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Exploration of the usage and perception of digital educational resources in UANL students

R. L. Cavazos Salazar. Universidad Autónoma de Nuevo León, México.

F. E. Hernandez Aguilar. Universidad Autónoma de Nuevo León, México.

Capítulo completo (inglés)

Full chapter (English)

 

https://doi.org/10.54988/uaj.000027.016

 


Resumen / Abstract


The study examines trends in the use of digital educational resources among high school and university students at the Autonomous University of Nuevo León (UANL). The main goal is to understand students' perceptions of these resources and compare their usage across different learning units. The research is driven by the need to integrate new technologies into education without compromising essential pedagogical methods. Innovative technologies such as interactive presentations, virtual reality, interactive videos, simulators, and video games are emphasized. The methodology is descriptive and quantitative, utilizing a questionnaire to gather data from a non-probabilistic sample. The findings indicate a positive attitude among students towards increased use of digital resources and a preference for their application in both theoretical and practical learning units. However, many students are unaware of the resources available at UANL. The study concludes that it is crucial to promote existing resources and develop more interactive and innovative tools. The Digital Education Directorate (DED) at UANL, responsible for implementing didactic strategies and digital resources, highlights the importance of tailoring educational offerings to meet students' needs to encourage their active participation and foster their academic and professional growth.


Palabras Clave / Keywords


Digital educational resources, Student´s perceptions, Innovative technologies.


Referencias / References


1. García Aretio, L.: Necesidad de una educación digital en un mundo digital. RIED. Rev Iberoam Educ Dist, 22(2), 9-19 (2019).

2. Losada, M., Zapata M, Arango S.: Entorno virtual para co-crear recursos educativos digitales en la educación superior. Campus Virtuales, 1(1), 101-111 (2020).

3. Lazzarato, M.: El funcionamiento de los signos y de las semióticas en el capitalismo contemporáneo. Palabra Clave, 15(3), 713-725 (2012). https://doi.org/10.5294/pacla.2012.15.3.15

4. Universidad Autónoma de Nuevo León, Modelo Académico de Técnico Superior Universitario, Profesional Asociado y Licenciatura (2022), https://www.uanl.mx/wp-content/uploads/2018/08/Modelo-Acad%C3%A9mico-2020-de-TSU-PA-y-Licenciatura-de-la-UANL.pdf, last accessed 2024/08/21.

5. Hernández-Sampieri, R., Fernández-Collado, C., Baptista-Lucio, P.: Selección de la muestra. Metodología de la Investigación. 6th edn. McGraw-Hill, Mexico City (2014).

6. Universidad Autónoma de Nuevo León, Modelo de Educación Digital (2022), http://ded.uanl.mx/documentos/Modelo_de_Educacion_Digital_UANL.pdf, last accessed 2024/08/21.


Cómo citar / How to cite


Cavazos Salazar, R. L., y Hernandez Aguilar, F. E. (2024). Exploration of the usage and perception of digital educational resources in UANL students. En C. Rusu et al., (1ª ed.), Transformación digital en la educación: innovaciones y desafíos desde los campus virtuales (pp. 93-96). Huelva (España): United Academic Journals (UA Journals). https://doi.org/10.54988/uaj.000027.016

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La Ciberseguridad como pilar de la calidad científica, la competitividad y la legitimidad académica

Jesús Alfonso Soto Pineda. Universidad Complutense de Madrid.

Capítulo completo (español)

Full chapter (Spanish)

 

https://doi.org/10.54988/uaj.979-13-990252-7-9_04

 


Resumen / Abstract


El presente documento analiza el papel de la ciberseguridad como un componente estratégico, jurídico y ético dentro del ecosistema de la investigación científica contemporánea. Con la creciente digitalización del entorno académico y la aparición de amenazas cibernéticas de mayor sofisticación, la ciberseguridad debe ser concebida no como un complemento técnico, sino como una dimensión transversal de la calidad científica que a su vez promueve la competitividad institucional. Por ello, este texto presenta casos recientes de ciberataques a universidades, explora el marco vigente de actuación y su razón de ser, y revisa modelos y estrategias de protección aplicadas por instituciones públicas y privadas. Asimismo, se proponen principios de actuación y recomendaciones para desarrollar una política integral de ciberseguridad en el ámbito universitario, dirigida a fortalecer la reputación y la competitividad, y a favorecer la implementación de políticas que tomen en consideración de manera nuclear la gobernanza institucional, la infraestructura tecnológica, la cooperación internacional y la formación ética.

This document analyzes the role of cybersecurity as a strategic, legal, and ethical component within the contemporary scientific research ecosystem. With the increasing digitalization of the academic environment and the emergence of more sophisticated cyber threats, cybersecurity must be understood not as a mere technical add-on, but as a cross-cutting dimension of scientific quality that also enhances institutional competitiveness. Accordingly, this paper presents recent cases of cyberattacks on universities, explores the current regulatory framework and its underlying rationale, and reviews protection models and strategies adopted by both public and private institutions. Furthermore, it proposes guiding principles and recommendations for developing a comprehensive cybersecurity policy in the university setting—one aimed at strengthening institutional reputation and competitiveness, while promoting the implementation of policies that place institutional governance, technological infrastructure, international cooperation, and ethical training at their core.


Palabras Clave / Keywords


Ciberseguridad académica, ética de la investigación, gobernanza universitaria, protección de datos, competitividad.

Academic cybersecurity, research ethics, university governance, data protection, competitiveness.


Referencias / References


1. Armas, R.; Taherdoost, H. (2025). Building a Cybersecurity Culture in Higher Education: Proposing a Cybersecurity Awareness Paradigm. Information 2025, 16, 336.

2. Aslan, A., Rahman, S., & Krempl, S. (2023). Cyber Threats and Research Integrity in Academia. Journal of Cybersecurity and Education, 15(2), 102–119.

3. Borgman, C. L. (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press.

4. Borgman, C. L. (2018). Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier. arXiv. Recuperado de https://arxiv.org/abs/1802.02953

5. Chertoff, M., & Simon, T. (2021). The Impact of Cybersecurity on Scientific Research. Brookings Institution Report.

6. CIO España. (2021). La UAB sufre un ciberataque y sus sistemas quedan paralizados. Recuperado de https://www.ciospain.es

7. Crick, T., Davenport, J. H., Irons, A., & Prickett, T. (2019). A UK case study on cybersecurity education and accreditation. 1–16.

8. DoD (Department of Defense). (2020). Cybersecurity Maturity Model Certification (CMMC) v1.0. https://www.acq.osd.mil

9. ENISA. (2023). Annual Threat Landscape Report. European Union Agency for Cybersecurity.

10. Fecher, B., & Friesike, S. (2014). Open Science: One Term, Five Schools of Thought. In Bartling, S. & Friesike, S. (Eds.), Opening Science (pp. 17–47). Springer.

11. Floridi, L. (2014). The Fourth Revolution: How the Infosphere is Reshaping Human Reality. Oxford University Press.

12. Georgieva, I. (2022). Cybersecurity and Legal Accountability in Research Institutions. Journal of Law and Technology, 45(2), 135–154.

13. Haque, A., Ahmad, S., John, A., Mishra, K., Kumar Mishra, B., Kumar, K & Nazeer, J. (2023). Cybersecurity in Universities: An Evaluation Model. SN COMPUT.SCI. 4 (569).

14. Hey, T., Tansley, S., & Tolle, K. (2009). The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research.

15. Hiller, J. S., & Russell, R. S. (2021). Information security and ethics in the university setting. Journal of Higher Education Policy and Management, 43(1), 1–16.

16. Jakobsson, M., & Myers, S. (Eds.). (2007). Phishing and countermeasures: Understanding the increasing problem of electronic identity theft. Wiley-Interscience.

17. Jang-Jaccard, J., & Nepal, S. (2014). A survey of emerging threats in cybersecurity. Journal of Computer and System Sciences, 80(5), 973–993.

18. Jiang, X., Li, Y., & He, Y. (2021). Cybersecurity threats to biomedical research during the COVID-19 pandemic: Challenges and countermeasures. Journal of Medical Internet Research, 23(5), e26545. https://doi.org/10.2196/26545

19. Kotsopoulou, A. (2019). Data protection challenges in academic research under the GDPR. International Data Privacy Law, 9(1), 28–45.

20. Landi, H. (2020). UCSF pays hackers $1.1M to regain access to medical school servers. Fierce Healthcare. https://www.fiercehealthcare.com/tech/ucsf-pays-hackers-1-14m-to-regain-access-to-medical-school-servers

21. Lipton, A. B. (2022). Cybersecurity, intellectual property, and the global university: Policy challenges in the age of digital espionage. Journal of Higher Education Policy and Management, 44(3), 267–281.

22. Lujan-Salamanca, A., Infante-Moro, A., Infante Moro, J.C., Gallardo-Pérez, J. (2024). La ciberseguridad en las empresas: estudio biométrico. Revista de Pensamiento Estratégico y Seguridad CISDE, 9(2), 61–73

23. Maastricht University. (2020). UM paid ransom to regain access to data after cyber attack. https://www.maastrichtuniversity.nl/news/um-paid-ransom-regain-access-data-after-cyber-attack

24. Modi, A., Kuzminykh, I., & Ghita, B. (2023). Data driven approaches to cybersecurity governance for board decision-making, 1–13.

25. National Academies of Sciences, Engineering, and Medicine. (2020). Protecting Research Integrity in a Digital Age. The National Academies Press.

26. Nature Editorial. (2020). Cybersecurity: A Scientific Priority. Nature, 580(7803), 563.

27. OECD. (2021). Digitalisation and Science: Research in a Time of Disruption. OECD Publishing.

28. O’Hanley, J. R., & Tiller, M. S. (2021). Cyber resilience in research ecosystems: Best practices and institutional challenges. Information Security Journal, 30(4), 201–215.

29. Pomerleau, M., & Martell, B. (2020). Data sabotage in machine learning systems: Implications for scientific integrity. Journal of Cybersecurity, 6(1)

30. Riebe, B. (2020). University of Maastricht pays ransom after ransomware attack. European Cybersecurity Journal, 6(2), 45–47.

31. Ross, R. S., McEvilley, M., & Oren, J. (2020). Protecting university infrastructure from distributed denial-of-service attacks. National Institute of Standards and Technology (NIST SP 800-82 Rev. 2).

32. Scott, J., & Spaniel, D. (2022). Cyber Espionage in the Age of Pandemics. International Journal of Cybersecurity, 8(1), 88–103.

33. Seshagirirao, V. K., & Babatope, A. B. (2024). The role of data governance in enhancing cybersecurity resilience for global enterprises. World Journal of Advanced Research and Reviews, 24(1), 1420–1432.

34. Shore, R., & Stein, M. (2021). Securing knowledge: Cybersecurity risks in higher education. Cyber Policy Studies Review, 4(3), 112–127.

35. Unión Europea. Reglamento (UE) 2016/679 del Parlamento Europeo y del Consejo de 27 de abril de 2016. Relativo a la protección de las personas físicas en lo que respecta al tratamiento de datos personales.

36. University of Newcastle. (2023). Internal audit report on AI project data integrity incident. (Documento institucional interno; citado con autorización).

37. UNViMe. (2023). UBA confirma ataque ransomware y activa protocolos de contingencia. https://www.unvime.edu.ar

38. UNESCO. (2021). Recommendation on Open Science. https://unesdoc.unesco.org

39. Yang, L., Li, J., Elisa, N., Prickett, T. & Chao, F. (2019). Towards big data governance in cybersecurity. Data-Enabled Discovery and Applications, 3(1), Article 10.

Cómo citar / How to cite


Soto Pineda, J. A. (2025). La Ciberseguridad como pilar de la calidad científica, la competitividad y la legitimidad académica. En Academia Iberoamericana de La Rábida, (1ª ed.), Formación en ciberseguridad y ética en trabajos académicos y científicos (pp. 97-112). Huelva: Academia Iberoamericana de La Rábida / United Academic Journals (UA Journals). https://doi.org/10.54988/uaj.979-13-990252-7-9_04

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2025    ----   Investigación Tradicional VS uso de Inteligencia Artificial para el análisis. Aprendizaje Significativo


Autora: Adriana Margarita Pacheco Cortés.

 

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Presentación

 

Capítulo 1. Introducción

 

Capítulo 2. Marco Teórico y Revisión de Literatura

 

Capítulo 3. Método

 

Capítulo 4. Resultados: Investigación tradicional

 

Capítulo 5. Construcción teórica con el uso de inteligencia artificial

 

Capítulo 6. Análisis y Discusión

 

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Proposed Emotional Questionnaire to Evaluate the User Experience of Virtual Learning Environments: Expert Validation

Laura N. Aballay. Instituto de Informática, Universidad Nacional de San Juan, San Juan, Argentina.

Silvana V. Aciar. Instituto de Informática, Universidad Nacional de San Juan, San Juan, Argentina.

César A. Collazos. Universidad del Cauca, Popayán, Colombia.

Alex A. Torres. Corporación Universitaria Comfacauca – UNICOMFACAUCA, Popayán, Colombia.

Capítulo completo (inglés)

Full chapter (English)

 

https://doi.org/10.54988/uaj.000028.012

 


Resumen / Abstract


This paper presents a proposed questionnaire for the evaluation of user experience (UX) with emotions. Although there are several questionnaires, such as AttrakDiff and the User Experience Questionnaire (UEQ), that measure product-centered perceptions and acceptance, few consider emotions suitable for evaluating virtual learning environments. In response to this limitation, a new questionnaire, "EMO-UX", designed to assess UX in virtual learning environments (VLE) from an affective approach, is proposed. This instrument, currently validated by experts, seeks to provide a more accurate and less confusing alternative to existing tools, integrating elements that allow a more complete capture of the user's emotional state during their interaction with the product. In addition, the characteristics of the main existing emotional questionnaires are compared and analyzed, highlighting their strengths and limitations. This work provides an innovative tool to improve the understanding of UX, especially in virtual educational contexts.


Palabras Clave / Keywords


Human computer interaction, Affective Computing, User Experience, Emotional Evaluation, Virtual Learning Environments, Surveys, Questionaries.


Referencias / References


1. K. Capota, M. van Hout, and T. van der Geest, “Measuring the emotional impact of websites,” in Proceedings of the 2007 conference on Designing pleasurable products and interfaces - DPPI ’07, 2007, p. 135.

2. L. Masip Ardévol, “User experience methodology for the design and evaluation of interactive systems,” University of Lleida, 2013.

3. D. Quiñones, C. Rusu, and V. Rusu, “A methodology to develop usability/user experience heuristics,” Comput. Stand. Interfaces, vol. 59, pp. 109–129, Aug. 2018.

4. M. Hassenzahl, S. Diefenbach, and A. Göritz, “Needs, affect, and interactive products – Facets of user experience,” Interact. Comput., vol. 22, no. 5, pp. 353–362, Sep. 2010.

5. A. F. Aguirre, V. F. Ángela, C. A. Collazos, and R. Gil, “Proposal to evaluate the satisfaction of use in Virtual Learning Environments,” in Proceedings of the XV International Conference on Human Computer Interaction - Interacción ’14, 2014, pp. 1–4.

6. E. Crisol-Moya, L. Herrera-Nieves, and R. Montes-Soldado, “Educación virtual para todos: una revisión sistemática,” Educ. Knowl. Soc., vol. 21, no. 0, p. 13, Jun. 2020.

7. F. J. García-Peñalvo, A. Miguel, and S. Pardo, “Una revisión actualizada del concepto de eLearning. Décimo Aniversario,” vol. 16, no. 1, 2015.

8. E. Ivanova and G. Borzunov, “Optimization of machine learning algorithm of emotion recognition in terms of human facial expressions,” Procedia Comput. Sci., vol. 169, pp. 244–248, Jan. 2020.

9. M. R. Mahmood et al., “Classification techniques’ performance evaluation for facial expression recognition,” Artic. Indones. J. Electr. Eng. Comput. Sci., vol. 21, no. 2, pp. 1176–1184, 2021.

10. S. Patil, A. Joshi, G. Deore, A. Taley, and S. Sawant, “Emotion Detection Using Facial Recognition,” SSRN Electron. J., 2020.

11. A. Vartanov, V. Ivanov, and I. Vartanova, “Facial expressions and subjective assessments of emotions,” Cogn. Syst. Res., vol. 59, no. 2020, pp. 319–328, 2020.

12. E. S. Salama, R. A. El-Khoribi, M. E. Shoman, and M. A. Wahby Shalaby, “A 3D-convolutional neural network framework with ensemble learning techniques for multimodal emotion recognition,” Egypt. Informatics J., vol. 22, no. 2, pp. 167–176, Jul. 2021.

13. L. Schoneveld, A. Othmani, and H. Abdelkawy, “Leveraging recent advances in deep learning for audio-Visual emotion recognition,” Pattern Recognit. Lett., vol. 146, pp. 1–7, Jun. 2021.

14. S. Cano, L. García, C. A. Collazos, and S. Albiol, “Towards the Design of a System to Measure Emotions using Physiological Signals as Biofeedback. Case Study in Higher Education Students,” REHAB 2019, 2019.

15. J. A. Domínguez-Jiménez, K. C. Campo-Landines, J. C. Martínez-Santos, E. J. Delahoz, and S. H. Contreras-Ortiz, “A machine learning model for emotion recognition from physiological signals,” Biomed. Signal Process. Control, vol. 55, p. 101646, Jan. 2020.

16. L. Aballay, C. Collazos, S. Aciar, and A. Torres, “Analysis of Emotion Recognition Methods: A Systematic Mapping of the Literature,” in WITCOM 2024 - Telematics & Computing (En proceso de aprobación), 2024.

17. P. M. Desmet, “Measuring emotions: Development of an instrument to measure emotional responses to products,” Funology from usability to enjoyment. Kluwer Acad. Publ. Dordrecht, Boston, Londres, no. Blythe, M. A.; Overbeeke, K.; Monk, A. F.; Wright, P. C. (ed.), 2003.

18. L. N. Aballay, S. V. Aciar, and C. A. Collazos, “Students Emotions Evaluation on Virtual Learning Environments (Atena Editora),” Students Emot. Eval. Virtual Learn. Environ. (Atena Ed., vol. 2, no. 16, pp. 2–11, Jan. 2022.

19. M. Hassenzahl, M. Burmester, and F. Koller, “Der USer Experience (UX) auf der Spur: Zum einsatz von www.attrakdiff.de.” 2008.

20. M. M. Bradley and P. J. Lang, “Measuring emotion: The self-assessment manikin and the semantic differential,” J. Behav. Ther. Exp. Psychiatry, vol. 25, no. 1, pp. 49–59, 1994.

21. G. Huisman, M. Van Hout, B. Van Dijk, T. Van Der Geest, and D. Heylen, “LEMtool - Measuring emotions in visual interfaces,” Conf. Hum. Factors Comput. Syst. - Proc., no. August 2014, pp. 351–360, 2013.

22. P. Desmet, “Measuring Emotion: Development and Application of an Instrument to Measure Emotional Responses to Products,” Funology From Usability to Enjoyment. Kluwer Acad. Publ. Print. Netherlands., pp. 111–123, 2003.

23. Y. A. Méndez-Alegría, C. A. Collazos, T. Granollers, and R. Gil, “Rueda de emociones de Ginebra+: instrumento para la valoración emocional de los usuarios mientras participan en una evaluación de sistemas interactivos,” Dyna, vol. 91, no. 2, pp. 151–155, 2016.

24. K. R. Sacharin, V., Schlegel, K., & Scherer, “Geneva Emotion Wheel Rating Study,” Geneva, Switz. Univ. Geneva, Swiss Cent. Affect. Sci., 2012.

25. L. N. Aballay, S. V. Aciar, and C. A. Collazos, “Emotions for Virtual Learning Environments,” IEEE-RITA, vol. 9, no. 3, 2021.

26. J. I. Cocunubo-Suárez, J. A. Parra-Valencia, and J. E. Otálora-Luna, “Propuesta para la evaluación de Entornos Virtuales de Enseñanza Aprendizaje con base en estándares de Usabilidad Evaluation of Virtual Teaching- Learning Environments based on usability standards Cómo citar / How to cite Propuesta para la evaluación de En,” vol. 21, no. 41, pp. 123–7799, 2018.

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28. L. N. Aballay, S. V. Aciar, and C. A. Collazos, “Students Emotions Evaluation on Virtual Learning Environments,” J. Eng. Res., vol. 2, no. 16, pp. 2–11, Jul. 2022.

29. R.- Likert, “A technique for the measurement of attitudes.,” psycnet.apa.org, 1932.

30. M. I. Bernal-García, D. R. Salamanca Jiménez, N. Perez Gutiérrez, and M. P. Quemba Mesa, “Content validity by expert judgment of an instrument to measure physico-emotional perceptions in anatomical dissection practice,” Educ. Medica, Oct. 2018.

31. L. A. Galicia Alarcón, J. A. Balderrama Trápaga, R. Edel Navarro, L. A. Galicia Alarcón, J. A. Balderrama Trápaga, and R. Edel Navarro, “Validez de contenido por juicio de expertos: propuesta de una herramienta virtual,” Apert. (Guadalajara, Jal.), vol. 9, no. 2, pp. 42–53, 2017.


Cómo citar / How to cite


Aballay, L. N., Aciar, S. V., Collazos, C. A., y Torres, A. A. (2024). Proposed Emotional Questionnaire to Evaluate the User Experience of Virtual Learning Environments: Expert Validation. En C. Rusu et al., (1ª ed.), Transformación digital en la educación: innovaciones y desafíos en la tecnología educativa (pp. 73-78). Huelva (España): United Academic Journals (UA Journals). https://doi.org/10.54988/uaj.000028.012


 

 Contact Info

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