Various studies empirically proved the value of highly informative feedback for enhancing
learner success. However, digital educational technology has yet to catch up as automated …

Automatically scoring student answers is an important task that is usually solved using
instance-based supervised learning. Recently, similarity-based scoring has been proposed …

This paper investigates crosslingual content scoring, a scenario where scoring models
trained on learner data in one language are applied to data in a different language. We …

Despite the success of Siamese encoder models such as sentence transformers (ST), little is
known about the aspects of inputs they pay attention to. A barrier is that their predictions …

This study leverages natural language processing (NLP) to deepen our understanding of
how students integrate their ideas about genetic inheritance while engaging in an adaptive …

Pre-trained large language models (PLMs) are adaptable to a wide range of downstream
tasks by fine-tuning their rich contextual embeddings to the task, often without requiring …

Essay writing tests, integral in many educational settings, demand significant resources for
manual scoring. Automated essay scoring (AES) can alleviate this by automating the …

Recent investigations in automated essay scoring research imply that hybrid models, which
combine feature engineering and the powerful tools of deep neural networks (DNNs), reach …

Abstract Short-Answer Grading (SAG) is a time-consuming task for teachers that automated
SAG models have long promised to make easier. However, there are three challenges for …

Evaluating students' textual response is a common and critical task in language research
and education practice. However, manual assessment can be tedious and may lack …