Mapping Students’ Cognitive Profiles on Newtonian Mechanics: A Rasch-Based Analysis via Four-Tier Digital Diagnostic Assessment

Authors

DOI:

https://doi.org/10.58524/oler.v6i1.1218

Keywords:

Cognitive profile, Diagnostic assessment, Four-tier instrument, Newtonian Mechanics, Rasch Model

Abstract

This study aims to develop a four-tier digital diagnostic instrument based on Google Forms and utilize it to map the cognitive ability profiles of high school students on Newton's Second Law across six levels of the Revised Bloom's Taxonomy. This study adopted a Research and Development design using the Research Design and Development model, and the resulting instrument was administered to 92 10th-grade students at a public high school in Bandar Lampung. Content validity was assessed by three experts with an average validity of 95.23%, while psychometric quality was analyzed using the Rasch Partial Credit Model through Ministep 5.10.0.0 based on 75 response records, resulting in a person reliability of 0.86 and a person separation of 2.47, sufficient to differentiate between student ability strata. Since each cognitive level is represented by only a few items, the overall psychometric quality of the instrument was evaluated using Rasch analysis, while the overall and Bloom-level cognitive profiles were mapped descriptively using achievement percentages. Profile mapping revealed high overall performance. Student achievement remained stable at the remembering, understanding, and applying levels, but declined at the analyzing and evaluating levels. C5 emerged as the lowest point, with significant student accumulation in the Sufficient category, particularly in reasoning about the role of friction and resultant force under balanced force conditions. This tiered profile allows teachers to design remediation that targets cognitive levels where students' understanding is weak, rather than simply re-teaching the material in its entirety.

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2026-03-30

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Mapping Students’ Cognitive Profiles on Newtonian Mechanics: A Rasch-Based Analysis via Four-Tier Digital Diagnostic Assessment. (2026). Online Learning In Educational Research (OLER), 6(1), 277-296. https://doi.org/10.58524/oler.v6i1.1218