Fostering digital competence among Philology students in Higher Education

Authors

DOI:

https://doi.org/10.46502/issn.1856-7576/2026.20.03.14

Keywords:

digital competence, philology students, artificial intelligence, higher education, and pedagogical intervention.

Abstract

The digital transformation of higher education has increased the need to develop digital competence among future philologists. This study aimed to evaluate the effectiveness of a pedagogical system for developing digital competence in philology students through a quasi-experimental intervention. The research employed a quasi-experimental design involving 126 undergraduate philology students, including an experimental group (n = 62) and a control group (n = 64). The intervention included three stages: ascertaining, formative, and control. Data were collected using a structured Digital Competence Questionnaire developed on the basis of the European Digital Competence Framework for Citizens (DigComp 2.2). Digital competence was evaluated according to three dimensions (motivational, content, and activity), and Pearson's χ² test was used to determine the statistical significance of the observed between-group differences. The findings demonstrated that the proposed pedagogical system significantly improved students' digital competence in the experimental group compared with the control group. According to the motivational criterion, the proportion of students with a high level of digital competence increased from 8.1% to 40.3%, while the proportion with a low level decreased from 40.3% to 4.8%. Similar positive changes were observed for the content criterion (high level: 8.1% to 41.9%; low level: 38.7% to 4.8%) and the activity criterion (high level: 9.7% to 50.0%; low level: 50.0% to 4.8%). Statistical analysis confirmed the significance of the observed improvements. The study concludes that integrating digital educational resources, artificial intelligence technologies, and interactive pedagogical approaches effectively enhances the digital competence of philology students. 

Author Biographies

Vasyl Shynkaruk, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.

Doctor of Philological Sciences, Professor, Professor of the Department of Philosophy and International Communication, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.

Yuliia Liakhovska, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Doctor of Philosophy, Military Institute, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.

Dmytro Marieiev, Oleksandr Dovzhenko Hlukhiv National Pedagogical University,  Hlukhiv, Ukraine. 

PhD in Philology, Associate Professor, Head of the Chair of Foreign Languages and Teaching Methods, Oleksandr Dovzhenko Hlukhiv National Pedagogical University,  Hlukhiv, Ukraine. 

Bohdan Nazarov, National University of Life and Environmental Sciences of Ukraine,  Kyiv, Ukraine.

Senior Lecturer, Department of Foreign Philology and Translation, National University of Life and Environmental Sciences of Ukraine,  Kyiv, Ukraine.

Alla Krokhmal, O.M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine. 

PhD (Pedagogy), Associate Professor, Associate Professor of the Department of Foreign Philology and Translation, O.M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine. 

References

Beatty, K. (2013). Teaching and researching computer-assisted language learning (2nd ed.). Routledge.

Boulton, A., & Cobb, T. (2017). Corpus use in language learning: A meta-analysis. Language Learning, 67(2), 348–393. https://doi.org/10.1111/lang.12224

Bowker, L., & Fisher, D. (2010). Computer-aided translation. In Y. Gambier & L. van Doorslaer (Eds.), Handbook of translation studies (Vol. 1, pp. 60–65). John Benjamins Publishing Company. https://benjamins.com/online/hts/articles/comp2

Díaz-Noguera, M. D., Hervás-Gómez, C., De la Calle-Cabrera, A. M., & López-Meneses, E. (2022). Autonomy, motivation, and digital pedagogy are key factors in the perceptions of Spanish higher-education students toward online learning during the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 19(2), 654. https://doi.org/10.3390/ijerph19020654

Falloon, G. (2020). From digital literacy to digital competence: The teacher digital competency (TDC) framework. Educational Technology Research and Development, 68(5), 2449–2472. https://doi.org/10.1007/s11423-020-09767-4

Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004

Hazari, S. (2024). Justification and roadmap for artificial intelligence (AI) literacy courses in higher education. Journal of Educational Research and Practice, 14(1), 106–118. https://doi.org/10.5590/JERAP.2024.14.1.07

Horváthová, B. (2023). Philological study programs in the digital age: A comprehensive analysis of Moodle integration and utilization. Journal of Language and Cultural Education, 11(2), 77–85. https://doi.org/10.2478/jolace-2023-0017

Hubbard, P., & Levy, M. (2016). Theory in computer-assisted language learning research and practice. In F. Farr & L. Murray (Eds.), The Routledge handbook of language learning and technology (pp. 24–38). Routledge. https://doi.org/10.4324/9781315657899

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

McEnery, T., & Hardie, A. (2011). Corpus linguistics: Method, theory and practice. Cambridge University Press.

Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6

O'Hagan, M. (2019). The Routledge Handbook of Translation and Technology. Routledge.

Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu. Publications Office of the European Union. https://doi.org/10.2760/159770

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10, 15. https://link.springer.com/article/10.1186/s40561-023-00237-x

Vuorikari, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The digital competence framework for citizens—With new examples of knowledge, skills and attitudes. Publications Office of the European Union. https://doi.org/10.2760/115376

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

Downloads

Published

2026-09-30

How to Cite

Shynkaruk, V., Liakhovska, Y., Marieiev, D., Nazarov, B., & Krokhmal, A. (2026). Fostering digital competence among Philology students in Higher Education. Eduweb, 20(3), 242–256. https://doi.org/10.46502/issn.1856-7576/2026.20.03.14

Issue

Section

Articles

Similar Articles

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)