Phuoc-Hai Nguyen

Using the Combination of GM(1,1) and Taylor Approximation Method to Predict the Academic Achievement of Student

The purpose of this study is to predict the academic achievement of student based on the combination of GM(1,1) and Taylor approximation method(abbreviated as T-GM(1,1)). The prediction model combined the first-order two variables grey differential equation model from grey system theory and Taylor approximation method from approximation optimization theory. This combined model can obtain the most optimal predicted value by multi-times approximate calculation. In addition, the researchers used MATLAB software to build a MATLAB toolbox for the prediction model based on GM(1,1) and T-GM(1,1). The experimental results showed that T-GM(1,1) can be adjusted repeatedly until reaches the optimal values and makes the predicted error reduce to the minimum. The comparison of the obtained results with the original GM(1,1) showed that T-GM(1,1) is a good alternative for parameters optimization of this prediction model.

RGSP Toolbox 1.0 for Educational Achievement

The main purpose of this research is to develop a toolbox for GSP chart and Rasch GSP methods. Through GSP chart analysis, teachers get information to diagnose the learning status of students and the quality of items. Rasch GSP provides information to assess the quality of the classes and test quality. The RGSP Toolbox 1.0 developed by this study is not a toolbox that implements calculation according to the basic steps of the two above methods. In order to increase the application range of the toolbox, this study has also proposed and executed a number of improvements. So, the RGSP Toolbox 1.0 is a useful tool to support teachers and researchers in educational achievement. This toolbox can quickly calculate and give exact results, draw graphs clearly. In addition, a graphical user interface (GUI) is also designed to be easy for use. The toolbox not only supplies researchers with big support in their research process but also can provide feedbacks about teaching and learning for teachers and students. So students can make reasonable adjustments for learning activity and teachers have an effective reference for guidance of learning.

GSM-RGSM Software and Its Application in Educational Measurement

Grey Structural Modeling (GSM) is an effective tool for analyzing complex systems and has been used in many educational researches in recent years. This study developed a tool to determine the relational structure between items and relational structure between students according to the GSM method. GSM-RGSM software, which is the result of this study, was developed by the MATLAB language. The software processes the data which is the result of a text and then provides results in graphs. GSM-RGSM software will help the user to reduce the complex mathematical calculations when using GSM method and provide results accurately and quickly. A graphical user interface is also designed to help users quickly become familiar and easy to use software. This software also provides RGSM graph, which is considered as a special case of the GSM. In this paper, a practical example of using GSM-RGSM software to analyze math test results is used as illustration for the application of the software in educational

Using Grey Student-Problem Chart in the Evaluation of Tests with Large Data Sets

High effective assessment methods need to be designed to reflect the variety of achievement targets in teaching and learning process. The purpose of this paper is to propose using Grey Student Problem (GSP) chart in evaluating the test with large data sets. This method applied criteria reasonably to evaluate data on the basis of statistics and sorting in order of priority criteria. The experimental results of this method have been compared with results processed by previous model as Item Response Theory (IRT) one-parameter logistic (1PL) model to determine the suitability of method. This comparison result showed that the fit between two methods was very high, moreover, the proposed method showed its advantage that was simple and easy to apply. Especially, it was not only best for handling small samples but also applicable for large statistical data. This new assessment method is a more convenient way for teachers and education managers to carry out the evaluation in teaching and learning process.