This paper presents a model for automatically selecting and allocating secondary education teachers to schools while considering various factors such as the diversity of sections and lessons, school distances, teacher specializations, teaching workloads, and other constraints. This poses a complex challenge that educational authorities in…

Advances in computational language models increasingly enable adaptive support for self-regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern for educational stakeholders (eg, policymakers, researchers, teachers and learners themselves). We compared…

Scholarly interest about how students learn and retain learned skills is vast. Cognitive psychologists have recommended various techniques used to increase retention. One technique, spaced retrieval practice, involves extending opportunities to retrieve course content beyond a customarily short window following the initial learning process. Our…

Using a Dynamic Geometry System (DGS) students can engage in a dynamic learning process that allows them to experiment, create strategies, make conjectures, argue, and deduce mathematical properties. A DGS enables the introduction of proofs, by providing visual aids. The proof of the conjectures made emerges as the next step towards formalising…

Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…

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…

Schools produce multiple products and digitization articulates with them in different ways. In this paper we expand the frame for analyzing instructional automation by examining its implications for three scholastic products -- embodied learning, grades and test scores, and the narratives that connect the two. We draw on data from interviews with…

Handwritten tasks are better suited than digital ones to assess higher-order mathematics skills, as students can express themselves more freely. However, maintaining reliability and providing feedback can be challenging when assessing high-stakes, handwritten mathematics exams involving multiple assessors. This paper discusses a new semi-automated…

Grading assignments is inherently subjective and time-consuming; automatic scoring tools can greatly reduce teacher workload and shorten the time needed for providing feedback to learners. The purpose of this paper is to propose a novel method for automatically scoring student responses to picture-cued writing tasks. As a popular paradigm for…

The purpose of this study is to introduce and evaluate a method for generating reading comprehension items using template-based automatic item generation. To begin, we describe a new model for generating reading comprehension items called the text analysis cognitive model assessing inferential skills across different reading passages. Next, the…

Providing timely and helpful writing feedback for student writers, especially those at the middle and high school level, can present an unwieldy challenge for teachers. Yet, feedback is necessary for students' growth as writers. There is an increased interest and use of automatic writing programs to provide students with writing feedback. However,…

The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…

While subtitles are considered a primary learning support tool for people who cannot understand video narration in foreign languages, recent advancements in artificial intelligence (AI) technologies have played a pivotal role in automatic subtitling on online video platforms such as YouTube. This study examines the effects of three different types…

This study aimed at examining the performance of generative artificial intelligence to extract argumentation elements from text. Thus, the researchers developed a web-based framework to provide automated assessment and feedback relying on a large language model, ChatGPT. The results produced by ChatGPT were compared to human experts across…

Current student-centred, multilingual, active teaching methodologies require that teachers have continuous access to texts that are adequate in terms of topic and language competence. However, the task of finding appropriate materials is arduous and time consuming for teachers. To build on automatic readability assessment research that could help…