Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

In the last few years, a large number of automatic evaluation metrics have been proposed for
evaluating Natural Language Generation (NLG) systems. The rapid development and …

In this paper, we argue that a particular set of issues mars traditional assessment practices.
They may be difficult for educators to design and implement; only provide discrete snapshots …

Generating short answer questions is a popular form of learnersourcing with benefits for
both the students' higher-order thinking and the instructors' collection of assessment items …

Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural
Language Processing. The goal of this field is to develop systems for answering the …

Multiple-choice questions with item-writing flaws can negatively impact student learning and
skew analytics. These flaws are often present in student-generated questions, making it …

Natural language processing technology has made significant progress in recent years,
fuelled by increasingly powerful general language models. This has also inspired a sizeable …

Questioning plays a vital role in education, directing knowledge construction and assessing
students' understanding. However, creating high-level questions requires significant …

The deliberative potential of online platforms has been widely examined. However, little is
known about how various interface-based reflection nudges impact the quality of …

Automatic generation of math word problems (MWPs) is a challenging task in Natural
Language Processing (NLP), particularly connecting it to real-life problems because it can …