Fuzzy Structural Modeling of Learning Tasks by a Number of Teachers.

Abstract

Structural modeling of learning tasks is an important process of designing classes. Designing classes is divided into three phases. The first phase is to determine a structural model which shows how the learning tasks are related. This is called the structural modeling of learning tasks. The second phase is to determine the sequence of learning tasks using the structural model obtained in the first phase. The third phase is to formulate an actual curriculum using the sequence decided on. In this paper, a method is proposed to obtain the structural model of learning tasks when a number of teachers plan the lessons. Let L_p be the set of learning tasks. Each teacher evaluates numerically the difficulty of each learning task. Structural model, that is, pseudo-ordered relation R on L_p, of each teacher can be calculated by applying a fuzzy implication function to the data. Teachers are assigned into clusters based on the evaluation for each learning task. Finally, FISM procedure is introduced to develop a consensus model between clusters that will help to determine the best curriculum structure.