Learn More
One of the most popular methods for modeling students' knowledge is Corbett and Anderson's[1] Bayesian Knowledge Tracing (KT) model. The original Knowledge Tracing model does not allow for individualization. Recently, Pardos and Heffernan [4] showed that more information about students' prior knowledge can help build a better fitting model and provide a(More)
Both Knowledge Tracing and Performance Factors Analysis, are examples of student modeling frameworks commonly used in AIED systems (i.e., Intelligent Tutoring Systems). Both of them use student correctness as a binary input, but student performance on a question might better be represented with a continuous value representing a type of partial credit.(More)
STAT6 plays a prominent role in adaptive immunity by transducing signals from extracellular cytokines. We now show that STAT6 is required for innate immune signaling in response to virus infection. Viruses or cytoplasmic nucleic acids trigger STING (also named MITA/ERIS) to recruit STAT6 to the endoplasmic reticulum, leading to STAT6 phosphorylation on(More)
An important aspect of Intelligent Tutoring Systems is providing assistance to students as well as assessing them. The standard state-of-the-art algorithms (Knowledge Tracing and Performance Factor Analysis) for tracking student knowledge, however, only look at the correctness of student first response and ignore the amount of assistance students needed to(More)
The goal of predicting student behavior on the immediate next action has been investigated by researchers for many years. However, a fair question is whether this research question is worth all of the attention it has received. This paper investigates predicting student performance after a delay of 5 to 10 days, to determine whether, and when, the student(More)