Multimodal reading strategies with TikTok and podcasts to improve reading comprehension in grades 8–10 of basic education
DOI:
https://doi.org/10.64747/czxf3r37Keywords:
multimodal reading, educational podcasts, TikTok, reading comprehension, difference‑in‑differencesAbstract
This study assessed the impact of a multimodal reading sequence—combining short educational podcasts and TikTok‑style videos with signaling, embedded questions, and guided production—on reading comprehension among 8th–10th‑grade students in Ecuador’s Basic Education system. We implemented a multi‑arm, pre–post quasi‑experimental design using multinomial propensity score matching (PSM) and difference‑in‑differences (DiD) to build a credible counterfactual. Four classroom‑level conditions were compared: C0 (business‑as‑usual, control), C1 (podcasts), C2 (short videos), and C3 (combined). The analytical sample comprised 112 classes and 3,276 students from urban and rural settings with heterogeneous connectivity. Instruments included IRT‑calibrated comprehension tests (literal, inferential, critical), a rubric for multimodal production, and process questionnaires (self‑efficacy and metacognition). Findings indicate significant improvements for C3 vs C0 in overall comprehension (0.24 SD; 95% CI [0.17, 0.31]) and in the probability of reaching a high achievement level (+7.8 pp; 95% CI [5.2, 10.4]). C1 (0.16 SD) and C2 (0.13 SD) also outperformed the control. The C3 vs {C1, C2} contrast revealed synergy (+0.07 SD). Gains were larger in inferential and critical comprehension. Mediation analyses suggested contributions from reading self‑efficacy (~28% of the total effect) and metacognitive strategies (~9%). The intervention proved feasible in low‑connectivity schools and did not widen within‑class variance. We conclude that offline‑friendly multimodal sequences can meaningfully improve reading comprehension in upper Basic Education at manageable costs. Policy and practice should institutionalize 8‑week cycles, strengthen teacher professional development in signaling and formative assessment, and sustain open repositories of curated resources. Future studies should estimate 6–12‑month persistence and cost‑effectiveness to inform scaling
References
Abadie, A., & Imbens, G. W. (2006). Large sample properties of matching estimators for average treatment effects. Econometrica, 74(1), 235–267. https://doi.org/10.1111/j.1468-0262.2006.00655.x
Aguilar, J. H., Yaguana, M. A., & Simbaña, K. D. (2025). Tecnología y rendimiento académico en estudiantes de ciclo medio en Piñas (Ecuador). Horizonte Científico International Journal, 3(2), 1–12. https://doi.org/10.64747/h1ftaz92
Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46(3), 399–424. https://doi.org/10.1080/00273171.2011.568786
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences‑in‑differences estimates? Quarterly Journal of Economics, 119(1), 249–275. https://doi.org/10.1162/003355304772839588
Callaway, B., & Sant’Anna, P. H. C. (2021). Difference‑in‑differences with multiple time periods. Journal of Econometrics, 225(2), 200–230. https://doi.org/10.1016/j.jeconom.2020.12.001
Cameron, A. C., & Miller, D. L. (2015). A practitioner’s guide to cluster‑robust inference. Journal of Human Resources, 50(2), 317–372. https://doi.org/10.3368/jhr.50.2.317
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. https://doi.org/10.1177/1529100612453266
Dversnes, G., Träff, U., & Skaftun, A. (2023). The potential of podcasts for exploratory talk in high school. Computers in the Schools, 40(3), 225–248. https://doi.org/10.1080/07380569.2023.2196963
Fiorella, L., & Mayer, R. E. (2015). Eight ways to promote generative learning. Educational Psychology Review, 27(4), 617–641. https://doi.org/10.1007/s10648-015-9348-9
García Cabrera, V. A., Guaman Chimbo, M. E., Rea Minchalo, C. B., & Vega Pérez, J. A. (2025). Impacto de los medios tecnológicos en el aprendizaje de estudiantes de educación básica media en contextos urbanos de Ecuador. Horizonte Científico International Journal, 3(2), 1–10. https://doi.org/10.64747/zvkjx362
Gong, Q., Zhang, C., & Xiong, Y. (2024). Short video use and academic performance among elementary students: The mediating role of attention. Frontiers in Psychology, 15, 1404105. https://doi.org/10.3389/fpsyg.2024.1404105
Guijarro‑Garvi, M., Miranda‑Escolar, B., Cedeño‑Menéndez, Y. T., & Moyano‑Pesquera, P. B. (2024). Does geographical location impact educational disparities among Ecuadorians? Humanities and Social Sciences Communications, 11, 1539. https://doi.org/10.1057/s41599-024-04068-0
Guo, X., Sun, L., & Zhang, Y. (2024). Advancing multimodal teaching: A bibliometric and content analysis. Humanities and Social Sciences Communications, 11, 431. https://doi.org/10.1057/s41599-024-04254-0
Johnson, A. P., Binta, H., Phan, M., & Are, C. (2024). The utilization of podcasts and other open‑access resources for surgical education. International Journal of Surgery Open, 63, 101256. https://doi.org/10.1016/j.ijso.2024.101256
Lim, F. V. (2022). Multimodality in the English language classroom. System, 108, 102831. https://doi.org/10.1016/j.system.2022.102831
Moreno, R., & Mayer, R. E. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309–326. https://doi.org/10.1007/s10648-007-9026-9
Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. https://doi.org/10.1093/biomet/70.1.41
Schwabe, A., & Krüger, J. (2022). No negative effects of reading on screen when reading narrative texts. Media Psychology, 25(5), 763–786. https://doi.org/10.1080/15213269.2022.2070216
Si, Q., Sun, Z., & Zhao, J. (2022). Multimodal literacies in K‑12 classrooms: A review of empirical research. Reading Psychology, 43(2), 113–141. https://doi.org/10.1080/19388071.2021.2008555
Song, K., Chakraborty, A., & Dawson, M. (2018). Does podcast playback speed affect comprehension? A randomized trial. Western Journal of Emergency Medicine, 19(1), 101–105. https://doi.org/10.5811/westjem.2017.10.36027
Sweller, J. (2011). Cognitive load theory. In B. Ross (Ed.), Psychology of Learning and Motivation (Vol. 55, pp. 37–76). Academic Press. https://doi.org/10.1016/B978-0-12-387691-1.00002-8
White, H. (1980). A heteroskedasticity‑consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/1912934
Xie, J., Liu, H., & He, J. (2023). Short‑form video addiction and academic procrastination: The mediating role of attentional control. Frontiers in Psychiatry, 14, 1260570. https://doi.org/10.3389/fpsyt.2023.1260570
Yélamos‑Guerra, M. S., García‑Gámez, M., & Moreno‑Ortiz, A. J. (2022). The use of TikTok in higher education as a motivating source for students. Porta Linguarum, 38, 83–98. https://doi.org/10.30827/portalin.vi38.21684
Zolkwer, M. B. (2023). Making educational videos more engaging and effective. International Journal of Lifelong Education, 42(5), 571–589. https://doi.org/10.1080/02601370.2023.2196449
