Scope and Vision
Creative computing emphasises computing activities at a high abstraction level, or at macro level. Traditionally, computing was to help accomplish a known task better while Creative Computing is to seek to accomplish a task in a novel way through computing.

It is important to differentiate between the terms “creative computing”, i.e., a more poetic endeavour of how the computing itself is done, and “computational creativity”, which is about achieving creativity through computation, i.e., using formal computational methods to mimic creativity as a human trait.

The theme of the symposium is CROWDSOURCING for Creative Computing.


Track I: Crowdsourcing

Worker behavior, ranking, evaluation, collaboration
Data cleansing, validation, analysis
Declarative languages for crowdsourcing
Tagging, resolution, trust models
Incentive scheme, game theory, competition models, stochastic models
System support for crowdsourcing, architecture, SaaS, PaaS
Scalable crowdsourcing, models
Human computation, experts participation, models
Social networks, social media, search
Quality Evaluation and voting,
Use cases, data,
Semantic modeling, reasoning, data linking
Software Crowdsourcing Process and Methodology

Track II: Creative Computing and Technology and Enterprise

Creativity support systems
Autonomous creative systems
Cognitive and psychological issues in creativity research
Creative interaction techniques
Creative social computing
Software-based stimulation of creativity
Methods, tools and techniques for observing and studying creative processes
Design cases illustrating the role of creativity
Theoretical insights into creative design processes
Visions on teaching & research in creative design
Creative computing for digital multimedia; Computer-generated contents for film, games and animation; Special visual effects; Edutainment; Generative art; Aesthetic evaluation, etc.
Creative research environments and their performance
Enterprise creativity idea, practice and case studies, tools
Feature selection/extraction in big data
Large big data stream processing
Big Data Solutions for Creative Computing
Hardware/software infrastructure for creativity
Data mining for creativity
Big data and creative applications (health care, medicine, finance, business, law, education, transportation, telecommunication, science, engineering, ecosystem, etc.)

Track III: Massive Open Online Course (MOOCs)

Pedagogy, Adaptive and Personalized Learning, collaborative learning
Learning Systems Platforms and Architectures
Mobile and Ubiquitous Learning
Ambient Intelligence and Smart Environments for Learning
Digital Game and Intelligent Toy Enhanced Learning
Web 2.0 and Social Computing for Learning and Knowledge Sharing
Semantic Web and Ontologies for Learning Systems
Data Mining and Web Mining in Education
Cloud-based Learning and Assessment
MOOCs Learning Data Management
Virtual Labs and Simulation in MOOCs
Intelligent Tutoring System