The 9th International Conference on Computer Science and Technologies in Education (CSTE 2027)

The 9th International Conference on Computer Science and Technologies in Education (CSTE 2027) explores the role of computer science and emerging technologies in education, focusing on topics such as collaborative learning, STEM education, and the use of AI and data analytics in educational systems.

Key Topics

• Computer-supported Collaborative Learning and Social Computing
  • Social computing and learning
  • Collaborative learning theories and models
  • Social media in education
  • Online communities and networks in education
  • Computer-supported argumentation and debate
  • Collaborative technologies in education
• Educational Technologies and Systems
  • Computer-supported collaborative learning
  • E-learning platforms and tools
  • Game-based learning
  • Mobile and ubiquitous learning
  • Adaptive learning systems
  • Virtual and augmented reality in education
  • Emerging technologies in education
  • Educational robotics and automation
• STEM Education and Computational Thinking
  • Computational thinking and coding education
  • STEM education and pedagogy
  • Computational modeling and simulation in education
  • Robotics and automation in STEM education
  • Digital fabrication and maker education
  • Educational applications of Internet of Things
• Artificial Intelligence in Education
  • Natural language processing in education
  • Intelligent tutoring systems
  • Intelligent educational systems and applications
  • Knowledge representation and reasoning in education
  • Cognitive modelling and educational implications
  • Smart learning environments
• Innovative Technologies for Teaching and Learning
  • Gamification and game-based learning
  • Wearable technology in education
  • Cloud computing in education
  • Personalized and adaptive learning
  • Immersive learning environments
  • Mobile learning and ubiquitous computing
• Educational Data Mining and Learning Analytics
  • Learning analytics and visualization
  • Data-driven approaches to education
  • Big data in education
  • Educational data mining and machine learning
  • Educational decision making
  • Personalized learning
  • Assessment and evaluation in e-learning