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CS Education Infrastructure for All: Interoperability for Tools and Data Analytics (Abstract Only)

CS Education makes heavy use of online educational tools like IDEs, Learning Management Systems, eTextbooks, interactive programming environments, and other smart content. Instructors and students would benefit from greater interoperability between tools. CS Ed researchers increasingly make use of the large collections of data generated by click streams coming from them. However, we all face barriers that slow progress: (1) Educational tools do not integrate well. (2) Information about CS learning process and outcome data generated by one system is not compatible with that from other systems. (3) CS problem solving and learning (e.g., coding solutions) is different from the type of data (discrete answers to questions or verbal responses) that current educational data mining focuses on. This BOF will discuss ways that we might support and better coordinate efforts to build community and capacity among CS Ed researchers, data scientists, and learning scientists toward reducing these barriers. CS Ed infrastructure should support broader re-use of innovative learning content that is instrumented for rich data collection, formats and tools for analysis of learner data, and best practices to make large collections of learner data available to researchers. Achieving these goals requires engaging a large community of researchers to define, develop, and use critical elements of this infrastructure to address specific data-intensive research questions.