Validation of cognitive models for subtraction of time involving years and centuries

Author:

CHIN Huan1ORCID,CHEW Cheng Meng1ORCID

Affiliation:

1. universiti sains malaysia

Abstract

Years and Centuries are the measurement units used to quantify a longer time duration, while subtraction is the operation required to determine the duration based on two given time points. However, subtraction of time is a difficult skill to be mastered by many elementary students. To identify the root cause of the student's failure in performing subtraction involving the unit of time, we developed and validated the three cognitive models related to this skill by conducting a descriptive study which involved 119 Grade Five students from three Malaysian elementary schools. The cognitive diagnostic assessment developed based on the three cognitive models was used to elicit the participants' responses. Then, Attribute Hierarchy Method and Classical Test Theory were employed to analyse the data. The findings indicated that the hierarchical structures of all cognitive models are supported by the student's responses. The three student-based cognitive models were also highly consistent with the corresponding expert-based cognitive models. The cognitive models developed could guide diagnostic assessment development and diagnostic inference making.

Funder

UNIVERSITI SAINS MALAYSIA

Publisher

International Journal of Assessment Tools in Education

Subject

General Medicine

Reference70 articles.

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2. Alves, C.B. (2012). Making diagnostic inferences about student performance on the Alberta education diagnostic mathematics project: An application of the Attribute Hierarchy Method. (Publication No. 919011661) [Doctoral Thesis, University of Alberta, Ann Arbor, Canada]. ProQuest Dissertations and Theses database.

3. Australian Curriculum Assessment and Reporting Authority [ACARA]. (2017). Numeracy learning progression and history. https://www.australiancurriculum.edu.au/media/3666/numeracy-history.pdf

4. Brace, N., Doran, C., Pembery, J., Fitzpatrick, E., & Herman, R. (2019). Assessing time knowledge in children aged 10 to 11 years. International Journal of Assessment Tools in Education, 6(4), 580-591.

5. Briggs, D.C., & Kizil, R.C. (2017). Challenges to the use of artificial neural networks for diagnostic classifications with student test data. International Journal of Testing, 17(4), 302-321.

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