Rinayanti Budi Harpeningtyas
Universitas PGRI Semarang

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Evaluating the Impact of Web-Assisted Teaching at the Right Level (TaRL) in Improving Mathematical Problem Solving Skills Rinayanti Budi Harpeningtyas; Nizaruddin; Ida Dwijayanti
Didaktika: Jurnal Kependidikan Vol. 14 No. 2 Mei (2025): Didaktika Jurnal Kependidikan
Publisher : South Sulawesi Education Development (SSED)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58230/27454312.1914

Abstract

This research was motivated by the observed low ability of students to solve mathematical problems effectively. To address this issue, the Teaching at the Right Level (TaRL) approach, which adapts instruction based on students’ current learning levels, was applied in combination with web-assisted learning tools to enhance engagement and accessibility. The web-assisted TaRL approach integrates adaptive teaching with online materials such as concept maps, interactive videos, and assessments tailored to student needs. The study aimed to evaluate the effect of this approach on students’ mathematical problem-solving skills. Using a posttest-only control group design, 70 students were purposively sampled and divided into an experimental group (34 students) receiving the web-assisted TaRL intervention, and a control group (36 students) undergoing conventional learning. The assessment consisted of three validated descriptive questions measuring problem-solving ability. Results showed that the experimental group achieved a higher average score (82.45) compared to the control group (65.65). Both groups met assumptions of normality and homogeneity, confirming the appropriateness of parametric testing. The independent samples t-test revealed a statistically significant improvement (p < 0.05) in the experimental group’s problem-solving skills. While these findings support the effectiveness of the web-assisted TaRL approach, limitations include the relatively small sample size and short intervention duration. Future research should consider larger, more diverse populations and explore long-term effects to strengthen generalizability and further optimize the integration of technology in adaptive learning.