Development of learning path map of work and energy for high schoolers by using cognitive diagnostic assessment
Kittitas Wancham 1 * , Kamonwan Tangdhanakanond 1
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1 Faculty of Education, Chulalongkorn University, Bangkok, THAILAND* Corresponding Author

Abstract

The conception of work and energy is fundamental to learning physics and is essential to learning other subjects. However, most students still lack knowledge and understanding of work and energy. This may be due to previous research that aimed to develop students using similar teaching methods without considering the individual knowledge state of each student. We, thus, sought to develop the mastery test on work and energy and the learning path map of work and energy using cognitive diagnostic assessment. Participants were 537 tenth graders in Bangkok, Thailand, which were chosen by the multistage random sampling. The mastery test on work and energy developed is divided into six attributes, i.e., (1) work, (2) power, (3) kinetic energy, (4) gravitational potential energy, (5) elastic potential energy, and (6) law of conservation of energy. The test exhibited good psychometric properties, which were evaluated based on item parameters, content validity, construct validity, concurrent validity, classification consistency index, and classification accuracy index. The significant finding was the development of the learning path map of work and energy. The map illustrates students’ learning progression in different attribute profiles regarding work and energy. It proves to be highly beneficial for teachers in designing personalized learning methods for individual students. Additionally, it allows for tracking the learning progress of students until they have a comprehensive understanding of work and energy in all its attributes.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2023, Volume 19, Issue 11, Article No: em2360

https://doi.org/10.29333/ejmste/13812

Publication date: 01 Nov 2023

Online publication date: 19 Oct 2023

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Article Downloads: 444

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