Using Collaborative Open Science to Advance K-12 Computing Education

Open science in computing education has been focused primarily on the data collected by automated learning systems such as those developed in intelligent tutoring systems and rote drill exercises. There is another aspect of data collection that is being continually conducted throughout K-12 and post-secondary computing education through surveys, summative assessments, interviews, and other methods to measure cognitive (e.g., algorithms, data structures, pointers) and noncognitive (e.g., self-efficacy, grit, attitude) factors. As a new field, we have the unique advantage of being able to build and share practical and comparable datasets in K-12 computing education that meets some of the new guidelines and best practices being put forth by the National Science Foundation and Department of Education. This short paper describes the data being collected that is now available as part of CSEdResearch.org, what is needed to add the capability to collect and compare additional data through collaborative open science practices, and a path towards meeting those needs. This work furthers Open Science by defining how to access the data that already exists in CSEdResearch.org as well as what is needed to create additional tools for researchers and evaluators to enter K-12 computing education data directly on the site. By creating the infrastructure for shareable data that meets current and evolving open source guidelines, the community can start to use this data to develop best practices from empirical evidence.