Profiling students' critical thinking skills and the implementation of Problem-Based Learning using innovative digital modules on static fluid concepts
This research aims to determine the profile of students' critical thinking skills and the application of Problem-Based Learning using three-dimensional digital modules, particularly in physics education focusing on static fluid material. Preliminary research with a sample of 106 students employs research methods including critical thinking skills tests, student response surveys, and interviews with students and teachers. The findings were analyzed using qualitative descriptive data analysis. The results of this research are as follows: Questionnaire responses reveal that students' critical thinking skills are predominantly in the low category, with 100 students in the low category, six in the medium category, and none in the high category; Among critical thinking skills, strategy and tactics rank the lowest; Teachers have implemented Problem-Based Learning through active teaching strategies, such as presentations and open-ended questions, to improve students' critical thinking skills. However, three-dimensional digital book media have not yet been utilized in physics learning; and the application of a Problem-Based Learning model supported by three-dimensional digital modules is expected to improve students' critical thinking skills in physics education. This study highlights the need for innovative learning approaches to enhance students' critical thinking skills, especially in physics education. The integration of Problem-Based Learning with three-dimensional digital modules offers significant potential for addressing this need.
Authors
- Binar Kurnia Prahanı (ORCID: https://orcid.org/0000-0002-5606-6629)
- Anisa Rizky
Institutions
- Universitas Negeri Surabaya (ID)
Publication Details
- Journal
- Advances in Mobile Learning Educational Research
- Published
- 2024-12-26
- DOI
- https://doi.org/10.25082/amler.2025.01.002
- Citations
- 2
- Primary Topic
- Teaching and Learning Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.82