As generative artificial intelligence (AI) rapidly transforms educational landscapes, understanding its impact on students' core competencies has become increasingly critical for educators and policymakers. Despite growing integration of AI technolog...
The rapid integration of cutting-edge technology is significantly transforming the higher education landscape. ChatGPT's groundbreaking technology has provided numerous advantages for higher education. This study explored students' behavioral intenti...
Knowledge tracing models predict students' mastery of specific knowledge points by analyzing their historical learning performance. However, existing methods struggle with handling a large number of skills, data sparsity, learning differences, and co...
In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing model (CL-PTKT...
Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted information are not well understood. Few models of social learning account for the fact that socially transm...
With the rapid development of artificial intelligence technology, digital human education platforms have become a research hotspot in education. This paper proposes a method to build a multi-modal digital human education platform based on a Generativ...
Communication is essential for success in today's world, making English language learning (ELL) a crucial skill. Innovative solutions are required to tackle complex language learning issues and meet the various demands of learners. Personalized learn...
Models are often evaluated when their behavior is at its closest to a single, sometimes averaged, set of empirical results, but this evaluation neglects the fact that both model and human behavior can be heterogeneous. Here, we develop a measure, -di...
This research explores the potential of combining Meta Reinforcement Learning (MRL) with Spike-Timing-Dependent Plasticity (STDP) to enhance the performance and adaptability of AI agents in Atari game settings. Our methodology leverages MRL to swiftl...
Prior research on student achievement has typically examined isolated factors or bivariate correlations, failing to capture the complex interplay between learning behaviors, pedagogical environments, and instructional design. This study addresses the...