Validation of a digital tool for diagnosing mathematical proficiency

Author:

Junpeng Putcharee,Marwiang Metta,Chinjunthuk Samruan,Suwannatrai Prapawadee,Chanayota Kanokporn,Pongboriboon Kissadapan,Tang Keow Ngang,Wilson Mark

Abstract

This study was aimed to validate a digital tool for diagnosing mathematical proficiency in the Number and Algebra strand of 1,504 Thai seventh-grade students. Researchers employed a multidimensional approach, an extension of the Rasch model to measure its quality. A design-based research method was adopted to create the diagnostic tool which consists of four components, namely register system, input data, process system, and diagnostic feedback report. The diagnostic framework consists of 18 tasks encompassing 11 and 7 tasks in the Mathematical Procedures Dimension and Structure of the Observed Learning Outcome dimension, respectively. The results revealed that there is internal structure evidence of validity based on the comparison of model fit and the Wright map. The results also indicated that the reliability evidence and item fit are compliant with the quality of the digital tool as shown in the analysis of standard error of measurement and infit and outfit of the items. In conclusion, the developed digital tool can diagnose seventh-grade students’ multiple mathematical proficiencies in terms of accuracy, consistency, and stability. This implies that the digital tool can provide fruitful information, particularly to those intermediate and high mathematical proficiency levels because the error for estimating proficiency in each dimension was at the lowest value for those students.

Publisher

Institute of Advanced Engineering and Science

Subject

Education

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Adaptive Diagnostics for Customized Learning Pathways of Students in the Mathematical Structure of Observed Learning Outcomes: A Supervised Machine Learning Classification Algorithm;2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC);2024-07-02

2. Efficiency of Decision Tree Depth to Diagnose Mathematical Procedures in Number and Algebra for Seventh-grade Students;2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC);2024-07-02

3. Efficiency of Predicting Student Mathematical Proficiency Levels in Open-Ended Questions of Statistics and Probability Strand through Machine Learning;2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC);2024-07-02

4. Diagnosing Mathematical Procedures in Number and Algebra Strand of 7th Students using the Machine Learning Platform for Khon Kaen University demonstration secondary school (Suksasart);2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC);2024-07-02

5. Diagnosing Mathematical Procedures in Measurement and Geometry of 7th Grade Students Through Machine Learning Platform for Demonstration School of Khon Kaen University, Thailand, Secondary Section (Mor Din Daeng);2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC);2024-07-02

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