Design of English reading cognitive evaluation system based on G-DINA model and fuzzy cognitive graph network

Abstract

Under the background of globalization, English reading ability, as an important language skill, has attracted more and more attention. Traditional English reading evaluation methods often ignore the cognitive process and knowledge structure of candidates. Therefore, this paper proposes a cognitive evaluation system of English reading based on Generalized DINA model and fuzzy cognitive graph network, aiming at improving the accuracy and effectiveness of reading comprehension. Firstly, the reading data of 1000 English learners are analyzed, and the correlation diagram between knowledge points and cognitive process is constructed. Through G-DINA model, the system can accurately identify the candidates’ mastery of specific knowledge points, and analyze the interaction between different knowledge points by using fuzzy cognitive graph network. When compared to traditional methods, the system demonstrates a 15% enhancement in the accuracy of reading evaluations. Furthermore, by visualizing the structure of knowledge, educators can attain a more lucid comprehension of students’ cognitive development and identify their weaknesses, enabling the formulation of more precisely targeted teaching strategies. Leveraging the network model of a fuzzy cognitive graph, the system possesses the capability to dynamically adapt the evaluation dimensions, thereby rendering the assessment outcomes more comprehensive and multi-dimensional. The cognitive evaluation system of English reading based on G-DINA model and fuzzy cognitive graph network not only provides a new perspective for English reading evaluation, but also opens up a new direction for the future research of intelligent education.