://www.oneusefulthing.org/p/the-future-of-education-in-a-world. Accessed 29 Sept 2023

  69. Mollick, E.: Setting time on fire and the temptation of the button. One Useful Thing (2023). https://www.oneusefulthing.org/p/setting-time-on-fire-and-the-temptation. Accessed 29 Sept 2023

  70. Jong, T.: Cognitive load theory, educational research, and instructional design: some food for thought. Instr. Sci. 38, 105–134 (2010). https://doi.org/10.1007/S11251-009-9110-0

    Article  Google Scholar 

  71. Moos, D., Pitton, D.: Student teacher challenges: using the cognitive load theory as an explanatory lens. Teach. Educ. 25, 127–141 (2014). https://doi.org/10.1080/10476210.2012.754869

    Article  Google Scholar 

  72. Seufert, T.: Building bridges between self-regulation and cognitive load—an invitation for a broad and differentiated attempt. Educ. Psychol. Rev. 32, 1151–1162 (2020). https://doi.org/10.1007/s10648-020-09574-6

    Article  Google Scholar 

  73. Chauncey, S.A., McKenna, H.P.: An exploration of the potential of large language models to enable cognitive flexibility in AI-augmented learning environments. In: Arai, K. (ed.) Proceedings of the Future Technologies Conference (FTC) 2023, Volume 4. FTC 2023. Lecture Notes in Networks and Systems, vol. 816. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-47448-4_11

  74. Holstein, K., Aleven, V.: Designing for human-AI complementarity in K-12 education. AI Maga. 43, 239–248 (2021). https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/7399

  75. Lai, Y., Kankanhalli, A., Ong, D.: Human-AI collaboration in healthcare: a review and research agenda. In: Hawaii International Conference on System Sciences (2021). https://aisel.aisnet.org/hicss-54/cl/machines_as_teammates/5/

  76. Tong, J.R., Lee, T.X.: Trustworthy AI that engages humans as partners in teaching and learning. Computer 56, 62–73 (2023). https://ieeexplore.ieee.org/abstract/document/10109264

  77. Dellermann, D., Calma, A., Lipusch, N., Weber, T., Weigel, S., Ebel, P. A.: The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems. In: Hawaii International Conference on System Sciences (2019). https://arxiv.org/abs/2105.03354

  78. Thompson, N.: Dialogues: On AI, Society, and What Comes Next. Atlantic Re:think. The Atlantic (2023). https://cdn.theatlantic.com/assets/marketing/prod/misc-files/2023/12/AtlanticRethink_Google_Dialogues_2023-mobile.pdf. Accessed 6 Dec 2023

  79. McKenna, H.P.: Urban life and the ambient in smart cities, learning cities, and future cities. IGI Global (2023). https://doi.org/10.4018/978-1-6684-4096-4

  80. Chauncey, S.A., Simpson, G.I.: The role of learning city “smart teams” in promoting, supporting, and extending the community school model. In: Stephanidis, C. (ed.) HCII 2020. LNCS, vol. 12425, pp. 326–344. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-60128-7_25

    Chapter  Google Scholar 

  81. McKenna, H.P., Chauncey, S.A.: Taking learning to the city: an exploration of the frictionless learning environment innovation. In: EDULEARN14 Proceedings, pp. 6324–6334 (2014). https://library.iated.org/view/MCKENNA2014TAK

  82. Knemeyer, D., Follett, J.: AI as design material: Seeing the design role in creating AI-driven products. Towards Data Science blog (2020). https://towardsdatascience.com/ai-as-design-material-2748d84bbb7b. Accessed 29 Sept 2023

  83. Feldstein, M.: ChatGPT: Post-ASU+GSV reflections on generative AI. eLiterate blog (2023). https://eliterate.us/chatgpt-post-asugsv-reflections-on-generative-ai/. Accessed 29 Sept 2023

  84. Cardona, M.A., Rodríguez, R.J., Ishmael, K.: Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations (2023). https://www2.ed.gov/documents/ai-report/ai-report.pdf

  85. Parrish, S.: Writing to Think. FS (Farnam Street) Blog (2023). https://fs.blog/writing-to-think/. Accessed 25 Nov 2023

  86. Jabareen, Y.: Building a conceptual framework: philosophy, definitions, and procedure. Int. J. Qual. Methods 8(4), 49–62 (2009). https://doi.org/10.1177/160940690900800406

    Article  Google Scholar 

  87. Ryan, R.M., Deci, E.L.: Intrinsic and extrinsic motivation from a self-determination theory perspective: definitions, theory, practices, and future directions. Contemp. Educ. Psychol. 61, 101860 (2020). https://doi.org/10.1016/j.cedpsych.2020.101860

    Article  Google Scholar 

  88. Bandura, A.: Social cognitive theory: an agentic perspective. Annu. Rev. Psychol. 52(1), 1–26 (2001). https://doi.org/10.1111/1467-839X.00024

    Article  MathSciNet  Google Scholar 

  89. Melaville, A., Berg, A.C., Blank, M.J.: Community-Based Learning: Engaging Students for Success and Citizenship. Coalition for Community Schools, Washington, DC (2006). https://eric.ed.gov/?id=ED490980

  90. Utilities One. Revolutionizing Citizen Engagement Communication Solutions for Inclusive Cities (2023). https://utilitiesone.com/revolutionizing-citizen-engagement-communication-solutions-for-inclusive-cities. Accessed 20 Nov 2023

  91. Cassada, K.: Lack of policy regarding generative AI use in school’s places students at risk. Forbes (2023). https://www.forbes.com/sites/katecassada-1/2023/09/17/lack-of-policy-regarding-generative-ai-use-in-schools-places-students-at-risk/. Accessed 17 Dec 2023

  92. Office of Educational Technology. Artificial Intelligence. US Department of Education (2023). https://tech.ed.gov/ai/. Accessed 17 Dec 2023

  93. Buck, D.: AI is a serious threat to student privacy. Thomas B. Fordham Institute (2023). https://fordhaminstitute.org/national/commentary/ai-serious-threat-student-privacy. Accessed 17 Dec 2023

  94. Jennings, J.: AI in education: Privacy and security. eSpark Learning (2023). https://www.esparklearning.com/blog/ai-in-education-privacy-and-security/. Accessed 17 Dec 2023

  95. Chilcote Bacco, L.: Why educators should lean in to AI to better support students. EdSurge (2023). https://www.edsurge.com/news/2023-10-02-why-educators-should-lean-in-to-ai-to-better-support-students. Accessed 17 Dec 2023

  96. Bailey, J.: AI in education: The leap into a new era of machine intelligence carries risks and challenges, but also plenty of promise. Educ. Next 23(4), 28–35 (2023). https://www.educationnext.org/a-i-in-education-leap-into-new-era-machine-intelligence-carries-risks-challenges-promises/. Accessed 17 Dec 2023

  97. AVID Open Access. AI as a student’s personal tutor: Discover how AI can be leveraged as a personal tutor for every student (2023). https://avidopenaccess.org/resource/ai-as-a-students-personal-tutor/. Accessed 17 Dec 2023

  98. Krause, B., Jones, W.: How to enact an AI policy in your K-12 schools. EdTech: Focus on K-12 (2023). https://edtechmagazine.com/k12/article/2023/07/how-enact-ai-policy-your-k-12-schools. Accessed 17 Dec 2023

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Author information

Authors and Affiliations

  1. Northville Central School District, Northville, NY, 12134, USA

    Sarah A. Chauncey

  2. AmbientEase, Victoria, BC, V8V 4Y9, Canada

    H. Patricia McKenna

Authors
  1. Sarah A. Chauncey
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  2. H. Patricia McKenna
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Editor information

Editors and Affiliations

  1. Smart Future Initiative, Frankfurt am Main, Germany

    Norbert A. Streitz

  2. Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

Appendices

Appendix A- Iterative Prompting in Support of Elaborative Interrogation - https://docs.google.com/document/d/1sMkA-C9FC56sIwdRDaQEP3J_fOnxNPpqyH-LNuGRS5s/edit

Beginning with the Prompt, “What is rewilding in urban settings?” we followed a selection of related prompts and noted additional prompts suggested by Perplexity, ChatGPT-4, and Claude. These prompts were submitted in November 2023.

Appendix B - Iterative Prompting for Urban Rewilding Using ChatGPT-4 - https://docs.google.com/document/d/1qOXu0lJLAWyQxJ341d6VPoFyK2SVrsTZbEUSzQgN70Y/edit

Using ChatGPT-4 we posed an initial prompt and asked ChatGPT to engage in elaborative interrogation - creating prompts that address rewilding in urban settings, to respond to the prompts, and then to iterate this process a second time. This was significant as ChatGPT was engaged as both the prompter and responder. These prompts were submitted in November 2023.

Appendix C - ChatGPT Create Playground

Using the ChatGPT Create Playground,—https://chat.openai.com/gpts/editor - we created three GPTs and then used them with example Prompts. These ChatGPTs were created and tested in November 2023 and the links will work only for those who have a ChatGPT-4 paid account.

Appendix D - AI-Human Collaboration in Support of Urban Development - https://docs.google.com/document/d/17BEp7yd32VrvCz-LWeuEHs2XHpxnMY066fvwKILf8os/edit

Prompts for this exemplar were submitted to ChatGPT-4 https://chat.openai.com/, Claude https://claude.ai, and BARD https://bard.google.com/. A Table of Contents is included below the prompts. These prompts were submitted in December 2023.

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Chauncey, S.A., McKenna, H.P. (2024). Exploring the Potential of Cognitive Flexibility and Elaboration in Support of Curiosity, Interest, and Engagement in Designing AI-Rich Learning Spaces, Extensible to Urban Environments. In: Streitz, N.A., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. HCII 2024. Lecture Notes in Computer Science, vol 14719. Springer, Cham. https://doi.org/10.1007/978-3-031-60012-8_13

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