Student personalized time interval perception attention mechanism knowledge tracking method

Abstract

The invention discloses a student personalized time interval perception attention mechanism knowledge tracking method, which comprises the following steps of: 1) collecting historical interaction data of student learning and timestamps for completing learning, and designing and realizing a student learning time interval relation matrix; 2) carrying out vector coding on the exercise sequence, the learning sequence, the absolute position and the personalized time interval; 3) establishing a time-aware attention mechanism to calculate the influence weight of the historical completed exercises on the subsequent new exercises, and summarizing the initial knowledge state of each node student based on the weight; and 4) fusing the preliminarily summarized historical knowledge states of the students by using a full connection layer, and tracking continuously changing knowledge states in the learning process of the students. Compared with other technologies, the method has the advantages that different time intervals for students to practice each question are effectively utilized, different knowledge mastering conditions of different students under the same learning sequence are mined, and the knowledge tracking accuracy is improved.

Description

technical field [0001] The invention specifically relates to a student's personalized time interval perception attention mechanism knowledge tracking method. Background technique [0002] With the further development of educational informatization, a large number of online learning systems such as Massive Open Online Course (MOOC) platform and Online Judge (OJ) system have emerged. In general, these platforms provide students with rich learning resources (such as lessons, exercises, lectures) and an open environment for them to learn and practice knowledge at their own pace. The advantages of autonomy and convenience have attracted public attention and attention. In response to this problem, an effective solution is to provide personalized services in the online learning system to improve students' learning experience. One of the most basic tasks is knowledge tracking. [0003] Knowledge tracking is to model students' knowledge status based on historical data, which repre...

AI Technical Summary

Problems solved by technology

However, the influence of learning curve and forgetting curve on knowledge tracking is ignored

In the learning sequences of different students, there will be some identical learning sequence fragments. Using the existing methods, it will be assumed that students have the same mastery of these exercises or knowledge points, which is contrary to reality.

Images