Intelligent technology plays a pivotal role in revolutionizing learning assessments, overcoming the constraints of traditional assessment methods and driving educational innovation. Knowledge tracing (KT) emerges as a critical component for assessing students' learning states and forecasting their future performance. However, existing graph-based…

Knowledge tracing (KT) plays a key role in adaptive learning, yet traditional recurrent neural network-based methods often struggle with sparse data and overlook relationships between knowledge points. To address these limitations, this paper proposes a novel knowledge tracing model (KGS-KT) that integrates knowledge graphs, graph convolutional…

The objective of question generation from knowledge graphs (KGQG) is to create coherent and answerable questions from a given subgraph and a specified answer entity. KGQG has garnered significant attention due to its pivotal role in enhancing online education. Encoder-decoder architectures have advanced traditional KGQG approaches. However, these…

Social science theories often postulate systems of causal relationships among variables, which are commonly represented using directed acyclic graphs (DAGs). As non-parametric causal models, DAGs require no assumptions about the functional form of the hypothesized relationships. Nevertheless, to simplify empirical evaluation, researchers typically…

To prepare undergraduates for complex careers, interdisciplinary higher education is gaining popularity. However, implementing interdisciplinary learning in engineering management is challenging due to the complex and intertwined knowledge structures. While smart education platforms provide access to extensive knowledge bases, the intricate web of…

Early identification of student success is crucial for enabling timely interventions, reducing dropout rates, and promoting on-time graduation. In educational settings, AI-powered systems have become essential for predicting student performance due to their advanced analytical capabilities. However, effectively leveraging diverse student data to…

Deeper learning (DL) is firmly rooted in learning science and computer science. However, a dearth of review studies has probed its trajectory in DL in foreign languages (DLFL). Utilizing SSCI from the Web of Science Core Collection, we employ Citespace and Vosviewer to analyze the scientific knowledge graph of DLFL literature. Our analysis…

Background: As educational institutions increasingly operate as multicultural hubs, leaders must navigate the complexities of cultural differences, language barriers and diverse learning styles in digital environments. These challenges are amplified by the lack of non-verbal cues and the asynchronous nature of online communication, which can lead…

[This paper is part of the Focused Collection in Artificial Intelligence Tools in Physics Teaching and Physics Education Research.] Artificial intelligence-based chatbots are increasingly influencing physics education because of their ability to interpret and respond to textual and visual inputs. This study evaluates the performance of two large…

The assessment of writing competency in French as a Foreign Language presents significant challenges due to the multidimensional nature of writing and heterogeneous evaluation practices. This research introduces an innovative framework integrating artificial intelligence and interactive visualization to support the formative assessment of writing…