Development and use of Virtual Tutor in commercial research teaching

Authors

DOI:

https://doi.org/10.31637/epsir-2026-2187

Keywords:

App development, virtual tutor, Bayesian networks, applied research, learning characteristics

Abstract

Introduction: The objective of this research work was to develop a virtual tutor and analyze relationships and usage patterns for learning. Methodology: It is divided into three stages: project design and development, installation and execution of the virtual tutor app on mobile devices, and analysis of the student experience. The study design is prospective, cross-sectional, with a relational approach. It uses psychometric cross-sectional Bayesian neural network analysis techniques and gender analysis criteria based on male and female. The study population is composed of students in the commercial research course. Results: The virtual tutor app was designed, implemented, and executed using the MIT® App Inventor platform, and a Bayesian network model was built. Discussion: Positive relationships are observed regarding innovativeness and fun, understanding of concepts, learning costs, and usefulness for learning. In addition, interactiveness, dynamicness, innovation, understanding of concepts and processes, reduction of learning time and costs, and the use of the tutor as a learning tool stand out. Conclusions: There are slight differences in the learning patterns of the networks analyzed.

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Author Biographies

Roberto Arturo Berríos Zepeda, Universidad Nacional Autónoma de Nicaragua-León

Director of the specific area of Business Administration and Marketing Sciences, tenured professor, PhD in Business Economics and advanced studies in Commercial Research Techniques from the Autonomous University of Madrid (UAM), Spain. Research professor in the fields of new technologies applied to higher education and marketing.

Lorgia Yolanda Márquez Mora, Universidad Nacional Autónoma de Nicaragua-León

Professor specializing in Administration, with a master's degree in Business Law. Research professor in the fields of new technologies applied to higher education and business law.

References

Augello, A., Gentile, M., Weideveld, L. y Dignum, F. (2016). A model of a social chatbot. Intelligent interactive multimedia systems and services 2016. Springer. DOI: https://doi.org/10.1007/978-3-319-39345-2_57

Allison, D.A. (2011). Chatbots in the Library: is it time? Faculty Publications. UNL Libraries. https://digitalcommons.unl.edu/libraryscience/280

Cabero, J., De la Horra, I. y Sánchez, J. (2018) La realidad aumentada como herramienta educativa. Paraninfo: Madrid.

Clark, D. (2017). 10 uses for Chatbots in learning. https://bit.ly/4kRE9bd

Cerdas, D. (2017). Historia de la Inteligencia artificial relacionada con los Chatbots. Planteta chatbot. https://bit.ly/4k6uLQ2

Clarizia, F., Colace, F., Lombardi, M., Pascale, F. y Santaniello, D. (2018). Chatbot: An education support system for student. International symposium on cyberspace safety and security. Springer. DOI: https://doi.org/10.1007/978-3-030-01689-0_23

Cunningham-Nelson, S., Boles, W., Trouton, L. y Margerison, E. (2019). A review of chatbots in education: Practical steps forward. 30th annual conference for the australasian association for engineering education (AAEE 2019): Educators becoming agents of change: Innovate, integrate. Motivate: Engineers Australia.

Dhyani, M. y Kumar, R. (2021). Un Chatbot inteligente que utiliza aprendizaje profundo con RNN bidireccional y modelo de atención. Actas, 34, 817-824. DOI: https://doi.org/10.1016/j.matpr.2020.05.450

Dörrenbächer, L., and Perels, F. (2016). More Is More? Evaluation of Interventions to Foster Self-Regulated Learning in College. Int. J. Educ. Res. 78, 50–65. https://doi.org/10. 1016/j.ijer.2016.05.010 DOI: https://doi.org/10.1016/j.ijer.2016.05.010

Durall, E. y Kapros, E. (2020). Co-design for a competency self-assessment chatbot and survey in science education. International conference on human-computer interaction. Springer. DOI: https://doi.org/10.1007/978-3-030-50506-6_2

García B., Fuertes M. y Molas N. (2018). Briefing paper: els xatbots en educació. Barcelona: eLearn Center. Universitat Oberta de Catalunya. ISBN: 978-84-09-03944-9 https://doi.org/10.7238/elc.chatbots.2018 DOI: https://doi.org/10.7238/elc.chatbots.2018

Hien, H. T., Cuong, P.-N., Nam, L. N. H., Nhung, H. L. T. K. y Thang, L. D. (2018). Intelligent assistants in higher-education environments: The fit-ebot, a chatbot for administrative and learning support. Proceedings of the ninth international symposium on information and communication tech- nology. DOI: https://doi.org/10.1145/3287921.3287937

Hill, J., Ford, W. R. y Farreras, I. G. (2015). Real conversations with artificial intelligence: A comparison between human–human online conversations and human–Chatbot conversations. Computers in Human Behavior, 49, 245-250. https://doi.org/10.1016/j.chb.2015.02.026 DOI: https://doi.org/10.1016/j.chb.2015.02.026

Ho, C. C., Lee, H. L., Lo, W. K. y Lui, K. F. A. (2018). Developing a chatbot for college student programme advisement. In 2018 international symposium on educational technology (ISET) (pp 52-56). IEEE. DOI: https://doi.org/10.1109/ISET.2018.00021

IESALC, UNESCO. (2020). COVID-19 y educación superior: De los efectos inmediatos al día después. https://bit.ly/4kV4mpi

Khan, R. y Das, A. (2017). Build Better Chatbots: A Complete Guide to Getting Started with Chatbots (1st ed.). New York: Apress. DOI: https://doi.org/10.1007/978-1-4842-3111-1_1

Kotler, P., Kartajaya, H. y Setiawan, I. (2021) Marketing 5.0 Tecnologías para la humanidad. John Wiley y Sons. Hoboken, New Jersey.

Kumar, M. N., Chandar, P. L., Prasad, A. V. y Sumangali, K. (2016). An-droid based educational chatbot for visually impaired people. In 2016 IEEE international conference on computational intelligence and computing Re- search (ICCIC), (pp 1-4). IEEE. DOI: https://doi.org/10.1109/ICCIC.2016.7919664

Lázaro-Carrascosa, C., Hernán-Losada, I., Palacios-Alonsoc, D. y Velázquez-Iturbide, A. (2021). Aula invertida y puzle de Aronson: una evaluación combinada en el Máster del profesorado. Education in the knowledge society, 22. https://doi.org/10.14201/eks.23617 | e23617 DOI: https://doi.org/10.14201/eks.23617

León-Gómez, A., Gil-Fernández, R. y Calderón-Garrido, D. (2021). Influence of CoVId on the educational use of Social Media by students of Teaching degrees. Education in the knowledge society, 22, e23623. https://doi.org/10.14201/eks.23623 DOI: https://doi.org/10.14201/eks.23623

McKeachie, W. J., Pintrich, P. R., Lin, Y. G. y Smith, D. A. (1987). Teaching and learning in the college classroom: A review of the literature. Ann Harbor, National Center for Research to Improve Postsecondary Teaching and Learning: The University of Michigan.

Melo, T. R., Neto, J. D. R. y Silva, J. J. (2021). Integration of virtual instrumentation in the teaching of data acquisition and interface systems course. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 16(2), 154-160. https://doi.org/10.1109/RITA.2021.3089928 DOI: https://doi.org/10.1109/RITA.2021.3089928

Mendoza, S., Hernandez-Leon, M., Sanchez-Adame, L. M., Rodrıguez, J., Decouchant, D., y Meneses-Viveros, A. (2020). Supporting student-teacher interaction through a chatbot. International conference on human- computer interaction. Springer. DOI: https://doi.org/10.1007/978-3-030-50506-6_8

Mikic-Fonte, F. A., Llamas-Nistal, M. y Caeiro-Rodrıguez, M. (2018). Using a chatterbot as a faq assistant in a course about computers architecture. In 2018 IEEE frontiers in education conference (FIE), (pp. 1-4). IEEE. DOI: https://doi.org/10.1109/FIE.2018.8659174

Mohammadi, R. y Wit, E. C. (2019). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models. Journal of Statistical Software, 89. https://doi.org/10.18637/ jss.v089.i03 DOI: https://doi.org/10.18637/jss.v089.i03

Mohammadi, R., Abegaz, F., van den Heuvel, E. y Wit, E. C. (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 66, 629-645. https://doi.org/10.1111/ rssc.12171 DOI: https://doi.org/10.1111/rssc.12171

Mor, E., Santanach, F., Tesconi, S. y Casado, C. (2018). Codelab: Designing a conversation-based educational tool for learning to code. International conference on human-computer interaction. Springer. DOI: https://doi.org/10.1007/978-3-319-92285-0_14

Neumann, A T., Arndt, T., Köbis, L., Meissner, R., Martin, A., de Lange, P., Pengel, N., Klamma, R. y Wollersheim, H. W. (2021) Chatbots as a Tool to Scale Mentoring Processes: Individually Supporting Self-Study in Higher Education. Front. Artif. Intell, 4, 668220. https://doi.org/ 10.3389/frai.2021.668220 DOI: https://doi.org/10.3389/frai.2021.668220

Ndukwe, I. G., Daniel, B. K. y Amadi, C. E. (2019). A machine learning grading system using chatbots. International conference on artificial intelligence in education. Springer. DOI: https://doi.org/10.1007/978-3-030-23207-8_67

Nguyen, H. D., Pham, V. T., Tran, D. A. y Le, T. T. (2019). Intelligent tutoring chatbot for solving mathematical problems in high school. In 2019 11th international conference on knowledge and systems engineering (KSE), (pp 1-6). IEEE. DOI: https://doi.org/10.1109/KSE.2019.8919396

Okonkwo, C. W. y Ade-Ibijola, A. (2021). Python-bot: A chatbot for teaching python programming. Engineering Letters, 29(1).

Okonkwo, C. W. y Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033 DOI: https://doi.org/10.1016/j.caeai.2021.100033

Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P. y Mazurek, G. (2019). En bot confiamos: una nueva metodología de medidas de desempeño de chatbot. Horizontes Empresariales, 62(6), 785-797. https://doi.org/10.1016/j.future.2018.01.055 DOI: https://doi.org/10.1016/j.bushor.2019.08.005

Smutny, P. y Schreiberova, P. (2020) Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers & Education, 151, https://doi.org/10.1016/j.compedu.2020.103862

Ranoliya, B. R., Raghuwanshi, N. y Singh, S. (2017). Chatbot for university related faqs. In 2017 international conference on advances in computing, communications, and informatics (ICACCI), (pp. 1525-1530). IEEE. DOI: https://doi.org/10.1109/ICACCI.2017.8126057

Romero, M., Casadevante, C. y Montoro, H. (2020). Cómo construir un psicólogo-chatbot. Papeles del Psicólogo, 41(1), 27-34. DOI: https://doi.org/10.23923/pap.psicol2020.2920

Ruan, S., Willis, A., Xu, Q., Davis, G. M., Jiang, L., Brunskill, E. y Landay, J. A. (2019). Bookbuddy: Turning digital materials into interactive foreign language lessons through a voice chatbot. In Proceedings of the sixth ACM conference on learning@ scale (pp. 1-4). DOI: https://doi.org/10.1145/3330430.3333643

Smutny, P. y Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook messenger. Computers & Education, 151, 103862. DOI: https://doi.org/10.1016/j.compedu.2020.103862

Thomas, H. (2020). Critical literature review on chatbots in education. International Journal of Trend in Scientific Research and Development, 4(6), 786-788.

Vinciotti, V., Behrouzi, P. y Mohammadi, R. (2022). Bayesian structural learning of microbiota systems from count metagenomic data. arXiv https://acortar.link/AP8gEu

Ureta, J. y Rivera, J. P. (2018). Using chatbots to teach stem related research concepts to high school students.

Published

2025-11-24

How to Cite

Berríos Zepeda, R. A., & Márquez Mora, L. Y. (2025). Development and use of Virtual Tutor in commercial research teaching. European Public & Social Innovation Review, 11, 1–15. https://doi.org/10.31637/epsir-2026-2187

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