FABER: An Educational Chatbot for Inclusive and Sustainable Transformation of Instructional Design

Autori

  • Fabrizio Schiavo INDIRE
  • Giuseppina Rita Jose Mangione INDIRE
  • Pio Alfredo Di Tore University of Cassino and Southern Lazio

Parole chiave:

Conversational artificial intelligence; instructional design; sustainability; teacher reflectivity; inclusion.

Abstract

Artificial intelligence is reshaping educational design, fostering new models of reflection and co-creation. The Faber project introduces an embodied conversational agent developed by INDIRE and the University of Cassino and Southern Lazio, conceived not as a prescriptive tutor but as an epistemic partner for instructional design. By integrating the principles of Universal Design for Learning and the GreenComp framework, Faber supports teachers in constructing inclusive, sustainable, and personalized learning pathways. The system employs an adaptive narrative design, a curated Knowledge Bank, and transparent source management, ensuring reliability and traceability. The experimentation, conducted through two co-design ateliers involving sixty teachers, applies a qualitative methodology grounded in thematic analysis, discourse analysis, and conversation analysis. Preliminary results indicate that the tool facilitates shifts from operational action to reflective practice, promoting agency, awareness, and systemic thinking. The chatbot encourages the formulation of metacognitive questions, the reformulation of learning objectives, and the articulation of pedagogical criteria. From this perspective, Faber represents a model of Generative Educational AI that enhances teacher professionalism through dialogue, transparency, and co-design. Rather than replacing the teacher, the technology strengthens their reflective role, contributing to the development of a more equitable, inclusive, and sustainable school system.

Riferimenti bibliografici

Altet, M. (2010). La formazione degli insegnanti tra teoria e pratica. Roma, Italia: Armando.

Bahja, M., Hammad, R., & Butt, G. (2020, July). A user-centric framework for educational chatbots design and development. In International conference on human-computer interaction (pp. 32-43). Cham: Springer International Publishing.

Bickmore, T., & Picard, R. W. (2005). Establishing and maintaining long-term human–computer relationships. ACM Transactions on Computer–Human Interaction, 12(2), 293–327.

Blikstein, P., & Worsley, M. (2016). Children are not Hackers: Building a culture of powerful ideas, deep learning, and equity in the maker movement. Harvard Educational Review, 86(2), 203–232. https://doi.org/10.17763/0017-8055.86.2.203

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901.

Bruner, J. (1991). The narrative construction of reality. Critical inquiry, 18(1), 1-21.

Cerini, G., & Spinosi, M. (2016). Il laboratorio nella formazione degli insegnanti. Firenze, Italia: Giunti Scuola.

Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Palo Alto, CA: Learning Policy Institute.

Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26(2), 247–273.

European Commission. (2022). GreenComp: The European sustainability competence framework. Luxembourg: Publications Office of the European Union.

Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive coding. International Journal of Qualitative Methods, 5(1), 80–92.

Gee, J. P. (2014). An introduction to discourse analysis: Theory and method (4th ed.). New York, NY: Routledge.

Graesser, A. C., Lippert, A. M., & Hampton, A. J. (2017). Successes and failures in building learning environments to promote deep learning: The value of conversational agents. In Informational environments: Effects of use, effective designs (pp. 273-298). Cham: Springer International Publishing.

Hatton, N., & Smith, D. (1995). Reflection in teacher education: Towards definition and implementation. Teaching and teacher education, 11(1), 33-49.

Heritage, J. (2004). Conversation analysis and institutional talk. In R. Sanders & K. Fitch (Eds.), Handbook of language and social interaction (pp. 103–147). Mahwah, NJ: Lawrence Erlbaum.

Hoffmann, J., Borgeaud, S., Mensch, A., Buchatskaya, E., Cai, T., Rutherford, E., ... & Sifre, L. (2022). Training compute-optimal large language models. arXiv preprint arXiv:2203.15556.

Holmes, W., Bialik, M., & Fadel, C. (2021). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (Vol. 2, pp. 215–239). Mahwah, NJ: Lawrence Erlbaum.

Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25–39. https://doi.org/10.1080/00461520.2012.748006

Khosrawi-Rad, B., Rinn, P., & Thomann, G. (2022). Conversational agents in education – A systematic literature review. In Proceedings of the 30th European Conference on Information Systems (ECIS 2022).

Khosrawi-Rad, B., Grogorick, L., & Robra-Bissantz, S. (2023). Game-inspired pedagogical conversational agents: A systematic literature review. AIS Transactions on Human-Computer Interaction, 15(2), 146-192.

Krajcovic, M., Demcak, P., & Kuric, E. (2025). Talking Surveys: How Photorealistic Embodied Conversational Agents Shape Response Quality, Engagement, and Satisfaction. arXiv preprint arXiv:2508.02376.

Kuhail, M. A., Alturki, N., Alramlawi, S., & Alhejori, K. (2023). Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28(1), 973-1018.

Lester, J. C., Converse, S. A., Kahler, S. E., Barlow, S. T., Stone, B. A., & Bhogal, R. S. (1997, March). The persona effect: affective impact of animated pedagogical agents. In Proceedings of the ACM SIGCHI Conference on Human factors in computing systems (pp. 359-366).

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.

Mangione, G. R., Di Tore, P. A., & Paloma, F. G. (2025). Perspective Chapter: Embodied AI and the Educational Turn–From Cognition to Situated Presence. In Teacher Training and Student Learning - Past Values, Present Uncertainties and Future Prospects.

Mangione, G. R. (2017). Il laboratorio nel curricolo formativo dei neoassunti. Formazione & Insegnamento, 15(3), 71–92.

Meadows, D. (2008). Thinking in systems: International bestseller. chelsea green publishing.

Mercer, N. (2000). Words and minds: How we use language to think together. London, UK: Routledge.

Micheli, M., Ponti, M., Craglia, M., & Suman, A. B. (2020). Emerging models of data governance in the age of AI. Public Policy and Administration, 35(4), 485–502. https://doi.org/10.1177/0952076720907087

Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Thousand Oaks, CA: Sage.

MIM (2025). Linee guida per l’introduzione dell’Intelligenza Artificiale nelle Istituzioni scolastiche. https://mim.gov.it/documents/20182/0/MIM_Linee+guida+IA+nella+Scuola_09_08_2025-signed.pdf/b70fdc45-4b75-1f7e-73bf-eab12989b928

Mottet, G. (1992). Les ateliers de formation professionnelle: une proposition pour les IUFM. Recherche et Formation, 11, 93–106.

OECD. (2020). Trustworthy artificial intelligence (AI) in education: Promises and challenges. OECD education working papers, (218), 0_1-17.

Ortega-Ochoa, E., Sabaté, J. M., Arguedas, M., Conesa, J., Daradoumis, T., & Caballé, S. (2024). Exploring the utilization and deficiencies of generative artificial intelligence in students’ cognitive and emotional needs: A systematic Mini-Review. Frontiers in Artificial Intelligence, 7, 1493566.

Pérez-Marín, D. (2021). A review of the practical applications of pedagogic conversational agents to be used in school and university classrooms. Digital, 1(1), 18–33.

Schiavo, F., Mangione, G. R. J., Di Domenico, M., & Di Tore, P. A. (2025). Towards a Somatic Pedagogy of Artificial Intelligence: interdisciplinary reflections between Embodied Cognition and Educational Design. Journal of Inclusive Methodology and Technology in Learning and Teaching, 5(2).

Schön, D. A. (1983). The reflective practitioner: How professionals think in action. New York, NY: Basic Books.

Sedrakyan, G. (2024). AI-driven feedback for metacognitive reflection: A design-based study. Proceedings of the ACM Learning Analytics Conference, 3702386. https://doi.org/10.1145/3702386.3702405

Senge, P. M. (1997). The fifth discipline. Measuring business excellence, 1(3), 46-51.

Silva, G. R. S., & Canedo, E. D. (2024). Towards user-centric guidelines for chatbot conversational design. International Journal of Human–Computer Interaction, 40(2), 98-120.

Sterling, S. (2010). Learning for resilience, or the resilient learner? Towards a necessary reconciliation in a paradigm of sustainable education. Environmental Education Research, 16(5–6), 511–528.

Stoll, L., Bolam, R., McMahon, A., Wallace, M., & Thomas, S. (2006). Professional learning communities: A review of the literature. Journal of Educational Change, 7(4), 221–258.

Valtolina, S. (2024). Designing Conversational Agents for Empowering Human Work. In CEUR WORKSHOP PROCEEDINGS (Vol. 3685). CEUR Workshop Proceedings. https://ceur-ws.org/Vol-3685/short7.pdf

Vygotskij, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

Wals, A. E. J. (2015). Beyond unreasonable doubt: Education and learning for socio-ecological sustainability in the Anthropocene. Wageningen, The Netherlands: Wageningen University.

Weber, F., Wambsganss, T., Rüttimann, D., & Söllner, M. (2021, February). Pedagogical Agents for Interactive Learning: A Taxonomy of Conversational Agents in Education. In ICIS.

Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge, UK: Cambridge University Press.

Yang, F. C., Acevedo, P., Guo, S., Choi, M., & Mousas, C. (2025). Embodied Conversational Agents in Extended Reality: A Systematic Review. IEEE Access.

Yusuf, H., Money, A., & Daylamani-Zad, D. (2025). Pedagogical AI conversational agents in higher education: a conceptual framework and survey of the state of the art. Educational technology research and development, 73(2), 815-874.

Zecca, L. (2016). Didattica laboratoriale e formazione. Bambini e insegnanti in ricerca. Milano, Italia: FrancoAngeli.

Zeichner, K. (2010). Rethinking the connections between campus courses and field experiences in college-and university-based teacher education. Journal of teacher education, 61(1-2), 89-99.

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Pubblicato

2025-11-21

Come citare

Schiavo, F., Mangione, G. R. J. ., & Di Tore, P. A. (2025). FABER: An Educational Chatbot for Inclusive and Sustainable Transformation of Instructional Design. Journal of Inclusive Methodology and Technology in Learning and Teaching, 5(4). Recuperato da https://www.inclusiveteaching.it/index.php/inclusiveteaching/article/view/483

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