Effective analysis and demonstration of these data features is of great significance for the optimization of interactive learning environment and learning behavior. Therefore, we take the big data set of learning behavior generated by an online interactive learning environment as the research object, define the features of learning behavior, and…

Online learning communities play a crucial role in delivering high-quality courses to a large number of learners. However, to maintain an economically sustainable and constantly evolving online learning ecosystem, it is essential to create a virtuous cycle from knowledge production to knowledge consumption by charging learners to incentivize…

Acceleration, compacting the curriculum, differentiation, and asynchronous development are just some of the many concepts that underpin the discipline of gifted education and its associated pedagogy. There is little discussion or indeed implementation of these strategies within the tertiary sector. What would tertiary education in Australia look…

This concept paper proposes a way of mapping educational landscapes to clarify the practice of experiential programming. It initially reviews how experiential education has been defined and suggestions for better definitional clarity. It then examines a recent initiative commissioned by the Society for Experiential Education to update its…

Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…

Traditional reviews of arts education have focused on why the arts are valuable for learning, but the arts' contributions to cross-disciplinary discourse remain undertheorized. In this article, we provide a theoretical review of the arts and learning to suggest a new way of thinking about how the arts contribute to learning across disciplines…

The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…

Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative training method of multi view learning interaction process driven by big data, so as to realize the tendency…

Background: While both Content and Language Integrated Learning (CLIL) and Digital Game-Based Learning (DGBL) are widely recognised as effective methods to enhance bilingual education, their combination often leads to cognitive overload and fragmented learning experiences. In Taiwan's bilingual education context, where integrating English into…

The literature on cognitive processing and strategic processing is murky with regard to how these types of processing influence learning. One reason for this is that the frameworks used to investigate these relations have separately focused on different aspects related to cognitive processing with little integration between them. To address these…

MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to…

This theoretical article, with recommendations for practice, interrogates how the field discusses dual language bilingual education (DLBE) models in the United States, with international implications for bilingual, immersion, and content and language integrated learning contexts. We reconceptualize the equity problems and potentials of so-called…

Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

This study introduces and validates the Technological Pedagogical Content Knowledge--Integrated Experiential Performance Learning (TPACK-EPL) Model, designed to enhance learners' digital competency through a structured instructional design framework. The model integrates the TPACK framework with experiential and performance-based learning,…