Pre-Service Mathematics Teacher Perception of Teaching Fraction
This study aims to examine pre-service mathematics teachers’ perceptions of fraction teaching. A total of 235 mathematics education students from three universities in Indonesia participated in this study. Data were collected through an online questionnaire covering perceptions regarding the importance of fraction teaching, conceptual understanding, and the chosen learning approach. Data analysis was conducted quantitatively through descriptive and inferential analysis. The results showed that most pre-service teachers had positive perceptions of the importance of fraction teaching as a foundation for advanced mathematical understanding. They also showed a tendency to choose a teaching approach based on visual modeling and the use of real contexts to help students understand the concept of fractions. In addition, more positive perceptions were correlated with a tendency to apply varied and conceptual understanding-oriented learning strategies. However, further findings showed a discrepancy between normative perceptions and pre-service teachers’ personal beliefs regarding their ability to use visual representations, especially in teaching multiplication and division of fractions. Although they believed in the importance of a visual representation-based approach, most respondents felt that they were not yet proficient enough in implementing the strategy effectively. These findings indicate the importance of strengthening practical competence in the use of visual representations during pre-service education. This research contributes to the development of mathematics teacher education curriculum, especially in strengthening conceptual understanding, pedagogical competence of content, and implementation skills of prospective teachers in teaching fractions, so that they are in line with the learning needs of students in the classroom.
Institutions
- State University of Semarang (ID)
- Universitas Negeri Surabaya (ID)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-23
- DOI
- https://doi.org/10.5281/zenodo.15726653
- Primary Topic
- Complex Network Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00