Building Recommendations for Conducting Equity-Focused, High Quality K-12 Computer Science Education Research
McGill, Monica M.; Heckman, Sarah; Chytas, Christos; Diaz, Lien; Liut, Michael; Kazakova, Vera; Sanusi, Ismaila Temitayo; Shah, Selina Marianna; Szabo, Claudia
(2023)
ITiCSE 2023, volume 2, pp. 565 - 566
Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, volume 2, pp. 565 - 566
28th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE 2023, volume 2, pp. 565 - 566
(Part of book)
Abstract
To investigate and identify promising practices in equitable K-12 computer science (CS) education, the capacity for education researchers to conduct this research must be rapidly built globally. Simultaneously, concerns have arisen over the last few years about the quality of research that is being conducted and the lack of equity-focused
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research. In this working group, we will tackle the research question: In what ways can previous research standards inform high-quality, equity-focused K-12 CS education research? We will use existing research and various standards bodies (e.g., European Educational Research Association, Australian Education Research Organisation, CONSORT, American Psychological Association) to synthesize key features in the context of equity-focused K-12 CS education research. We will then vet these attributes with experts who can provide feedback and refine our recommendations and guidelines. Our working group will select the experts using a strata reflecting a diversity of backgrounds and experiences to support our focus on student populations that have been historically marginalized in computing (e.g., low-income students, rural students, girls, students with disabilities). Our recommendations will directly impact future equitable computing education research by providing guidance on conducting high-quality research such that the findings can be aggregated and impact future policy with evidence-based results. While we recognize that different countries and regions may yield differing answers to this question, our recommendations will be robust enough that researchers in each country or region may choose to use those most appropriate to their context.
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Keywords: computer science education research, computing education, equity, evidence, high quality, research, standards, Taverne, Management of Technology and Innovation, Education
ISSN: 1942-647X
ISBN: 9798400701399
Publisher: Association for Computing Machinery (ACM)
Note: Funding Information: This material is based upon work supported by the U.S. National Science Foundation under Grant Nos. 2122212. Publisher Copyright: © 2023 Owner/Author.
(Peer reviewed)
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