Educational AI and the Formation of Inclusive Change Agents among SEA-UV Pedagogy Students

Authors

  • Sajid Demian Lonngi Reyna Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México https://orcid.org/0000-0001-8625-536X
  • Susana García Aguilar Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México https://orcid.org/0000-0002-3694-5052
  • Jeysira Jacqueline Dorantes Carrión Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México

DOI:

https://doi.org/10.56200/mentor.v5i5.13497

Keywords:

inclusive education, educational artificial intelligence, teacher education, Barriers to Learning and Participation, educational change agent

Abstract

Initial preparation of education professionals requires learning experiences that connect inclusion, the analysis of Barriers to Learning and Participation (BLP), and the critical use of artificial intelligence (AI), particularly in open-learning settings. This study analyzed observed results in dimensions related to the competence of acting as an inclusive educational change agent among Pedagogy students in the Open Education System at Universidad Veracruzana. A mixed-methods study with quantitative predominance and descriptive scope was conducted with a group of 40 students; participation varied across activities and items. Diagnostic and final Wooclap activities, open-ended responses, and 16 Complex Performance Evidence products assessed with an analytic rubric were analyzed. In the final evaluation, 10 of 22 students perceived themselves as quite prepared, 9 as moderately prepared, and 3 as very prepared to design inclusive projects using APRA. The Complex Performance Evidence products obtained a mean score of 19.31/20 (SD = 0.87), and Shambala was identified as the most useful AI tool by 16 of 24 participants. Final responses included references to belonging, rights, context, and ethics. The findings provide situated evidence on dimensions related to inclusive professional preparation, without supporting causal attribution or estimates of individual change.

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Author Biographies

Sajid Demian Lonngi Reyna , Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México

Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México

Susana García Aguilar , Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México

Dr. Susana García Aguilar holds a bachelor’s degree in Pedagogy from Universidad Veracruzana, a master’s degree in Educational Psychology, and a doctorate in Education. She is a full-time faculty member and holds the rank of Professor “C” in the Pedagogy Program of the Open Education System at Universidad Veracruzana. She has been awarded PRODEP Preferred Faculty Profile status and Level VI recognition in the Academic Staff Performance Incentive Program. She is a member of the UV-CA-542 Academic Group, Emerging Educational Processes, and leads the research project Structural and Cultural Barriers in Inclusive Education. Since 2020, she has coordinated the Department of Educational Guidance at the Open Education System and has participated in international Collaborative Online International Learning (COIL) projects with institutions in Argentina, Brazil, Costa Rica, and Colombia. Her academic work focuses primarily on inclusive education, educational guidance, tutoring, pedagogical innovation, and the use of technology in educational processes.

Jeysira Jacqueline Dorantes Carrión , Universidad Veracruzana, Sistema de Enseñanza Abierta Pedagogía. Xalapa-México

Dr. Jeysira Jacqueline Dorantes Carrión holds a bachelor’s degree in Pedagogy and a master’s degree in Education from Universidad Veracruzana, as well as a PhD in Pedagogy from the National Autonomous University of Mexico. She is a full-time faculty member and holds the rank of Professor “C” in the Pedagogy Program of the Open Education System at Universidad Veracruzana. She also teaches in the Doctoral Program in Innovation in Higher Education. She is a Level II member of Mexico’s National System of Researchers, holds PRODEP Preferred Faculty Profile status, and has achieved Level VI in the Academic Staff Performance Incentive Program. She coordinates the UV-CA-542 Academic Group, Emerging Educational Processes, and is a member of the Mexican Council for Educational Research and RENIRS-CEMERS. Her research focuses on social representations, school and gender-based violence, cyberbullying, and cultures of peace. In 2023, she received the Veracruz State Science and Technology Award in Humanities and Behavioral Sciences.

References

Ainscow, M. (2020). Promoting inclusion and equity in education: Lessons from international experiences. Nordic Journal of Studies in Educational Policy, 6(1), 7–16. https://doi.org/10.1080/20020317.2020.1729587

Booth, T., & Ainscow, M. (2011). Index for inclusion: Developing learning and participation in schools (3rd ed.). Centre for Studies on Inclusive Education.

Bracho, T. (2002). Desigualdad social y educación en México. Una perspectiva sociológica. EDUCAR, 29, 31–54. https://doi.org/10.5565/rev/educar.325

Branch, R. M. (2009). Instructional design: The ADDIE approach. Springer. https://doi.org/10.1007/978-0-387-09506-6

Cai, H., Han, B., Sun, J., Li, X., & Wong, L.-H. (2025). Harnessing AI for teacher education to promote inclusive education: Investigating the effects of ChatGPT-supported lesson plan critiques on the development of pre-service teachers' lesson planning skills. The Internet and Higher Education, 67, 101022. https://doi.org/10.1016/j.iheduc.2025.101022

Campbell, D. T., & Stanley, J. C. (1966). Experimental and quasi-experimental designs for research. Rand McNally.

Consejo Nacional de Evaluación de la Política de Desarrollo Social. (2020). Medición multidimensional de la pobreza en México 2008–2018. CONEVAL.

Consejo Nacional de Evaluación de la Política de Desarrollo Social. (2021). Informe de evaluación de la política de desarrollo social 2020. CONEVAL.

Cope, B., & Kalantzis, M. (2009). Ubiquitous learning: An agenda for educational transformation. In B. Cope & M. Kalantzis (Eds.), Ubiquitous learning (pp. 3–14). University of Illinois Press.

Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE.

Dick, W., Carey, L., & Carey, J. O. (2015). The systematic design of instruction (8th ed.). Pearson.

Flick, U. (2018). Doing qualitative data collection: Charting the routes. In U. Flick (Ed.), The SAGE handbook of qualitative data collection (pp. 3–16). SAGE Publications. https://doi.org/10.4135/9781526416070.n1

Florian, L. (2014). What counts as evidence of inclusive education? European Journal of Special Needs Education, 29(3), 286–294. https://doi.org/10.1080/08856257.2014.933551

Freire, P. (2000). Pedagogy of the oppressed (30th anniversary ed.). Continuum.

Fullan, M. (2007). The new meaning of educational change (4th ed.). Teachers College Press.

Garrison, D. R., & Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. The Internet and Higher Education, 7(2), 95–105. https://doi.org/10.1016/j.iheduc.2004.02.001

Hwang, G.-J., & Chang, H.-F. (2011). A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Computers & Education, 56(4), 1023–1031. https://doi.org/10.1016/j.compedu.2010.12.002

Instituto Nacional de Estadística y Geografía. (2019). Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH) 2018. https://www.inegi.org.mx/programas/enigh/nc/2018/

Instituto Nacional de Estadística y Geografía. (2021). Censo de Población y Vivienda 2020. https://www.inegi.org.mx/programas/ccpv/2020/

Kalniņa, D., Nīmante, D., & Baranova, S. (2024). Artificial intelligence for higher education: Benefits and challenges for pre-service teachers. Frontiers in Education, 9, 1501819. https://doi.org/10.3389/feduc.2024.1501819

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall.

Lonngi, S. D. (2020). Modelo para el diseño, desarrollo, implementación y evaluación de experiencias educativas... In A. C. Hernández, R. Lonngi, & S. García (Eds.), La labor académica y artística desde la Universidad Veracruzana (pp. 293–314). Morlis Books.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Melo-López, V.-A., Basantes-Andrade, A., Gudiño-Mejía, C.-B., & Hernández-Martínez, E. (2025). The impact of artificial intelligence on inclusive education: A systematic review. Education Sciences, 15(5), 539. https://doi.org/10.3390/educsci15050539

Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE.

Moore, M. G., & Kearsley, G. (2011). Distance education: A systems view of online learning (3rd ed.). Wadsworth Cengage Learning.

Moorhouse, B. L., Wan, Y., Wu, C., Kohnke, L., Ho, T. Y., & Kwong, T. (2024). Developing language teachers' professional generative AI competence: An intervention study in an initial language teacher education course. System, 125, 103399. https://doi.org/10.1016/j.system.2024.103399

Murillo, F. J., & Krichesky, G. J. (2012). El proceso del cambio escolar: Una guía para impulsar y sostener la mejora de las escuelas. REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 10(1), 26–43. https://doi.org/10.15366/reice2012.10.1.001

Organización de las Naciones Unidas. (2006). Convención sobre los derechos de las personas con discapacidad. https://www.un.org/esa/socdev/enable/documents/tccconvs.pdf

Organización de las Naciones Unidas. (2015). Transformar nuestro mundo: La Agenda 2030 para el Desarrollo Sostenible (A/RES/70/1). https://digitallibrary.un.org/record/3923923/files/A_RES_70_1-ES.pdf

Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura. (1994). Declaración de Salamanca y marco de acción para las necesidades educativas especiales. https://unesdoc.unesco.org/ark:/48223/pf0000098427_spa

Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura. (2017). Guía para asegurar la inclusión y la equidad en la educación. https://unesdoc.unesco.org/ark:/48223/pf0000259592

Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura. (2022). Recomendación sobre la ética de la inteligencia artificial. https://unesdoc.unesco.org/ark:/48223/pf0000381137_spa

O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.

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

Schiff, D. (2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2

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

Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.

Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10. https://www.scirp.org/reference/referencespapers?referenceid=148504

Sperling, K., Stenberg, C.-J., McGrath, C., Åkerfeldt, A., Heintz, F., & Stenliden, L. (2024). In search of artificial intelligence (AI) literacy in teacher education: A scoping review. Computers and Education Open, 6, 100169. https://doi.org/10.1016/j.caeo.2024.100169

Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE handbook of mixed methods in social & behavioral research (2nd ed.). SAGE Publications. https://doi.org/10.4135/9781506335193

Tobón, S. (2017). Evaluación socioformativa: Estrategias e instrumentos. Kresearch. https://doi.org/10.24944/isbn.978-0-9969924-0-4

Wiggins, G., & McTighe, J. (2005). Understanding by design (2nd ed.). ASCD.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, 39. https://doi.org/10.1186/s41239-019-0171-0

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: A systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7

Published

20.10.2026

How to Cite

Lonngi Reyna , S. D., García Aguilar , S., & Dorantes Carrión , J. J. (2026). Educational AI and the Formation of Inclusive Change Agents among SEA-UV Pedagogy Students. MENTOR Revista De investigación Educativa Y Deportiva , 5(5), 1–17. https://doi.org/10.56200/mentor.v5i5.13497