A Study on the Rare Factors Exploration of Learning Effectiveness by Using Fuzzy Data Mining

Abstract

The phenomenon of low fertility has been negative impacted on the social structure of the educational environment in Taiwan. To increase the learning effectiveness of students became the most important issue for the Universities in Taiwan. Due to the subjective judgment of evaluators and the attributes of influenced factors are always fuzzy, it is not easy to measure the learning effectiveness by using the crisp values for the qualitative factors. In additional, the negative behaviors or the infrequent learning data (rare item sets) cannot easily excavate from educational database. Therefore, a systematic mining method is proposed here by combining fuzzy set theory with data mining technology to explore the key factors of learning effectiveness from the infrequent data. A case study implemented in this paper and showed that the proposed method can effectively find the important factors and valuable patterns from the survey data. The results of this paper can provide the important information for teachers to help students increase the learning effectiveness. Finally, the conclusions are addressed at the end of this paper.

Learning Behavior Based on Data Mining Technology

“…e structure of a typical BP neural network is shown in Figure 1, where the leftmost layer is the input layer, the rightmost layer is called the output layer, and layers in the middle are named hidden layers. Neurons in adjacent layers of the BP neural network are fully connected, but neurons within the same layer are not connected [17][18][19]. e three types of layers that make up the neural network are information for the neural system is in the input nodes.…”

Human Resource Allocation Based on Fuzzy Data Mining Algorithm

“…e association rule mining technology is applied to the electronic file management information system of university officials [22], and artificial neural network technology is applied to the evaluation process and integration with the system. It studies the necessity of establishing a human resource management system based on data mining technology [23][24][25][26]. It is based on this point that the solution of human resource management system began to pay attention to the application of data mining [27,28], pointing out that coal companies do not pay attention to the prediction and planning of talents, the brain drain is serious, the talent market development is not sound enough, and the talents are ignored.…”

The patterns of accessing learning management system among students

“…Different fields are applying data mining including government, banking, cybersecurity, entertainment, finance, hospital, engineering, biomedicine, education etc. [10][11].…”