Educational Advances

Featured Articles - Volume 1, Number 1

• Edge Computing-Enabled Smart Classroom System with IoT Sensors for Automatic Learning Behavior Analysis

  Xingwang Pi, Yanlun Chen

  Traditional classroom monitoring systems rely heavily on centralized cloud processing, which creates significant latency issues when analyzing student learning behaviors in real-time. This research presents a distributed edge computing framework that integrates multiple IoT sensors...

  Keywords: Edge Computing, IoT Sensors, Learning Behavior Analysis, Smart Classroom

• Multivariate Time Series Analysis for Early Prediction of Student Dropout Risk in MOOCs Using Transformer Architecture

  Yifei Yin

  Student dropout remains a persistent challenge in massive open online courses, with completion rates typically falling below 15% across various platforms. Traditional prediction models often fail to capture the complex temporal patterns...

  Keywords: Student Dropout Prediction, Multivariate Time Series, Transformer Architecture, MOOC Analytics

• Multi-Modal AI-Driven Personalized Learning Path Optimization: A Deep Reinforcement Learning Approach for Adaptive Curriculum Sequencing

  Yanling Liu

  Traditional educational systems face significant challenges in delivering personalized learning experiences that adapt to individual student needs and learning patterns. Current approaches to curriculum sequencing often rely on static rule-based systems...

  Keywords: Personalized Learning, Deep Reinforcement Learning, Multi-Modal Data Fusion, Adaptive Curriculum

• Haptic-Enhanced Virtual Laboratory Design: Measuring Learning Effectiveness through Embodied Interaction in Chemistry Education

  Ling Liu

  Chemistry education faces significant challenges in providing hands-on laboratory experiences, particularly when dealing with hazardous materials or expensive equipment. Traditional virtual laboratories often lack the tactile feedback...

  Keywords: Haptic Technology, Virtual Laboratory, Chemistry Education, Embodied Learning

• A Multimodal Physiological Signal Fusion Algorithm for Real-time Learning Engagement Detection in Digital Learning Environments

  Ruirui Zou

  Learning engagement detection has become a critical component in modern educational technology systems. Traditional assessment methods rely heavily on behavioral observations and self-reporting mechanisms...

  Keywords: Physiological Signal Processing, Learning Engagement, Multimodal Fusion, Real-Time Detection