Computerized adaptive testing (CAT) is a form of personalized testing th...
We study the problem of generating arithmetic math word problems (MWPs) ...
Knowledge tracing (KT) refers to the problem of predicting future learne...
Knowledge tracing (KT) models, e.g., the deep knowledge tracing (DKT) mo...
Deep neural networks achieve state-of-the-art performance for a range of...
The 2016 United States presidential election has been characterized as a...
Social learning, i.e., students learning from each other through social
...
The Rasch model is widely used for item response analysis in application...
Phase retrieval refers to the problem of recovering real- or complex-val...
Phase retrieval deals with the recovery of complex- or real-valued signa...
Probit regression was first proposed by Bliss in 1934 to study mortality...
An important, yet largely unstudied, problem in student data analysis is...
Sensor selection refers to the problem of intelligently selecting a smal...
While computer and communication technologies have provided effective me...
The recently proposed SPARse Factor Analysis (SPARFA) framework for
pers...
Machine learning offers novel ways and means to design personalized lear...
We propose SPARFA-Trace, a new machine learning-based framework for
time...
Modern machine learning methods are critical to the development of
large...
We develop a new model and algorithms for machine learning-based learnin...