Multi-Factors Aware Dual-Attentional Knowledge Tracing

08/10/2021
by   Moyu Zhang, et al.
1

With the increasing demands of personalized learning, knowledge tracing has become important which traces students' knowledge states based on their historical practices. Factor analysis methods mainly use two kinds of factors which are separately related to students and questions to model students' knowledge states. These methods use the total number of attempts of students to model students' learning progress and hardly highlight the impact of the most recent relevant practices. Besides, current factor analysis methods ignore rich information contained in questions. In this paper, we propose Multi-Factors Aware Dual-Attentional model (MF-DAKT) which enriches question representations and utilizes multiple factors to model students' learning progress based on a dual-attentional mechanism. More specifically, we propose a novel student-related factor which records the most recent attempts on relevant concepts of students to highlight the impact of recent exercises. To enrich questions representations, we use a pre-training method to incorporate two kinds of question information including questions' relation and difficulty level. We also add a regularization term about questions' difficulty level to restrict pre-trained question representations to fine-tuning during the process of predicting students' performance. Moreover, we apply a dual-attentional mechanism to differentiate contributions of factors and factor interactions to final prediction in different practice records. At last, we conduct experiments on several real-world datasets and results show that MF-DAKT can outperform existing knowledge tracing methods. We also conduct several studies to validate the effects of each component of MF-DAKT.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/18/2022

DAGKT: Difficulty and Attempts Boosted Graph-based Knowledge Tracing

In the field of intelligent education, knowledge tracing (KT) has attrac...
research
12/09/2020

Improving Knowledge Tracing via Pre-training Question Embeddings

Knowledge tracing (KT) defines the task of predicting whether students c...
research
09/03/2023

Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing

The Knowledge Tracing (KT) task plays a crucial role in personalized lea...
research
02/14/2023

Enhancing Deep Knowledge Tracing with Auxiliary Tasks

Knowledge tracing (KT) is the problem of predicting students' future per...
research
07/26/2020

Deep Knowledge Tracing with Convolutions

Knowledge tracing (KT) has recently been an active research area of comp...
research
01/18/2023

Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training

Understanding mathematical questions effectively is a crucial task, whic...
research
06/13/2020

HGKT : Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing

Knowledge tracing (KT) which aims at predicting learner's knowledge mast...

Please sign up or login with your details

Forgot password? Click here to reset