Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…

Recent advances in the development of large language models (LLMs) have led to power innovative suites of generative AI tools that are capable of not only simulating human-like-dialogue but also composing more complex artifacts, such as social media posts, essays, and even research articles. While this abstract has been written entirely by a human…

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…

Modern educational technology systems allow learners to access large amounts of learning materials such as educational videos, learning notes, and teaching books. Automated summarization techniques simplify the access and exploration of complex data collections by producing synthetic versions of the original content. This paper addresses the…

This paper explores three simple data manipulation techniques (synthesis, augmentation, curriculum) for improving abstractive summarization models without the need for any additional data. We introduce a method of data synthesis with paraphrasing, a data augmentation technique with sample mixing, and curriculum learning with two new difficulty…

Digital image processing is an integral part of the computer vision field. However, traditional digital image processing teaching methods mainly focus on theoretical knowledge, lacking practical teaching content. To address this issue, this article proposes a project-based learning (PBL) model that consists of four key stages: project proposal,…

This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target…

While numerous studies have investigated teachers' professional learning through their interaction with resources, the question of how teachers' knowledge evolves at different stages of the instructional process remains underexplored. To address this gap, this article builds on the documentational approach to didactics (DAD) and the theory of…

Quality is a main issue when practices of validation are developed. In the Nordic countries, a model of quality assurance in validation has been introduced, to be applied in the development of validation practices. The model puts the individual at the centre and introduces eight factors for quality: information, preconditions, documentation,…

The research presented in this paper aims to shed light on the complex role of mathematics teacher educators who led courses for prospective mathematics teachers. Theoretically, the research combines the documentational approach to didactics and the meta-didactical transposition frameworks, complementing the study with the analysis of the teacher…

Cloze items are commonly used for both assessing learning and as a learning activity. This paper investigates the selection of sentences for cloze item creation by comparing methods ranging from simple heuristics to deep learning summarization models. An evaluation using human-generated cloze items from three different science texts indicates that…

Gifted education has been recognised as a fractured field that can be categorised using varying paradigmatic approaches. Over the past thirty years, Gagne's Differentiated Model of Giftedness and Talents (DMGT) has maintained a strong influence in Australia, which means that the paradigmatic assumptions that are present in this model have shaped…

Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…

The study of revision has been a topic of interest in writing research over the past decades. Numerous studies have, for instance, shown that learning-to-revise is one of the key competences in writing development. Moreover, several models of revision have been developed, and a variety of taxonomies have been used to measure revision in empirical…

Language documentation is increasingly seen as a collaborative process, engaging community members as active participants. Collaborative research produces better documentation that is valuable for both the academic community and the speakers. However, in many communities, speakers and language advocates lack the skills necessary to fully engage in…