In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…

High-quality feedback requires understanding of a student's work, insights into what concepts would help them improve, and language that matches the preferences of the specific teaching team. While Large Language Models (LLMs) can generate coherent feedback, adapting these responses to align with specific teacher preferences remains an open…

We propose a novel method for automated short answer grading (ASAG) designed for practical use in real-world settings. The method combines LLM embedding similarity with a nonlinear regression function, enabling accurate prediction from a small number of expert-graded responses. In this use case, a grader manually assesses a few responses, while…

The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…

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 fast development of artificial intelligence and emerging technologies, automatic recognition of students' facial expressions has received increased attention. Facial expressions are a kind of external manifestation of emotional states. It is important for teachers to assess students' emotional states and adjust teaching activities…

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…

Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…

Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…

In the evolving techno-educational landscape, it is crucial to reimagine transformative pedagogies based on techno-teacher collaboration to revolutionize teaching effectiveness and efficiency. Although the cutting-edge generative AI tool, Chat GPT, is speculated to be a revolutionary CALL (computer-assisted language learning) tool for teaching…

Scientific modeling is a vital educational practice that helps students apply scientific knowledge to real-world phenomena. Despite advances in AI, challenges in accurately assessing such models persist, primarily due to the complexity of cognitive constructs and data imbalances in educational settings. This study addresses these challenges by…

Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and instructor-defined knowledge components, making it challenging to integrate AI-generated educational content with…

In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…

Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…