T-SKIRT: Online Estimation of Student Proficiency in an Adaptive Learning System

02/14/2017
by   Chaitanya Ekanadham, et al.
1

We develop T-SKIRT: a temporal, structured-knowledge, IRT-based method for predicting student responses online. By explicitly accounting for student learning and employing a structured, multidimensional representation of student proficiencies, the model outperforms standard IRT-based methods on an online response prediction task when applied to real responses collected from students interacting with diverse pools of educational content.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/09/2020

Predicting Student Performance in Interactive Online Question Pools Using Mouse Interaction Features

Modeling student learning and further predicting the performance is a we...
research
04/08/2016

Back to the Basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation

Estimating student proficiency is an important task for computer based l...
research
05/26/2019

Adaptive Learning Material Recommendation in Online Language Education

Recommending personalized learning materials for online language learnin...
research
05/25/2018

An Improved Phrase-based Approach to Annotating and Summarizing Student Course Responses

Teaching large classes remains a great challenge, primarily because it i...
research
07/13/2022

Wide Deep Learning for Judging Student Performance in Online One-on-one Math Classes

In this paper, we investigate the opportunities of automating the judgme...
research
09/20/2018

Neural network approach to classifying alarming student responses to online assessment

Automated scoring engines are increasingly being used to score the free-...

Please sign up or login with your details

Forgot password? Click here to reset