Aprendizaje independiente de inglés por estudiantes universitarios utilizando las TIC: un enfoque de modelos de ecuaciones estructurales
Descargas
DOI
https://doi.org/10.25267/Hachetetepe.2024.i29.2205Información
Autores/as
- Tubagus Zam Zam Al Arif (ID) Universitas Jambi
- Urip Sulistiyo (ID) Universitas Jambi
- Sri Wachyunni (ID) Universitas Jambi
Resumen
El crecimiento de la tecnología de la información y la comunicación (TIC) puede potenciar la independencia de los estudiantes en el aprendizaje de idiomas. Este estudio se llevó a cabo para investigar los factores que influyen en el aprendizaje autónomo de idiomas mediante el uso de las TIC. Se aplicaron métodos cuantitativos, involucrando a 1.022 estudiantes de inglés de nueve universidades en Indonesia. La recolección de datos se realizó a través de cuestionarios, y el análisis se llevó a cabo utilizando PLS-SEM. Los resultados revelaron que la actitud de los estudiantes es la variable más significativa en la mejora del aprendizaje autodirigido de idiomas a través de las TIC. Este hallazgo es valioso tanto para alumnos como para educadores en su intento de aprovechar las TIC en el aprendizaje de idiomas. Para maximizar el uso de estas tecnologías, los estudiantes deben poseer conocimientos adecuados sobre TIC y mantener actitudes positivas hacia su aplicación en el aprendizaje del inglés. Asimismo, los profesores deben estar capacitados en TIC para ofrecer experiencias de aprendizaje personalizadas que se ajusten a las necesidades de los estudiantes en la era digital. La investigación también proporciona recomendaciones para que educadores y responsables políticos desarrollen infraestructuras TIC adecuadas.Palabras clave
Descargas
Cómo citar
Licencia
Derechos de autor 2024 Tubagus Zam Zam Al Arif, Urip Sulistiyo, Sri Wachyunni
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Aquellos autores/as que tengan publicaciones con esta revista, aceptan los términos siguientes:
- Conservarán sus derechos de autor y garantizarán a la revista el derecho de primera publicación de su obra, el cual estará simultáneamente sujeto a la Licencia de reconocimiento de Creative Commons. Se pueden copiar, usar, difundir, transmitir y exponer públicamente, siempre que se cite la autoría, la url, y la revista, y no se usen para fines comerciales. No se permite hacer obras derivadas.
- Podrán adoptar otros acuerdos de licencia no exclusiva de distribución de la versión de la obra publicada (p. ej.: depositarla en un archivo telemático institucional o publicarla en un volumen monográfico) siempre que se indique la publicación inicial en esta revista.
- Difundir su obra a través de Internet (p. ej.: en archivos telemáticos institucionales o en su página web) una vez que el manuscrito sea aceptado, lo cual puede producir intercambios interesantes y aumentar las citas de la obra publicada. (Véase El efecto del acceso abierto)
Hachetetepé. Revista científica de educación y comunicación no cobra honorarios ni por la presentación de manuscritos ni por la publicación de sus artículos.
Citas
Alfadda, H. A., & Mahdi, H. S. (2021). Measuring Students’ Use of Zoom Application in Language Course Based on the Technology Acceptance Model (TAM). Journal of Psycholinguistic Research, 50(4), 883–900. https://doi.org/10.1007/s10936-020-09752-1
Arif, T. Z. Z. A, Sulistiyo, U., Ubaidillah, M. F., Handayani, R., Junining, E., & Yunus, M. (2022). A Look at Technology Use for English Language Learning from a Structural Equation Modeling Perspective. Computer Assisted Language Learning Electronic Journal, 23(2), 18–37.
Arif, T. Z. Z. A, Kurniawan, D., Handayani, R., Hidayati, & Armiwati. (2024). EFL university students’ acceptance and readiness for e-learning: a structural equation modeling approach. The Electronic Journal of E-Learning, 22(1), 1–16. www.ejel.org
Artman, B., & Crow, R. S. (2022). Instructional technology integration and self-directed learning: A dynamic duo for education. International Journal of Self-Directed Learning, 19(1), 30–44.
Bosch, C., Mentz, E., & Goede, R. (2019). Self-directed learning: A conceptual overview. In Self-Directed Learning for the 21st Century: Implications for Higher Education (pp. 1–36). AOSIS.
https://doi.org/https://doi.org/10.4102/aosis.2019.BK134.01
Chau, K. Y., Law, K. M. Y., & Tang, Y. M. (2021). Impact of Self-Directed Learning and Educational Technology Readiness on Synchronous E-Learning. Journal of Organizational and End User Computing, 33(6), 1–20. https://doi.org/10.4018/joeuc.20211101.oa26
Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.
Creswell, J.W., 2014. Research design: qualitative, quantitative, and mixed methods approaches. 4th edn. SAGE Publications, Inc.
Damrow, A. L., & Faye, T. P. El. (2022). I had to change: empowering students through self-study research. International Journal of Self-Directed Learning, 19(1), 17–29.
Dogham, R. S., Elcokany, N., Ghaly, A., Dawood, T. M. A., Aldakheel, F. M., Llaguno, M. B. B., & Mohsen, D. M. (2022). Self-directed learning readiness and online learning self-efficacy among undergraduate nursing students. International Journal of Africa Nursing Sciences, 17, 100490. https://doi.org/10.1016/J.IJANS.2022.100490
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L.,
Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on
opportunities, challenges and implications of generative conversational AI for research, practice and policy.
International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Fisher, M., King, J., & Tague, G. (2001). Development of a self-directed learning readiness scale for nursing education. Nurse Education Today, 21(7), 516–525. https://doi.org/10.1054/nedt.2001.0589
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Garrison, D. R. (1997). Self-directed learning: Toward a comprehensive model. Adult Education Quarterly, 48(1), 18–33. https://doi.org/10.1177/074171369704800103
Hadiyanto, H., Failasofah, F., Armiwati, A., Abrar, M., & Thabran, Y. (2021). Students’ practices of 21st century skills between conventional learning and blended learning. Journal of University Teaching and Learning Practice, 18(3), 1–23. https://doi.org/10.53761/1.18.3.7
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hamidi, H., & Chavoshi, A. (2019). Social, individual, technological and pedagogical factors influencing mobile learning acceptance in higher education: A case from Iran. Telematics and Informatics, 38, 133–165. https://doi.org/10.1016/j.tele.2018.09.007
Kessler, G. (2018). Technology and the future of language teaching. Foreign Language Annals, 51(1). https://doi.org/10.1111/flan.12318
Kline, R. B. (2016). Principles and practices of structural equation modelling 4th edition. In Methodology in the social sciences.
Lai, Y., Saab, N., & Admiraal, W. (2022). University students’ use of mobile technology in self-directed language learning: Using the integrative model of behavior prediction. Computers and Education, 179, 104413. https://doi.org/10.1016/j.compedu.2021.104413
Marín-Díaz, V., & Sampedro, B. (2023). View of digital competence the university student. Hachetetepé. Revista Científica de Educación y Comunicación, 26. https://doi.org/10.25267/hachetetepe.2023.i26.1102
Mentz, E., & Bailey, R. (2019). A systematic review of research on the use of technology-supported cooperative learning to enhance self-directed learning. In Self-Directed Learning for the 21st Century: Implications for Higher
Education (1st ed., pp. 203–238). AOSIS. https://doi.org/https://doi.org/10.4102/aosis.2019.BK134.07
Mentz, E., Beer, J. De, & Bailey, R. (2019). Self-Directed Learning for the 21st Century: Implications for Higher Education (1st ed., Vol. 1). AOSIS. https://doi.org/10.4102/aosis.2019.bk134.01
Pan, X. (2020). Technology Acceptance, Technological Self-Efficacy, and Attitude Toward Technology-Based Self-Directed Learning: Learning Motivation as a Mediator. Frontiers in Psychology, 11, 1–11.
https://doi.org/10.3389/fpsyg.2020.564294
Pan, X., & Shao, H. (2020). Understanding factors influencing EFL students’ technology-based self-directed learning. International Journal of Social Sciences and Education Research, 6(4), 450–459. https://doi.org/10.24289/ijsser.781472
Park, K.-Y., Sung, T.-S., & Joo, C.-W. (2018). On the Relationship between College Students’ Attitude toward the Internet and their Self-directed English Learning Ability. Journal of The Korea Society of Computer and Information, 23(2), 117–123. https://doi.org/10.9708/jksci.2018.23.02.117
Payne, S. (2021). Using an e-portfolio system to evaluate student learning outcomes and to foster more self- direction within the curricula. International Journal of Self-Directed Learning, 18(1), 1–9.
Rahim, M. N., & Chandran, S. S. C. (2021). Investigating EFL Students’ Perceptions on E-learning Paradigm-Shift During Covid-19 Pandemic. Elsya : Journal of English Language Studies, 3(1), 56–66. https://doi.org/10.31849/elsya.v3i1.5949
Sulistiyo, U., Zam, T., Al Arif, Z., Handayani, R., Ubaidillah, M. F., & Wiryotinoyo, M. (2022). Determinants of Technology Acceptance Model (TAM) Towards ICT Use for English Language Learning. Journal of Language and Education, 8(2), 18-31 https://doi.org/10.17323/jle.2022.12467
Sumuer, E. (2018). Factors related to college students’ self-directed learning with technology. Australian Journal of Educational Technology, 34(4), 29–43.
Tekkol, I. A., & Demirel, M. (2018). An investigation of self-directed learning skills of undergraduate students. Frontiers in Psychology, 9(NOV), 1–14. https://doi.org/10.3389/fpsyg.2018.02324
Teo, T., Tan, Chee, S., Lee, C. B., Chai, C. S., Koh, J. H. L., Chen, W. L., & Horn Mun, C. (2010). The self-directed learning with technology scale (SDLTS) for young students: An initial development and validation. Computers and Education, 55(4), 1764–1771. https://doi.org/10.1016/j.compedu.2010.08.001
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.1006/mvre.1994.1019
Yan, Y., & Singh, M. (2023). On the Educational Theory and Application of Mobile-assisted Language Learning and Independent Learning in College English Teaching. Cilt, 29(3), 137–151.
Yavuzalp, N., & Bahcivan, E. (2021). A structural equation modeling analysis of relationships among university students’ readiness for e-learning, self-regulation skills, satisfaction, and academic achievement. Research and Practice in Technology Enhanced Learning, 16(1), 1–17. https://doi.org/10.1186/s41039-021-00162-y
Zhang, D., & Pérez-Paredes, P. (2019). Chinese postgraduate EFL learners’ self-directed use of mobile English learning resources. Computer Assisted Language Learning, 0(0), 1–26. https://doi.org/10.1080/09588221.2019.1662455
Zhou, L., Xue, S., & Li, R. (2022). Extending the Technology Acceptance Model to Explore Students’ Intention to Use an Online Education Platform at a University in China. SAGE Open, 12(1). https://doi.org/10.1177/21582440221085259
Zhu, M., & Bonk, C. J. (2019). Designing MOOCS to facilitate participant self-monitoring for self-directed learning. Online Learning Journal, 23(4), 106–134. https://doi.org/10.24059/olj.v23i4.2037