Ekt: Exercise-aware knowledge tracing for student performance prediction
For offering proactive services (eg, personalized exercise recommendation) to the students
in computer supported intelligent education, one of the fundamental tasks is predicting …
in computer supported intelligent education, one of the fundamental tasks is predicting …
A systematic review: machine learning based recommendation systems for e-learning
SS Khanal, PWC Prasad, A Alsadoon… - Education and Information …, 2020 - Springer
The constantly growing offering of online learning materials to students is making it more
difficult to locate specific information from data pools. Personalization systems attempt to …
difficult to locate specific information from data pools. Personalization systems attempt to …
A survey of knowledge tracing
High-quality education is one of the keys to achieving a more sustainable world. In contrast
to traditional face-to-face classroom education, online education enables us to record and …
to traditional face-to-face classroom education, online education enables us to record and …
Enhancing the prediction of student performance based on the machine learning XGBoost algorithm
ABSTRACT Performance Factors Analysis (PFA) is considered one of the most important
Knowledge Tracing (KT) approaches used for constructing adaptive educational …
Knowledge Tracing (KT) approaches used for constructing adaptive educational …
Dynamic key-value memory networks for knowledge tracing
Knowledge Tracing (KT) is a task of tracing evolving knowledge state of students with
respect to one or more concepts as they engage in a sequence of learning activities. One …
respect to one or more concepts as they engage in a sequence of learning activities. One …
On the expressive power of deep neural networks
We propose a new approach to the problem of neural network expressivity, which seeks to
characterize how structural properties of a neural network family affect the functions it is able …
characterize how structural properties of a neural network family affect the functions it is able …
[HTML][HTML] Statistical mechanics of deep learning
The recent striking success of deep neural networks in machine learning raises profound
questions about the theoretical principles underlying their success. For example, what can …
questions about the theoretical principles underlying their success. For example, what can …
Algorithmic fairness in education
RF Kizilcec, H Lee - The ethics of artificial intelligence in education, 2022 - taylorfrancis.com
Data-driven predictive models are increasingly used in education to support students,
instructors, and administrators, which has raised concerns about the fairness of their …
instructors, and administrators, which has raised concerns about the fairness of their …
Graph-based knowledge tracing: modeling student proficiency using graph neural network
Recent advancements in computer-assisted learning systems have caused an increase in
the research of knowledge tracing, wherein student performance on coursework exercises is …
the research of knowledge tracing, wherein student performance on coursework exercises is …
RKT: relation-aware self-attention for knowledge tracing
S Pandey, J Srivastava - Proceedings of the 29th ACM international …, 2020 - dl.acm.org
The world has transitioned into a new phase of online learning in response to the recent
Covid19 pandemic. Now more than ever, it has become paramount to push the limits of …
Covid19 pandemic. Now more than ever, it has become paramount to push the limits of …