The Second Workshop on AI-supported Education for Computer Science (AIEDCS) held at ITS 2014

Over the last two decades, Computer Science (CS) has emerged as a crucial area of study for students at many levels of education, and basic CS literacy has become an essential competency required for any profession. Recent years have seen innovation in the field of CS education, yet we still have tremendous challenges related to improving quality of instruction and increasing the diversity of students in CS classes. One of the solutions to these problems lies with effective technology-enhanced learning and teaching approaches, and especially those enhanced with AI-based functionality. Providing education in Computer Science requires not only specific teaching techniques but also appropriate supporting tools. The number of AI-supported tools for primary, secondary and higher CS education is small and evidence about the integration of AI-supported tools in teaching and learning at various education levels is still rare. 

Not only does designing AI-supported tools for CS education present important challenges, but deploying AI-supported tools in Computer Science education may give rise to several important areas for study. By addressing these challenges and problems as a research community, we will be poised to make great strides in building intelligent, highly effective AI-supported educational tools for Computer Science and developing innovative approaches to support teaching and learning. 

Spurred by the growing need for intelligent teaching/learning tools that support Computer Science education, the second workshop on AI-supported Education for Computer Science (AIEDCS 2014) follows up on the inaugural workshop, held at AIED 2013, and comes at an important time for solidifying this community.

Topics of Interests

  • Teaching approaches using AI-supported tools
  • Learning approaches using AI-supported tools
  • Student modeling for Computer Science learning
  • Adaptation and personalization within Computer Science learning environments
  • Intelligent support for collaborative Computer Science problem solving
  • Affective and motivational aspects related to Computer Science learning
  • Adaptive feedback, adaptive testing for Computer Science learning
  • Discourse and dialogue research related to classroom, online, collaborative, or one-on-one learning of Computer Science
  • Online learning environments for Computer Science