WEB-BASED INTERACTIVE STRATEGIES FOR EFFECTIVE TOEFL ITP READING SKILLS

Arda Adianto, Eva Sulistiana, Wardatun Nadzifah


Abstract


The TOEFL ITP reading comprehension section poses a significant challenge for many EFL learners, necessitating innovative instructional approaches. This study aims to develop and evaluate a dedicated web-based learning platform integrating interactive strategies to enhance reading skills for the TOEFL ITP. Employing a Research and Development (R&D) design with the 4D model (Define, Design, Develop, Disseminate), the study involved 109 university students selected through purposive sampling. The platform's development included validation by English teaching and educational technology experts, followed by a limited field test. Data were collected through pre-test/post-test assessments and a usability questionnaire. The results indicated a substantial improvement in reading proficiency, with mean scores increasing from 355.88 to 423.45, a statistically significant gain of 18.98% (Z = -9.019, p < .001). Furthermore, user evaluations revealed positive feedback on the platform's accessibility, interactivity, and ability to maintain engagement. This study concludes that the purpose-built web-based platform serves as an effective intervention for improving TOEFL ITP reading skills. It contributes to the field of digital-based EFL instruction by demonstrating the efficacy of a tailored, interactive learning tool for standardized test preparation.

Keywords


TOEFL ITP; reading comprehension; web-based learning; research and development; educational technology; higher education.

Full Text:

PDF

References


Abdulrahaman, M. D., et al. (2020). Multimedia tools in the teaching and learning processes: A systematic review. Heliyon, 6(11), e05312. https://doi.org/10.1016/j.heliyon.2020.e05312

Aeni, N. (2024). Students' challenges and approaches to comprehending the TOEFL reading section. International Journal of Education Research and Development, 4(2), 81–90.

Aldosari, S. A. M. (2020). The future of higher education in the light of artificial intelligence transformations. International Journal of Higher Education, 9(3), 145–151. https://doi.org/10.5430/ijhe.v9n3p145

Broadbent, J., Panadero, E., Lodge, J. M., & de Barba, P. (2020). Technologies to enhance self-regulated learning in online and computer-mediated learning environments. In M. J. Bishop, E. Boling, J. Elen, & V. Svihla (Eds.), Handbook of research in educational communications and technology: Learning design (pp. 37–52). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-030-36119-8_3

Carby, N. (2023). Personalized feedback in a virtual learning environment. Journal of Educational Sciences, 6(1), 25–40. https://doi.org/10.31045/jes.6.1.3

Chen, Y. C., Hwang, G. J., & Lai, C. L. (2024). Motivating students to become self-regulatory learners: A gamified mobile self-regulated learning approach. Education and Information Technologies. Advance online publication. https://doi.org/10.1007/s10639-024-12462-z

Fajri, D. R. (2019). An analysis of student strategy in completing TOEFL reading comprehension test. Journal of English Language Teaching and Literature (JELTL), 2(2), 84–91. https://doi.org/10.47080/jeltl.v2i2.598

Fitria, T. N. (2022). An analysis of the students' difficulty in TOEFL prediction test of reading section. EDUJOURNAL: Jurnal Pendidikan dan Pembelajaran, 7(1), 45–56.

Hidayati, D., Widiati, U., Zen, E. L., & Astuti, U. P. (2025). Effectiveness of LMS-based ESP courses in fostering learning outcomes and self-efficacy. Studies in Linguistics, Culture, and FLT, 13(1), 96–119.

Maier, U., & Klotz, C. (2022). Personalized feedback in digital learning environments: Classification framework and literature review. Computers and Education: Artificial Intelligence, 3, 100080. https://doi.org/10.1016/j.caeai.2022.100080

Maisaroh, S., & Sofia, D. (2022). Web-based learning design and its implementation on TOEIC reading skills to measure the usability and learning outcome: A case study at Global Institute. Jurnal Sisfotek Global, 12(2), 94–100.

Nation, I. S. P. (2019). The different aspects of vocabulary knowledge. In S. Webb (Ed.), The Routledge handbook of vocabulary studies (pp. 15–29). Abingdon, England: Routledge.

Pratiwi, D. I., & Waluyo, B. (2022). Integrating task and game-based learning into an online TOEFL preparatory course during the COVID-19 outbreak at two Indonesian higher education institutions. Malaysian Journal of Learning and Instruction (MJLI), 19(2), 37–67.

Rahmati, J., Izadpanah, S., & Shahnavaz, A. (2021). A meta-analysis on educational technology in English language teaching. Language Testing in Asia, 11(1), 7. https://doi.org/10.1186/s40468-021-00121-w

Sailuddin, S. P. (2022). The effectiveness of TOEFL preparation course to improve students' reading comprehension. EDU Journal – English Department of UMMU Journal, 2(2), 46–52.

Sari, Y. A., Latief, S., & Umar Al Faruq, A. H. (2021). Student difficulties on structure and written expression section of TOEFL in higher education at Metro City. Curricula: Journal of Teaching and Learning, 6(1), 33–69.

Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611.

Sukandi, S. S. (2024). Action research on TOEFL ITP® tests and scores: Insights from TOEFL preparation course. RiELT Journal, 1(1), 59–84.

Sweller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1–16. https://doi.org/10.1007/s11423-019-09701-3

Wibowo, H. S. (2023). Pengembangan teknologi media pembelajaran: Merancang pengalaman pembelajaran yang inovatif dan efektif [Development of learning media technology: Designing innovative and effective learning experiences]. Yogyakarta, Indonesia: Tiram Media.

Zalha, F. B., Alfiatunnur, A., & Kamil, C. A. T. (2020). Strategies in dealing with the reading section of “TOEFL prediction”: A case of Aceh EFL learners. IJEE (Indonesian Journal of English Education), 7(2), 159–171.




DOI: https://doi.org/10.30743/ll.v1i1.12239

Refbacks

  • There are currently no refbacks.