Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…

Large Language Models (LLM) -- powerful algorithms that can generate and transform text -- are set to disrupt language learning education and text-based assessments as they allow for automation of text that can meet certain outcomes of many traditional assessments such as essays. While there is no way to definitively identify text created by this…

Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…

We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…

Modern society demands renewed attention on the competencies required to best equip students for a dynamic and uncertain future. We present exploratory work based on the premise that metacognitive and reflective competencies are essential for this task. Bringing the concepts of metacognition and reflection together into a conceptual model within…

The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary…

We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given…

This work covers topics in event coreference and event classification from spoken conversation. Event coreference is the process of identifying descriptions of the same event across sentences, documents, or structured databases. Existing event coreference work focuses on sentence similarity models or feature based similarity models requiring slot…

Three experiments examine whether a naturalistic reading task can induce long-lasting changes of syntactic patterns in memory. Judgment of grammatical acceptability is used as an indirect test of memory for sentences that are identical or only syntactically similar to those read earlier. In previous research (Luka & Barsalou, 2005) both sorts of…

This article addresses issues in embodied sentence processing from a "cognitive neural systems" approach that combines analysis of the behavior in question, analysis of the known neurophysiological bases of this behavior, and the synthesis of a neuro-computational model of embodied sentence processing that can be applied to and tested in the…