Computer-supported Collaborative Learning

As John Carroll and Ann Bishop state, "Most learning is taking place in the community" (2005). This is a more formal environment such as an informal community such as conversation at work or a distance education course. Regardless of the format, humans learn from each other through some kind of exchange. For educators, the problem is the best way to guide this natural learning tendency and the way to make maximum use of technology in the process. Therefore, computer-assisted collaborative learning (CSCL) focuses on the benefits of leveraging collaborative learning via networked computers (Computer Assisted Collaborative Learning, 2007).

Have you participated in e-learning example through social interaction? So you are already familiar with the concept of a computer-aided collaborative learning system already abbreviated CSCLS. CSCLS is a tool for educating people through social interaction. One of the earliest evidences of CSCLS was the design and implementation of the Intelligent Collaborative Learning System (ICLS), which formed the latest approach to artificial intelligence and education.

The online collaboration space combines educator's interest in constructivism, classroom technology, and social learning opportunities through innovative critical thinking and practical learning methods. Also called CSCL (Computer Supported Collaborative Learning) (Resta & Laferierre, 2007; Deal, 2009), online collaboration space allows you to work together in an interactive and flexible online environment. These online spaces facilitate the exchange of various modes, including text, speech and multimedia formats, reflecting Vygotsky's theory on the importance of language use for learning. They can also offer diverse participants than actual classrooms, allowing cross-cultural connections to stimulate social learning.

In a new paper called "Mixing as a way to computational thinking" recently announced at the ACM Computer Assisted Collaborative Work and the Social Computing Conference (CSCW) meeting, we tried to find it using a series of quantitative indicators of online behavior . Evidence that may support the theory of positive correlation between mixing and learning in scratch Of course, Scratch is an informal environment without a fixed path, so there is no lesson planning and testing, learning measurements are unresolved problems is. In our study we have established two different ways to measure learning with scratch. In the first method, users take into account the number of different types of programming blocks available in Scratch, and users use their life cycle with Scratch (120 total). This can be thought of as a block library or vocabulary. In previous studies this scale was used to simulate informal learning in scratch.