Psicopedagogía y TIC: estrategias para mejorar hábitos de estudio en estudiantes con baja motivación
DOI:
https://doi.org/10.71112/6dztsr31Palabras clave:
TIC, psicopedagogía, hábitos de estudio, motivación académica, intervención educativa.Resumen
El estudio tuvo como propósito analizar el impacto de una intervención psicopedagógica mediada por Tecnologías de la Información y la Comunicación (TIC) en los hábitos de estudio y la motivación académica de estudiantes de una institución fiscal del Ecuador. Se aplicó un diseño cuasiexperimental con pretest y postest, conformando un grupo experimental y un grupo control. La intervención incluyó estrategias de autorregulación, planificación del tiempo, uso de plataformas educativas y actividades digitales orientadas al fortalecimiento de la motivación. Los resultados descriptivos e inferenciales muestran mejoras significativas en el grupo experimental en comparación con el grupo control, evidenciando incrementos en la organización del estudio, la participación y el compromiso académico. Asimismo, la integración de acompañamiento psicopedagógico con herramientas tecnológicas permitió atender necesidades individuales y favorecer una participación más activa. Se concluye que las TIC, cuando se utilizan con una orientación pedagógica clara, constituyen un recurso eficaz para promover hábitos de estudio sólidos y elevar la motivación en estudiantes con bajos niveles de desempeño académico.
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Benoot, C., Hannes, K., y Bilsen, J. (2016). The use of purposive sampling in qualitative research. Qualitative Health Research, 26(3), 451–462. https://doi.org/10.1177/1049732315617444
Bond, M. (2020). Facilitating student engagement through educational technology: Evidence and implications. Computers & Education, 151, 103–111. https://doi.org/10.1016/j.compedu.2020.103857
Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., y Kerres, M. (2021). Digital transformation in education: A meta-analysis of the impact of technology-enhanced interventions on student engagement. Educational Research Review, 33, 100390. https://doi.org/10.1016/j.edurev.2021.100390
Buchanan, E. A., Hvizdak, E., y Zimmer, M. T. (2021). Ethical considerations in educational data research: Protecting student privacy in the digital age. Educational Research Review, 34, 100408. https://doi.org/10.1016/j.edurev.2021.100408
Chinna, K., y Sundar, S. (2021). Quasi-experimental research design in educational settings: Strengths, limitations, and practical considerations. Journal of Positive School Psychology, 5(3), 149–158.
Dent, A. L., y Koenka, A. C. (2016). The relation between self-regulated learning and academic achievement across childhood and adolescence: A meta-analysis. Educational Psychology Review, 28(3), 425–474.
Dhakal, C. P. (2022). t-tests and ANOVA: A practical guide for educational research. International Journal of Education and Practice, 10(1), 1–12.
Etikan, I., y Bala, K. (2017). Sampling and sampling methods in educational research. Biostatistics & Epidemiology, 1(1), 1–4.
Gopalan, M., Rosinger, K., y Ahn, J. B. (2020). Use of quasi-experimental research designs in education research: Growth, promise, and challenges. Review of Research in Education, 44(1), 218–243. https://doi.org/10.3102/0091732X20903302
Han, S., Tan, L., y Zhang, Y. (2023). Quasi-experimental approaches in educational intervention research: Design and application. Frontiers in Psychology, 14, 1123458.
Jager, J., Putnick, D. L., y Bornstein, M. H. (2017). More than just convenient: The scientific merits of homogeneous convenience samples. Monographs of the Society for Research in Child Development, 82(2), 13–30. https://doi.org/10.1111/mono.12376
Kim, H., y Lee, J. (2020). The effectiveness of educational interventions using quasi-experimental designs: A meta-analytic perspective. Educational Psychology Review, 32, 97–121. https://doi.org/10.1007/s10648-019-09483-3
Kusmaryono, I., Jupriyanto, J., Sari, R. M., y Kusumawardani, D. (2022). Validity and reliability of Likert scales in educational measurement. International Journal of Educational Methodology, 8(4), 625–640. https://doi.org/10.12973/ijem.8.4.625
Makransky, G., y Petersen, G. B. (2021). The effectiveness of technology-enhanced learning on student motivation and academic outcomes: A systematic review. Computers & Education, 174, 104318. https://doi.org/10.1016/j.compedu.2021.104318
Osmanović Zajić, J., y Maksimović, J. (2022). Quasi-experimental research as an epistemological–methodological approach in education research. International Journal of Cognitive Research in Science, Engineering and Education, 10(3), 177–183. https://doi.org/10.23947/2334-8496-2022-10-3-177-183
Pallant, J. (2020). SPSS survival manual (7th ed.). McGraw-Hill. https://doi.org/10.4324/9781003117452
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, 422. https://doi.org/10.3389/fpsyg.2017.00422
Prada-Núñez, R., Gamboa-Suárez, A. A., y Avendaño-Castro, W. R. (2020). Hábitos de estudio y ambiente escolar: determinantes del rendimiento académico. Revista Espacios, 41(35), 160–169. https://doi.org/10.48082/espacios-a20v41n46p08
Ramos-Navas-Parejo, M., Sánchez-Martín, M., Holguín-Alvárez, J., y Rojas Ruiz, G. (2022). Study habits, academic performance and digital competence in university students during COVID-19. Education Sciences, 12(5), 332. https://doi.org/10.3390/educsci12050332
Razali, N., y Wah, Y. B. (2011). Power comparisons of Shapiro–Wilk, Kolmogorov–Smirnov, and Lilliefors tests. Journal of Statistical Modeling and Analytics, 2(1), 21–33. https://doi.org/10.2139/ssrn.4825093
Ryan, R. M., y Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination perspective. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Sailer, M., y Homner, L. (2021). The effects of educational technology interventions on student learning outcomes: A meta-analysis. Educational Research Review, 34, 100411. https://doi.org/10.1016/j.edurev.2021.100411
Sung, Y.-T., Chang, K.-E., y Liu, T.-C. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis. Computers & Education, 94, 252–275. https://doi.org/10.1016/j.compedu.2015.11.008
Taherdoost, H. (2022). Importance of sampling methods in applied educational research. Journal of Applied Research in Education, 9(1), 15–28.
Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., y Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis. Review of Educational Research, 81(1), 4–28. https://doi.org/10.3102/0034654310393361
Tondeur, J., Van Braak, J., Ertmer, P., y Ottenbreit-Leftwich, A. (2021). Understanding the link between teacher support and student engagement in technology-enhanced learning. Computers & Education, 168, 104193. https://doi.org/10.1016/j.compedu.2021.104193
Tracy, S. J. (2020). A humanizing approach to ethics in educational research. Qualitative Inquiry, 26(2), 194–206. https://doi.org/10.1177/1077800419857743
Vargas López, Y. B., Quevedo Sinche, T. L., Castro Quinto, L. H., Márquez Espinoza, T. G., y Arreaga Jiménez, J. M. (2025). Influencia de herramientas tecnológicas en la motivación estudiantil. Revista Latinoamericana de Calidad Educativa, 2(2), 25–33. https://doi.org/10.70625/rlce/149
Young, M., Mitchell-Yellin, B., y Randall, S. (2024). Rapid classroom observation protocols for active learning environments. Teaching and Teacher Education, 140, 104625. https://doi.org/10.1177/14697874241229421
Zhang, Y., y Xiao, L. (2023). Digital self-regulation tools and their impact on students’ learning motivation and time-management skills. Journal of Educational Computing Research, 61(2), 253–270.
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Derechos de autor 2025 Maira Elizabeth Moreno Saavedra , Maura Mirey Lalangui Pogo, Berónica Anabel Barrera Cuenca, Lorgia Iralda Correa Correa, Madeleine Melissa Delgado Espinoza (Autor/a)
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
