Artificial intelligence and collective intelligence in digital higher education: a quasi-experimental study using the Kampal platform
DOI:
https://doi.org/10.5944/ried.45560Keywords:
artificial intelligence, AI-mediated learning, higher education, collective intelligence, distance education, KampalAbstract
The emergence of Artificial Intelligence (AI) in higher education poses the challenge of integrating personalized learning with collaborative learning. Collective intelligence is presented in this study as a tool that allows both approaches to be articulated, transforming individual contributions into shared knowledge through AI-mediated technologies. Within this framework, the perception of the Kampal platform as a learning environment that simultaneously promotes student autonomy and collective knowledge construction is analyzed. A pretest-posttest quasi-experimental design was used with an initial sample of 399 digital distance higher education students and a final matched sample of 25 cases. Three dimensions were evaluated through a structured questionnaire: familiarity with the tool, perception of its effectiveness, and expectations of use or future willingness to use similar technologies. The results show a significant increase in familiarity with Kampal and willingness to use collective intelligence tools in the future, although no significant changes were found in expectations or perceptions of immediate effectiveness. Factor analysis revealed two main dimensions: familiarity and effectiveness/expectations. The findings suggest that these tools promote a favorable attitude toward their future use, although without significant changes in perceived effectiveness. This highlights the need for intentional teacher mediation. When properly supervised, AI empowers hybrid environments that integrate personalization and collaboration, where collective intelligence operates as a nexus, facilitating complex dynamics such as swarm intelligence in higher education.
Downloads
References
Baltzersen, R. K. (2022). Cultural-historical perspectives on collective intelligence: Patterns in problem solving and innovation. Cambridge University Press. https://doi.org/10.1017/9781108981361
Bayly-Castaneda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: A systematic literature review. Frontiers in Education, 9, 1-12. https://doi.org/10.3389/feduc.2024.1424386
Bautista-Alcaine, P., Íñiguez-Berrozpe, T., & Fernández-Albás, J. (2025). Collective intelligence online experiments: A learning method and its pedagogical applications through online collaborative work platforms. In V. Goglio & C. Biancalana (Eds.), Mapping the evolution of platform society (pp. 13-26). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83608-028-220251002
Bozkurt, A. (2023). Generative artificial intelligence (AI) powered conversational educational agents: The inevitable paradigm shift. Asian Journal of Distance Education, 18(1), 198-204. https://doi.org/10.5281/zenodo.7716416
Broome, B., & Hogan, M. (2020). Core competencies of collective intelligence facilitators. Systems Research and Behavioral Science, 38, 940-944. https://doi.org/10.1002/sres.2734
Cebollero-Salinas, A., Elboj-Saso, C., Íñiguez-Berrozpe, T., & Bautista-Alcaine, P. (2024). Confronting fake news through collective intelligence in adolescents. International Journal of Human–Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2024.2405567
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, 43. https://doi.org/10.1186/s41239-023-00411-8
Consuegra-Fernández, M., Sanz-Aznar, J., Burguera-Serra, J. G., & Caballero-Molina, J. J. (2024). ChatGPT: El dilema sobre la autoría de las actividades evaluables en educación universitaria. Revista de Investigación Educativa, 42(2). https://doi.org/10.6018/rie.565391
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Duenas, T., & Ruiz, D. (2024). The path to superintelligence: A critical analysis of OpenAI's five levels of AI progression [Preprint]. ResearchGate. https://doi.org/10.13140/RG.2.2.33794.70085
European Union. (2024). Reglamento del Parlamento Europeo y del Consejo de 13 de marzo de 2024 por el que se establecen normas armonizadas en materia de inteligencia artificial y se modifican determinados actos legislativos de la Unión. Diario Oficial de la Unión Europea, L 1689, 12 de julio de 2024. https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX:32024R1689
Fidalgo-Blanco, Á., Sein-Echaluce, M. L., & García-Peñalvo, F. J. (2017, 4–6 October). Inteligencia colectiva en el aula. Un paradigma cooperativo [Conference presentation]. IV Congreso Internacional sobre Aprendizaje, Innovación y Competitividad, Zaragoza, España. https://doi.org/10.26754/CINAIC.2017.000001_125
Field, A. (2009). Discovering statistics using SPSS (3rd ed.). SAGE Publications.
García Aretio, L. (2020). Bosque semántico: ¿educación/enseñanza/aprendizaje a distancia, virtual, en línea, digital, eLearning…? RIED-Revista Iberoamericana de Educación a Distancia, 23(1), 9-28. https://doi.org/10.5944/ried.23.1.25495
Gonzalo, A., Sanz-García, F., Pelacho, M., Tarancón, A., Rivero, A., Varela, O., & Moreno, A. (2023). Collective intelligence to find solutions to the challenges posed by the Sustainable Development Goals. Citizen Science: Theory and Practice, 8(1), 47. https://doi.org/10.5334/cstp.587
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage.
Hernández Sampieri, R., Fernández Collado, C., & Baptista Lucio, M. P. (2010). Metodología de la investigación (5.ª ed.). McGraw-Hill.
Hogan, M. J., Barton, A., Twiner, A., James, C., Ahmed, F., Casebourne, I., Hamilton, P., Shi, S., Zhao, Y., Harney, O., & Wegerif, R. (2023). Education for collective intelligence. Irish Educational Studies, 44(1), 137-166. https://doi.org/10.1080/03323315.2023.2250309
Khlaif, Z. N., Ayyoub, A., Hamamra, B., Bensalem, E., Mitwally, M. A. A., Ayyoub, A., Hattab, M. K., & Shadid, F. (2024). University teachers’ views on the adoption and integration of generative AI tools for student assessment in higher education. Education Sciences, 14(10), 1090. https://doi.org/10.3390/educsci14101090
Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025, 10 June). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2506.08872
Ley Orgánica 3/2008, de 13 de octubre, de reconocimiento de la Universidad Internacional de La Rioja. Boletín Oficial del Estado, núm. 261, 42805-42806. https://www.boe.es/eli/es-ri/l/2008/10/13/3
Marrón Luna, Y. A. (2021). Trabajo colaborativo: una opción en la educación en línea. Revista SUAyED Psicología, (2), 26–31. https://www.psicologia.unam.mx/documentos/pdf/publicaciones/revista_suayed/suayed_psicologia_2021_2.pdf
Msambwa, M. M., Wen, Z., & Daniel, K. (2025). The impact of AI on the personal and collaborative learning environments in higher education. European Journal of Education, 60(1). https://doi.org/10.1111/ejed.12909
Mulgan, G. (2018). Big mind: How collective intelligence can change our world. Princeton University Press. https://doi.org/10.1515/9781400888511
Orejudo, S., Cano-Escoriaza, J., Cebollero-Salinas, A. B., Bautista, P., Clemente-Gallardo, J., Rivero, A., Rivero, P., & Tarancón, A. (2022). Evolutionary emergence of collective intelligence in large groups of students. Frontiers in Psychology, 13, 1-16. https://doi.org/10.3389/fpsyg.2022.848048
Penfield, R. D., & Giacobbi, P. R. (2004). Applying a score confidence interval to Aiken's item content-relevance index. Measurement in Physical Education and Exercise Science, 8(4), 213-225. https://doi.org/10.1207/s15327841mpee0804_3
Riedl, C., & Bogert, E. (2024). Effects of AI feedback on learning, the skill gap, and intellectual diversity [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2409.18660
Riedl, C., & De Cremer, D. (2025). AI for collective intelligence. Collective Intelligence, 4(2). https://doi.org/10.1177/26339137251328909
Russell, S. J., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.
Stevens, J. P. (2002). Applied multivariate statistics for the social sciences. Routledge. https://doi.org/10.4324/9781410604491
Sullivan, G. M., & Artino, A. R. (2013). Analyzing and interpreting data from Likert-type scales. Journal of Graduate Medical Education, 5(4), 541-542. https://doi.org/10.4300/JGME-5-4-18
Ullmann, T. D., De Liddo, A., & Bachler, M. (2019). Un panel de visualización para la inteligencia colectiva controvertida: analíticas de aprendizaje para la mejora de creación de ideas en grupos de discusión. RIED-Revista Iberoamericana de Educación a Distancia, 22(1), 41-80. https://doi.org/10.5944/ried.22.1.22294
UNED. (2025, 20 February). Lorenzo García Aretio: un gran legado en la educación a distancia. https://www.uned.es/universidad/inicio/noticias/mostrarnoticia.html?noticia=lorenzo-garcia-aretio-un-gran-legado-en-la-educacion-a-distancia
Universidad Internacional de La Rioja. (2024). Manual de calidad. UNIR. https://static.unir.net/calidad/Manual_calidad.pdf
Universidad Internacional de La Rioja. (2025). Centro de Estudios sobre Innovación (CEI). UNIR. https://www.unir.net/universidad-online/vicerrectorados/vicerrectorado-investigacion/cei/
Wang, H., Wang, C., Zhan, C., Liu, F., Bao, C., & Xianlong, X. (2025). Impact of AI-agent-supported collaborative learning on the learning outcomes of university programming courses. Education and Information Technologies, 30(12), 17717-17749. https://doi.org/10.1007/s10639-025-13487-8
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(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Alicia Martínez-De la muela, Juan Pablo Ruiz-Fuentes, José Luis González Geraldo
This work is licensed under a Creative Commons Attribution 4.0 International License.
The articles that are published in this journal are subject to the following terms:
1. The authors grant the exploitation rights of the work accepted for publication to RIED, guarantee to the journal the right to be the first publication of research understaken and permit the journal to distribute the work published under the license indicated in point 2.
2. The articles are published in the electronic edition of the journal under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. You can copy and redistribute the material in any medium or format, adapt, remix, transform, and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
3. Conditions for self-archiving. Authors are encouraged to disseminate electronically the OnlineFirst version (assessed version and accepted for publication) of its articles before publication, always with reference to its publication by RIED, favoring its circulation and dissemination earlier and with this a possible increase in its citation and reach among the academic community.
