Development of a Real-time Digital Learning Platform for Diagnosing Degrees of Mathematical Competency

The research aims to develop and verify a real-time digital learning platform for diagnosing the degree of mathematical competency of seventh-grade students. A total of 1,559 students from four regions of Thailand and six experts participated in this research. The researchers employed a design-based approach and the Multidimensional Coefficient Multinomial Logit Model to evaluate the effectiveness of the real-time digital learning platform. The measurement tool consists of two aspects, namely mathematical measures and the construction of knowledge dimensions, with 58 items to simulate students’ responses to the three respective content constituents: number and algebra, measurement and geometry, and statistics and probability. The findings showed that the multidimensional model offered a significantly better statistical fit in measurement, geometry, statistics, and probability, while numbers and algebra fit better in the unidimensional model. There were positive, strong, and significant correlations between the dimensions. The findings indicated that all items fit the OUTFIT MNSQ and INFIT MNSQ, which are between 0.75-1.33. The findings revealed that the internal structure when it came to evaluating the degrees of students’ mathematical competency using the Wright map and the Multidimensional Test Response Model conformed with the quality of the digital learning platform in terms of its usefulness, accuracy, and feasibility. This real-time digital learning platform for diagnosing the degree of mathematical competency can be accessed from anywhere with an internet connection, making education more accessible to a wider audience, including individuals in remote areas or those with physical disabilities.