In recent years, the US has begun scaling up efforts to increase access to CS into K-12 classrooms and many teachers are turning to block-based programming environments to minimize the syntax and conceptual challenges students encounter in text-based languages. Block-based programming environments, such as Scratch and App Inventor, are currently being used by millions of students in and outside the classroom. We know that when novice programmers are learning to program in block-based programming environments, they need to understand the components of these environments, how to apply programming concepts, and how to create artifacts. However, we still do not know how are they learning these components or what learning challenges they face that hinder their future participation in Computer Science. In addition, the mental effort/cognitive workload students exert while learning programming constructs is still an open question. The goal of this project is to leverage advances in Electroencephalography (EEG) research to explore how students learn CS concepts, write programs, and complete programming tasks in block-based programming.


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