A reliable response representation enhanced knowledge tracing method
Knowledge Tracing(KT)is a key task in educational data mining,aiming at modeling students'changing knowledge states over time to infer students'proficiency on concepts.However,most of existing knowledge tracing methods ignore the reliability and high-dimensional sparsity of the student-concept space based on the student-exercise-concept relationship,and do not combine the student's response to the exercise to generate a reliable response representation.To address the above issues,a reliable response representation enhanced knowledge tracing method is proposed.Specifically,firstly,the student-exercise space is divided into fine-grained student-exercise spaces based on the student's response records,and different student-concept spaces are obtained based on the exercise-concept space;secondly,the reliability of the student-concept space is obtained from both the relative reliability and absolute reliability of the student-concept space,and a reliable and low-dimensional student-concept space is obtained using dimensionality reduction methods;thirdly,the reliable response representation of the exercise is obtained by combining the student's response to the exercise and the ex-ercise representation method under two response conditions;finally,the student's knowledge state at different timesteps is evaluated using a long short-term memory network and the obtained reliable re-sponse representation.Experimental results on four real datasets demonstrate the effectiveness and in-terpretability of the proposed method.
knowledge tracingeducational data miningreliable response representationlong short-term memory network
万方数据
维普
