Research On Directed Graph Of Problem Space Based On Conjunctive Skill Function

Based on the conjunctive skill function.this paper deeply studies the learning evaluation of students with different ability states.According to the characteristics of students’ thinking skills.This article categorizes students into high-level thinking skill features[HOTS]and low-level thinking skill features[LOTS]based on whether they fully master a certain skill,and gives the coverage description of students’ ability states in different knowledge states.First of all.for the initial state in the problem space.this paper gives the equivalent characterization of its atoms in the knowledge structure by using approximation operators.Secondly.this paper describes the learning path in the knowledge space using the maximum description in the covering.Moreover.algorithms were used to describe the corresponding ability states of two thinking skills and the skills that need to be further mastered from one knowledge state to another.Thirdly,for these two types of thinking skills.we use the covering method to describe the covering characterization of the ability state associated with the behavior state.and then give the algorithm design of four characterization,and use Python language to design corresponding programs and carry out data experiments to illustrate its effectiveness.Finally,based on the above research results.this paper constructs a directed graph of problem space based on conjunctive skill function.