Assessing Students Understanding of Chemical Bonds Material by Rasch Modeling

Almubarak Almubarak(1*), Parham Saadi(2), Restu Prayogi(3), Pamela Paula Maldini(4)

(1) Faculty of Teacher Training and Education, Universitas Lambung Mangkurat
(2) Faculty of Teacher Training and Education, Universitas Lambung Mangkurat
(3) Faculty of Teacher Training and Education, Universitas Lambung Mangkurat
(4) Faculty of Management and Business, Tampere University of Applied Sciences
(*) Corresponding Author

Abstract

This study aimed to assess high school student’s understanding of Banjarmasin by Rasch modeling, preci-sely the cognitive aspect. The research method was descriptive with a quantitative approach to assess the pattern of reactions and symptoms of Rasch data. According to the research findings, the person reliability (students) was +0.66 based on the Rasch modeling analysis, with the criterion satisfactory, indicating that the students knowledge was adequate. At the same time, Cronbachs’ alpha score had a value of +0.71 and met the criteria of excellent. In addition, the students with the highest level of understanding were coded 127P12B with a logit value (person measure) of 2.52 and average students with logit value of -0.77 or <0. In contrast, the students with low abilities were coded 030P10B and 059L11B (same logit value, -3.27 or <0). Other data were INFIT MNSQ and OUTFIT MNSQ (person) with average values of +0.99 and +1.14 (closer to 1, the better), while the INFIT and OUTFIT ZSTD values were -0.1 and 0.0 respectively (closer to 0, better). The most difficult question was Q16, which had a logit score of 1.96; students’ logit values carried this question. Students were regarded to have appropriate knowledge even though their ability excee-ded the problem ability. In conclusion, the Rasch model-based pre-learning evaluation was found to be useful in measuring students’ cognitive grasp of chemical bonding material. This study could serve as the primary reference for teachers in assessing students’ level of knowledge before they begin learning. In addi-tion to interpreting student knowledge through various Rasch data presentations, a study of the structure of questions with varying difficulty levels could be used to assess the full group of students’ understanding of chemistry.

Keywords

cognitive aspect; learning progress; pre-learning evaluation; rasch modeling

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DOI: 10.23917/ijolae.v5i3.22242

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