Background: In the digital environment, users' academic reading behaviour has changed, working with many articles simultaneously to search, filter, scan, link, annotate and analyse content fragments. The semantic enhancement environment has been widely set with semantic technologies to offer additional and handy support for users and thus…

Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…

Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…

A semantic diagram tool is proposed in this study in order to structure collaborative problem solving (CPS) based on cognitive load theory (CLT). To investigate its effects on transaction cost and the deepening of user understandings, a comparative quasi-experiment was designed and conducted with 49 participants from a university in East China.…

This study examined the effects of an intervention with a multicomponent reading game on the development of reading skills in 60 Dutch primary school children with special educational needs. The game contains evidence-based reading exercises and is based on principles of applied gaming. Using a multiple baseline approach, we tested children's…

"Ensemble" is an interdisciplinary research and development project exploring the potential role of emerging Semantic Web technologies in case-based learning across learning environments in higher education. Empirical findings have challenged the claim that cases "bring reality into the classroom" and that this, in turn, might…