qualitative analysis, data analysis, programming, social science
WHAT WE DO
Key Points:
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Assess the relationship between computers, data, and society from equity and social justice perspectives.
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Analyze datasets using R.
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Engage with qualitative research methods (interviews, survey design, etc.).
Detailed Description:
Technology and data influence how society operates and innovates. The goal of the Computing & Society stream is to create high-quality, mixed-methods research projects that blend computing topics and the social sciences. We perform research that interrogates exclusionary and harmful practices within the computing community by collecting qualitative and quantitative data, analyzing numerical data in R, and developing high-quality research projects.
WHY IT MATTERS
Key Points:
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Computing research can have negative and positive consequences on society.
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Researchers must be able to see how computing research is also social science research.
Detailed Description:
Developers and researchers who collect and analyze data do not always understand the impact that their findings and research can have on people and communities. For example, multiple scholars have repeatedly shown how data has, intentionally or unintentionally, exacerbated racial, gender, and socioeconomic injustice in society. By becoming a community of critically conscious researchers, we can dismantle inequities that arise in the research process by informing the design of future computing research efforts.
WHAT YOU LEARN
Key Points:
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The entire research process and how to analyze existing research.
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Social science and data analysis research methodologies.
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Statistical analyses.
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Programming in R.
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The formal publication process and venues of publication.
Detailed Description:
This stream is an opportunity for students to understand the research process from start to finish: 1) design a research question, 2) analyze a dataset to answer their research question using practices from both social science and data science fields, and 3) write and publish their findings to share with the broader research community. All students will learn how to use R to clean and analyze datasets. They will also learn how to perform and interpret statistical tests, analyze qualitative data, and navigate UMD's Institutional Review Board (IRB) process for human subjects research.
