Ali, I., Warraich, N. F., & Butt, K. (2025). Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction. Information Development, 41(3), 859–874. https://doi.org/10.1177/02666669241257206
Anderson, J. R. (2014). Rules of the Mind. Psychology Press. https://doi.org/10.4324/9781315806938
Belle, V. (2023). Knowledge representation and acquisition for ethical AI: challenges and opportunities. Ethics and Information Technology, 25(1), 22. https://doi.org/10.1007/s10676-023-09692-z
Bereiter, C., & Scardamalia, M. (2014). Knowledge Building and Knowledge Creation: One Concept, Two Hills to Climb. In S. C. Tan, H. J. So, & J. Yeo (Eds.), Knowledge Creation in Education (pp. 35–52). Springer Singapore. https://doi.org/10.1007/978-981-287-047-6_3
Bibi, A., Yamin, S., Natividad, L. R., Rafique, T., Akhter, D. N., Fernandez, S. F., & Samad, A. (2024). Navigating The Ethical Landscape: Ai Integration In Education. Educational Administration: Theory and Practice, 30(6), 1579–1585. https://doi.org/10.53555/kuey.v30i6.5546
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993–1022. https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf
Boyd, D., & Crawford, K. (2012). Critical Questions for Big Data. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878
Cantú-Ortiz, F. J., Galeano Sánchez, N., Garrido, L., Terashima-Marin, H., & Brena, R. F. (2020). An artificial intelligence educational strategy for the digital transformation. International Journal on Interactive Design and Manufacturing (IJIDeM), 14(4), 1195–1209. https://doi.org/10.1007/s12008-020-00702-8
Cheng, X., Yan, X., Lan, Y., & Guo, J. (2014). BTM: Topic Modeling over Short Texts. IEEE Transactions on Knowledge and Data Engineering, 26(12), 2928–2941. https://doi.org/10.1109/TKDE.2014.2313872
Clark, A., & Chalmers, D. (1998). The Extended Mind. Analysis, 58(1), 7–19. https://doi.org/10.1093/analys/58.1.7
Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732
Dabis, A., & Csáki, C. (2024). AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanities and Social Sciences Communications, 11(1), 1006. https://doi.org/10.1057/s41599-024-03526-z
Dai, Y., Lin, Z., Liu, A., & Wang, W. (2024). An embodied, analogical and disruptive approach of AI pedagogy in upper elementary education: An experimental study. British Journal of Educational Technology, 55(1), 417–434. https://doi.org/10.1111/bjet.13371
Dawson, M. G., Deer, R., & Boguslawski, S. (2025). Cognitive dissonance in programming education: A qualitative exploration of the impact of generative AI on application-directed learning. Computers in Human Behavior Reports, 19, 100724. https://doi.org/10.1016/j.chbr.2025.100724
Dieterle, E., Dede, C., & Walker, M. (2024). The cyclical ethical effects of using artificial intelligence in education. AI & Society, 39(2), 633–643. https://doi.org/10.1007/s00146-022-01497-w
Dixon-Román, E., Nichols, T. P., & Nyame-Mensah, A. (2020). The racializing forces of/in AI educational technologies. Learning, Media and Technology, 45(3), 236–250. https://doi.org/10.1080/17439884.2020.1667825
Dogruel, L., Facciorusso, D., & Stark, B. (2022). ‘I’m still the master of the machine.’ Internet users’ awareness of algorithmic decision-making and their perception of its effect on their autonomy. Information, Communication & Society, 25(9), 1311–1332. https://doi.org/10.1080/1369118X.2020.1863999
Du, H., Sun, Y., Jiang, H., Islam, A. Y. M. A., & Gu, X. (2024). Exploring the effects of AI literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11(1), 559. https://doi.org/10.1057/s41599-024-03101-6
Edwards, B. I., Olugbade, D., & Ojo, O. A. (2024). Facilitating Cognitive Load Management and Improved Learning Outcomes and Attitudes in Middle School Technology and Vocational Education Through AI Chatbot. Journal of Technical Education and Training, 16(3), 114–131. https://doi.org/10.30880/jtet.2024.16.03.009
Feenberg, A. (2012). Questioning Technology. Routledge. https://doi.org/10.4324/9780203022313
Feldman-Maggor, Y., Cukurova, M., Kent, C., & Alexandron, G. (2025). The Impact of Explainable AI on Teachers’ Trust and Acceptance of AI EdTech Recommendations: The Power of Domain-specific Explanations. International Journal of Artificial Intelligence in Education, 35(5), 2889–2922. https://doi.org/10.1007/s40593-025-00486-6
Ferrario, A., Loi, M., & Viganò, E. (2020). In AI We Trust Incrementally: a Multi-layer Model of Trust to Analyze Human-Artificial Intelligence Interactions. Philosophy & Technology, 33(3), 523–539. https://doi.org/10.1007/s13347-019-00378-3
Fiok, K., Farahani, F. V., Karwowski, W., & Ahram, T. (2022). Explainable artificial intelligence for education and training. The Journal of Defense Modeling and Simulation, 19(2), 133–144. https://doi.org/10.1177/15485129211028651
Fortunati, L., Edwards, A., Ye, W., Manganelli, A. M., Edwards, C., Caballero, S., Mukhongo, L., et al. (2025). Making Sense of the Role of ChatGPT in Education: An Examination of Student Views in China, Italy, Kenya, Uruguay, and the U.S. Human-Machine Communication, 11, 81–105. https://doi.org/10.30658/hmc.11.5
Fütterer, T., Fischer, C., Alekseeva, A., Chen, X., Tate, T., Warschauer, M., & Gerjets, P. (2023). ChatGPT in education: global reactions to AI innovations. Scientific Reports, 13(1), 15310. https://doi.org/10.1038/s41598-023-42227-6
Genus, A., & Stirling, A. (2018). Collingridge and the dilemma of control: Towards responsible and accountable innovation. Research Policy, 47(1), 61–69. https://doi.org/10.1016/j.respol.2017.09.012
Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006
Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A Human–Machine Communication research agenda. New Media & Society, 22(1), 70–86. https://doi.org/10.1177/1461444819858691
Hassija, V., Chamola, V., Mahapatra, A., Singal, A., Goel, D., Huang, K., Scardapane, S., et al. (2024). Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence. Cognitive Computation, 16(1), 45–74. https://doi.org/10.1007/s12559-023-10179-8
Hazaimeh, M., & Al-Ansi, A. M. (2024). Model of AI acceptance in higher education: arguing teaching staff and students perspectives. International Journal of Information and Learning Technology, 41(4), 371–393. https://doi.org/10.1108/ijilt-01-2024-0005
Heersmink, R. (2015). Dimensions of integration in embedded and extended cognitive systems. Phenomenology and the Cognitive Sciences, 14(3), 577–598. https://doi.org/10.1007/s11097-014-9355-1
Hirvonen, N., Jylhä, V., Lao, Y., & Larsson, S. (2024). Artificial intelligence in the information ecosystem: Affordances for everyday information seeking. Journal of the Association for Information Science and Technology, 75(10), 1152–1165. https://doi.org/10.1002/asi.24860
Huang, G., & Wang, S. (2023). Is artificial intelligence more persuasive than humans? A meta-analysis. Journal of Communication, 73(6), 552–562. https://doi.org/10.1093/joc/jqad024
Jarvis, P. (2009). The Routledge International Handbook of Lifelong Learning. Routledge. https://doi.org/10.4324/9780203870549
Jarvis, P. (2012). Towards a Comprehensive Theory of Human Learning. Routledge. https://doi.org/10.4324/9780203001677
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., et al. (2022). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074. https://doi.org/10.1016/j.caeai.2022.100074
Khreisat, M. N., Khilani, D., Rusho, M. A., Karkkulainen, E. A., Tabuena, A. C., & Uberas, A. D. (2024). Ethical Implications Of AI Integration In Educational Decision Making: Systematic Review. Educational Administration: Theory and Practice, 30(5), 8521–8527. https://doi.org/10.53555/kuey.v30i5.4406
Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069–6104. https://doi.org/10.1007/s10639-021-10831-6
Knowles, B., & Richards, J. T. (2021). The Sanction of Authority: Promoting Public Trust in AI. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 262–271). ACM Digital Library. https://doi.org/10.1145/3442188.3445890
Kotsis, K. T. (2024). Artificial Intelligence Creates Plagiarism or Academic Research? European Journal of Arts, Humanities and Social Sciences, 1(6), 169–179. https://doi.org/10.59324/ejahss.2024.1(6).18
Kousa, P., & Niemi, H. (2023). AI ethics and learning: EdTech companies’ challenges and solutions. Interactive Learning Environments, 31(10), 6735–6746. https://doi.org/10.1080/10494820.2022.2043908
Lee, E.-J. (2024). Minding the source: toward an integrative theory of human–machine communication. Human Communication Research, 50(2), 184–193. https://doi.org/10.1093/hcr/hqad034
Lee, H. D. P. (2003). The Republic. Penguin.
Leon, C., Lipuma, J., & Oviedo-Torres, X. (2025). Artificial intelligence in STEM education: A transdisciplinary framework for engagement and innovation. Frontiers in Education, 10, 1619888. https://doi.org/10.3389/feduc.2025.1619888
Li, L., Ma, Z., Fan, L., Lee, S., Yu, H., & Hemphill, L. (2024). ChatGPT in education: a discourse analysis of worries and concerns on social media. Education and Information Technologies, 29(9), 10729–10762. https://doi.org/10.1007/s10639-023-12256-9
Li, S., & Gu, X. (2023). A Risk Framework for Human-centered Artificial Intelligence in Education: Based on Literature Review and Delphi-AHP Method. Educational Technology & Society, 26(1), 187–202. https://doi.org/10.30191/ETS.202301_26(1).0014
Liao, Q. V., Gruen, D., & Miller, S. (2020). Questioning the AI: Informing Design Practices for Explainable AI User Experiences. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–15). ACM Digital Library. https://doi.org/10.1145/3313831.3376590
Mayer, R. E., & Alexander, P. A. (2011). Handbook of Research on Learning and Instruction. Routledge. https://doi.org/10.4324/9780203839089
Melisa, R., Ashadi, A., Triastuti, A., Hidayati, S., Salido, A., Ero, P. E. L., Marlini, C., et al. (2025). Critical Thinking in the Age of AI: A Systematic Review of AI’s Effects on Higher Education. Educational Process: International Journal, 14, e2025031. https://doi.org/10.22521/edupij.2025.14.31
Morales Caluña, E. R., Cervantes Diaz, D. J., & Morales Caluña, C. I. (2025). Patrones de percepción y uso de ChatGPT en estudiantes universitarios: Un análisis HJ-Biplot y de conglomerados. Comunicar, 33(80), 39–48. https://doi.org/10.5281/zenodo.15565693
Obrenovic, B., Gu, X., Wang, G., Godinic, D., & Jakhongirov, I. (2025). Generative AI and human–robot interaction: implications and future agenda for business, society and ethics. AI & Society, 40(2), 677–690. https://doi.org/10.1007/s00146-024-01889-0
Oeldorf-Hirsch, A., & Neubaum, G. (2023). Attitudinal and behavioral correlates of algorithmic awareness among German and U.S. social media users. Journal of Computer-Mediated Communication, 28(5), zmad035. https://doi.org/10.1093/jcmc/zmad035
Oliver, M. B., Gil de Zúñiga, H., & Afifi, T. D. (2024). Reflecting on 50 years of theory in Human Communication Research: where do we go from here. Human Communication Research, 50(2), 143–145. https://doi.org/10.1093/hcr/hqae003
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020
Ouyang, F., Wu, M., Zhang, L., Xu, W., Zheng, L., & Cukurova, M. (2023). Making strides towards AI-supported regulation of learning in collaborative knowledge construction. Computers in Human Behavior, 142, 107650. https://doi.org/10.1016/j.chb.2023.107650
Perkins, D. N. (1993). Person Plus: A Distributed View of Thinking and Learning. In G. Salomon (Ed.), Distributed Cognitions: Psychological and Educational Considerations (pp. 126–152). Cambridge University Press.
Rawls, J. (1971). A Theory of Justice. Harvard University Press. https://doi.org/10.2307/j.ctvjf9z6v
Reeves, B., & Nass, C. (1996). The Media Equation: How People Treat Computers, Television, and New Media Like Real People and Places. Cambridge University Press.
Rienties, B., Køhler Simonsen, H., & Herodotou, C. (2020). Defining the Boundaries Between Artificial Intelligence in Education, Computer-Supported Collaborative Learning, Educational Data Mining, and Learning Analytics: A Need for Coherence. Frontiers in Education, 5, 128. https://doi.org/10.3389/feduc.2020.00128
Riva, G., Wiederhold, B. K., & Cipresso, P. (2025). Humane Artificial Intelligence: Psychological, Social, and Ethical Dimensions. Cyberpsychology, Behavior, and Social Networking, 28(7), 457–461. https://doi.org/10.1089/cyber.2025.0202
Schäffer, B., & Lieder, F. R. (2023). Distributed interpretation – teaching reconstructive methods in the social sciences supported by artificial intelligence. Journal of Research on Technology in Education, 55(1), 111–124. https://doi.org/10.1080/15391523.2022 . 2148786
Shin, D. (2020). How do users interact with algorithm recommender systems? The interaction of users, algorithms, and performance. Computers in Human Behavior, 109, 106344. https://doi.org/10.1016/j.chb.2020.106344
Silva, D. E., Chen, C., & Zhu, Y. (2024). Facets of algorithmic literacy: Information, experience, and individual factors predict attitudes toward algorithmic systems. New Media & Society, 26(5), 2992–3017. https://doi.org/10.1177/14614448221098042
Simon, H. A. (1996). Designing Organizations for an Information-Rich World. International Library of Critical Writings in Economics, 70, 187–202.
Sundar, S. S., & Kim, J. (2019). Machine Heuristic: When We Trust Computers More than Humans with Our Personal Information. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1–9). ACM Digital Library. https://doi.org/10.1145/3290605.3300768
Tang, Q., Deng, W., Huang, Y., Wang, S., & Zhang, H. (2025). Can Generative Artificial Intelligence be a Good Teaching Assistant?—An Empirical Analysis Based on Generative AI-Assisted Teaching. Journal of Computer Assisted Learning, 41(3), e70027. https://doi.org/10.1111/jcal.70027
Topali, P., Ortega-Arranz, A., Rodríguez-Triana, M. J., Er, E., Khalil, M., & Akçap?nar, G. (2025). Designing human-centered learning analytics and artificial intelligence in education solutions: a systematic literature review. Behaviour & Information Technology, 44(5), 1071–1098. https://doi.org/10.1080/0144929X.2024.2345295
Tuomi, I. (2024). Beyond Mastery: Toward a Broader Understanding of AI in Education. International Journal of Artificial Intelligence in Education, 34(1), 20–30. https://doi.org/10.1007/s40593-023-00343-4
Tyndall, E., Gayheart, C., Some, A., Genz, J., Wagner, T., & Langhals, B. (2025). Impact of retrieval augmented generation and large language model complexity on undergraduate exams created and taken by AI agents. Data & Policy, 7, e57. https://doi.org/10.1017/dap.2025.10024
Usher, M., & Barak, M. (2024). Unpacking the role of AI ethics online education for science and engineering students. International Journal of STEM Education, 11(1), 35. https://doi.org/10.1186/s40594-024-00493-4
van Aalst, J. (2009). Distinguishing knowledge-sharing, knowledge-construction, and knowledge-creation discourses. International Journal of Computer-Supported Collaborative Learning, 4(3), 259–287. https://doi.org/10.1007/s11412-009-9069-5
Vargas, E. G., Chiappe, A., & Durand, J. (2024). Reshaping education in the era of artificial intelligence: insights from Situated Learning related literature. Journal of Social Studies Education Research, 15(2), 1–28. https://hdl.handle.net/10818/62738
Vicente-Yagüe-Jara, M. I., López-Martínez, O., Navarro-Navarro, V., & Cuéllar-Santiago, F. (2023). Writing, creativity, and artificial intelligence. ChatGPT in the university context. Comunicar, 77, 47–57. https://doi.org/10.3916/C77-2023-04
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2023). Transitioning to Human Interaction with AI Systems: New Challenges and Opportunities for HCI Professionals to Enable Human-Centered AI. International Journal of Human–Computer Interaction, 39(3), 494–518. https://doi.org/10.1080/10447318.2022.2041900
Yan, W., Nakajima, T., & Sawada, R. (2024). Benefits and Challenges of Collaboration between Students and Conversational Generative Artificial Intelligence in Programming Learning: An Empirical Case Study. Education Sciences, 14(4), 433. https://doi.org/10.3390/educsci14040433
Yang, H., & Sundar, S. S. (2024). Machine heuristic: concept explication and development of a measurement scale. Journal of Computer-Mediated Communication, 29(6), zmae019. https://doi.org/10.1093/jcmc/zmae019
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., et al. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 2021(1), 8812542. https://doi.org/10.1155/2021/8812542
Zouhaier, S. (2023). The Impact of Artificial Intelligence on Higher Education: An Empirical Study. European Journal of Educational Sciences, 10(1), 17–33. https://doi.org/10.19044/ejes.v10no1a17