Papers by Author: Jeng Ming Yih

Abstract: Knowledge Management of Mathematics Concepts was essential in educational environment. The purpose of this study is to provide an integrated method of fuzzy theory basis for individualized concept structure analysis. This method integrates Fuzzy Logic Model of Perception (FLMP) and Interpretive Structural Modeling (ISM). The combined algorithm could analyze individualized concepts structure based on the comparisons with concept structure of expert. The empirical data is Basic Mathematic test of Junior College students. The object of concept advanced interpretive structural modeling (CAISM) is to provide individualized hierarchy structure of knowledge of examinees based on response patterns of tests. It shows that knowledge structures will be feasible for remedial instruction and this procedure will also useful for cognition diagnosis.

Abstract: The purpose of this study is to compare the reliability of Likert scale between crisp and fuzzy data. The survey data is simulated based on two kinds of questionnaire data. They are questionnaire of crisp data and fuzzy data respectively. According to the viewpoints of fuzzy logic, human thinking is multi-value and fuzzy data will be more appropriate for survey. Therefore, it is proposed that the reliability from fuzzy data will be higher. Results of the simulation show that reliability of fuzzy data performs better than crisp data. Based on the findings of this study, some suggestions and recommendations are discussed for future research.

Abstract: The purpose of this study is to investigate the performance of mathematics reading based on fuzzy clustering. Mathematics reading proficiency is an importance issue which is related to the reading comprehension, mathematics achievement and mathematics literacy. Theoretical foundation of mathematics reading consists of three components, which are general reading comprehension, prior knowledge of mathematics and specific skills of mathematics. The subject is sixth graders. The researchers develop internet system of mathematics assessment and adopt fuzzy clustering to appropriately classify students. Results show that three clusters are the best and there exist characteristics and differences among clusters. Based on the findings, some recommendations and suggestions for future research are provided.

Abstract: The popular fuzzy c-means algorithm based on Euclidean distance function converges to a local minimum of the objective function, which can only be used to detect spherical structural clusters. Gustafson-Kessel clustering algorithm and Gath-Geva clustering algorithm were developed to detect non-spherical structural clusters. However, Gustafson-Kessel clustering algorithm needs added constraint of fuzzy covariance matrix, Gath-Geva clustering algorithm can only be used for the data with multivariate Gaussian distribution. In GK-algorithm, modified Mahalanobis distance with preserved volume was used. However, the added fuzzy covariance matrices in their distance measure were not directly derived from the objective function. In this paper, an improved Normalized Supervised Clustering Algorithm Based on FCM by taking a new threshold value and a new convergent process is proposed. The experimental results of real data sets show that our proposed new algorithm has the best performance. Not only replacing the common covariance matrix with the correlation matrix in the objective function in the Normalized Supervised Clustering Algorithm.

Abstract: The purpose of this study is to use ordering theory (OT) to determine existing hierarchies among items with specifically learning style. Furthermore, an empirical data of capacity concepts testing for algebra learning was analyzed based on the integrated method student-problem chart (S-P Chart) is adopted to classify all students into proper learning styles. Cooperating S-P chart and OT are as an integrated method of cognition diagnosis. The empirical data is algebra concepts test of university students. The results showed that cognition diagnosis would be feasible for remedial teaching and design of teaching materials. Finally, some suggestions and recommendations for future research and educational research are provided.

Abstract: The main purpose of this paper is to analyze the operation strategies of the world’s top 20 shipping companies by using SWOT (Strength, Weakness, Opportunity, and Threat) analysis method. Finally, some conclusions and suggestions are given to shipping companies, port managers, and departments of governmental maritime transportation as references.

Abstract: The purpose of this study is to integrate two methodological approaches to explore concept structures. One approach is student-problem chart (S-P chart) and ordering theory (OT) and the other is fuzzy clustering and item relational structure (IRS). S-P chart is adopted to classify all students into proper learning styles. OT is to determine hierarchies of concept structures. Fuzzy clustering is soft computation to cluster features of students and combine IRS so as to determine the precondition and ordering relationship among items. The empirical data is statistics concepts test of university students. The results show that integration of these two approaches is feasible for cognition diagnosis and would be helpful for remedial instruction. Finally, some suggestions and recommendations for future research and educational research are provided.

Abstract: The purpose of this study was to cooperate student-problem chart (S-P Chart) and ordering theory (OT) as an integrated method of cognition diagnosis. S-P chart was used to classify students into proper learning styles, In order to use OT to determine existing hierarchies among items with specifically learning style. Furthermore, an empirical data of capacity concepts testing for fundamental mathematics learning was analyzed based on the integrated method. The results showed that cognition diagnosis would be feasible for remedial teaching and design of teaching materials.

Abstract: The purpose of this study is to integrate pathfinder and item response theory so as to manage concept structures. Concept structure is one important issue of knowledge management as to human knowledge storage. Pathfinder and item response theory are based on graph theory and psychometrics respectively and this integrated method should be feasible to represent concept structures. Besides, fuzzy clustering technique is adopted to provide features of concept structures based on homogeneity of sample. In this study, the empirical data is the assessment of linear algebra for university students. The important concepts of linear algebra consist of subspace, spanning, linear independent, R² and R³ and many literatures indicate concept structures of linear algebra will influence advanced mathematics. However, little is known about the concept structure and cognition diagnosis on linear algebra. In this study, it shows that lack of concrete examples in general dimensional space will prevent the development of the general theory. There are some limitations for students to use some materials to clarify complicated mathematic concepts perfectly. Most students could not be able to use the geometric insight and apply the Pythagorean of R² or R³. It shows that methodology of the pathfinder and item response theory will reveal important information of concept structures for students. In addition, fuzzy clustering could distinguish characteristics of concept structures on linear algebra. Finally, some limitations and suggestions as to this study are discussed.