Scientific Epistemology of Grade 10 Students in Validating the Period of a Pendulum
Mamdoh S. Laguindab, Bartolome L. Cagas
Asian Journal of Education and Social Studies · pp. 708–727 · Published 24 Jan 2026
10.9734/ajess/2026/v52i12809Abstract
Understanding how students justify, evaluate, and validate scientific knowledge is central to effective physics instruction, particularly in laboratory-based learning. This study examined the scientific epistemology of Grade 10 students from an advanced science high school in the Philippines as they validated the period of a simple pendulum within an investigative laboratory context. Employing a qualitative research design, data were collected from 30 students through a six-item open-ended questionnaire administered after a guided pendulum experiment. Students’ written responses were analyzed using thematic analysis and classified according to epistemic reasoning patterns, specifically formal epistemic reasoning and epistemic fragmentation, based on how students coordinated theory, evidence, and experimental procedures. The findings indicate that most students demonstrated formal epistemic reasoning when tasks explicitly required coordination between experimental procedures and theoretical models, particularly in varying pendulum length and angular amplitude, comparing experimental and theoretical values, and calculating experimental error. In contrast, epistemic fragmentation was more prevalent in contexts where intuitive reasoning conflicted with formal theory, most notably in explanations involving the mass of the pendulum bob. These results suggest that students’ epistemic reasoning is highly context-sensitive and shaped by the epistemic framing of laboratory tasks. The study highlights the role of sustained laboratory exposure and advanced science curricula in supporting students’ engagement in theory–evidence coordination. The findings have implications for physics laboratory instruction, emphasizing the importance of designing activities that emphasize epistemic aims such as model validation, justification, and uncertainty evaluation to foster deeper scientific reasoning.
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