Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…

With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…

Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…

Pre-emption describes a system of automated knowledge creation and intervention that steers the present towards a desirable future, by building on knowledge derived from the past. Folding together temporalities makes it impossible to disprove pre-emption. It is increasingly featured within EdTech, introducing new forms of automated governance into…

Selecting courses in an open-curriculum education program is a difficult task for students and academic advisors. Course recommendation systems nowadays can be used to reduce the complexity of this task. To control the recommendation error, we argue that course recommendations need to be provided together with "statistical" confidence.…

The recommender system has gained research attention from education research communities mainly due to two main reasons: increasing needs for personalized learning and big data availability in the education sector. This paper presents a hybrid user-collaborative, rule-based filtering recommendation system for education context. User profiles are…

Extensive literature in artificial intelligence in education focuses on developing automated methods for detecting cases in which students struggle to master content while working with educational software. Such cases have often been called "wheel-spinning," "unproductive persistence," or "unproductive struggle." We…

Recent advances in Artificial Intelligence (AI) have sparked renewed interest in its potential to improve education. However, AI is a loose umbrella term that refers to a collection of methods, capabilities, and limitations--many of which are often not explicitly articulated by researchers, education technology companies, or other AI developers.…