Precise item categorisation is essential in aligning exam questions with content domains outlined in assessment blueprints. Traditional methods, such as manual classification or supervised machine learning, are often time-consuming, error-prone, or limited by the need for large training datasets. This study presents a novel approach using…

Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…

Understanding students' multi-party epistemic and topic based-dialogue contributions, or how students present knowledge in group-based chat interactions during collaborative game-based learning, offers valuable insights into group dynamics and learning processes. However, manually annotating these contributions is labor-intensive and challenging.…

Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…

Purpose: This study examines existing automatic screening methods for developmental language disorder (DLD), a neurodevelopmental language deficit without known biomedical etiologies, focusing on languages, data sets, extracted features, performance metrics, and classification methods. Additionally, it summarizes the strengths and weaknesses of…

Student evaluations of teaching (SET) act as the primary means to gauge instructor effectiveness. Likewise, SETs provide the primary qualitative feedback to instructors via student comments. However, mostly students with strong feelings tend to write comments. Among the most recallable are toxic comments: comments that are unhelpful/hurtful in…

Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus on the study identification process, but tools to assist in analysis and categorization are also needed. One possibility is to use unsupervised automatic text clustering, in which each study is automatically assigned to one or more meaningful…

It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…

Automatic short-answer grading has been studied for more than a decade. The technique has been used for implementing auto assessment as well as building the assessor module for intelligent tutoring systems. Many early works automatically grade mainly based on the similarity between a student answer and the reference answer to the question. This…

Competency in skills associated with collaborative problem solving (CPS) is critical for many contexts, including school, the workplace, and the military. Innovative approaches for assessing individuals' CPS competency are necessary, as traditional assessment types such as multiple-choice items are not well suited for such a process-oriented…

Competency in skills associated with collaborative problem solving (CPS) is critical for many contexts, including school, the workplace, and the military. Innovative approaches for assessing individuals' CPS competency are necessary, as traditional assessment types such as multiple-choice items are not well suited for such a process-oriented…

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…

Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…

E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…

Massive open online courses (MOOCs) offer rich opportunities to comprehend learners' learning experiences by examining their self-generated course evaluation content. This study investigated the effectiveness of fine-tuned BERT models for the automated classification of topics in online course reviews and explored the variations of these topics…