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Teaching Programming Skills in Methods Courses Is an Opportunity, Not a Burden

Published online by Cambridge University Press:  21 December 2021

Rob Williams Open the ORCID record for Rob Williams [Opens in a new window]
Rob Williams*
Affiliation:
Washington University in St. Louis, USA
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Abstract

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Type
Teaching Political Methodology
Information
PS: Political Science & Politics , Volume 55 , Issue 1 , January 2022 , pp. 221 - 224
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political Science Association

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References

REFERENCES

Abbate, Janet. 2012. Recoding Gender: Women’s Changing Participation in Computing. History of Computing. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Beyer, Sylvia. 2014. “Why Are Women Underrepresented in Computer Science? Gender Differences in Stereotypes, Self-Efficacy, Values, and Interests and Predictors of Future CS Course-Taking and Grades.” Computer Science Education 24 (2–3): 153–92. https://doi.org/10.1080/08993408.2014.963363.CrossRefGoogle Scholar
Carlana, Michela. 2019. “Implicit Stereotypes: Evidence from Teachers’ Gender Bias.” Quarterly Journal of Economics 134 (3): 1163–224. https://doi.org/10.1093/qje/qjz008.CrossRefGoogle Scholar
Chávez, Kerry, and Kristina, M. W. Mitchell. 2020. “Exploring Bias in Student Evaluations: Gender, Race, and Ethnicity.” PS: Political Science & Politics 53 (2): 270–74. https://doi.org/10.1017/S1049096519001744.Google Scholar
Cheng, Ching-Ching, and Huang, Kuo-Hung. 2016. “Stereotypes and Technology Education: Different Perceptions of Computer Career Among Elementary School Students.” Journal of Baltic Science Education 15 (3): 271–83. DOI:10.33225/jbse/16.15.271.CrossRefGoogle Scholar
Davenport, Thomas H., and Patil, Dhanurjay. 2012. “Data Scientist: The Sexiest Job of the 21st Century.” Harvard Business Review 90 (10): 70–76.Google Scholar
Funke, Alexandra, Berges, Marc, and Hubwieser, Peter. 2016. “Different Perceptions of Computer Science.” In 2016 International Conference on Learning and Teaching in Computing and Engineering (LaTICE), 14–18. https://doi.org/10.1109/LaTiCE.2016.1.CrossRefGoogle Scholar
Gewin, Virginia. 2020. “The Time Tax Put on Scientists of Colour.” Nature 583 (7816): 479–81. https://doi.org/10.1038/d41586-020-01920-6.CrossRefGoogle ScholarPubMed
Google. 2015. “Images of Computer Science: Perceptions Among Students, Parents and Educators in the U.S.”Google Scholar
Irizarry, Yasmiyn. 2021. “On Track or Derailed? Race, Advanced Math, and the Transition to High School.” Socius 7 (January 11). https://doi.org/10.1177/2378023120980293.CrossRefGoogle Scholar
Lewis, Colleen M., Yasuhara, Ken, and Anderson, Ruth E.. 2011. “Deciding to Major in Computer Science: A Grounded Theory of Students’ Self-Assessment of Ability.” In Proceedings of the Seventh International Workshop on Computing Education Research, 3–10. ICER ’11. New York: Association for Computing Machinery. https://doi.org/10.1145/2016911.2016915.Google Scholar
Li, Ruoxi. 2019. “Teaching Undergraduates R in an Introductory Research Methods Course: A Step-by-Step Approach.” Journal of Political Science Education September:1–19. https://doi.org/10.1080/15512169.2019.1667811.Google Scholar
Lindner, Chris. 2018. “Where Do Data Scientists Come From?” Indeed Engineering Blog. https://engineering.indeedblog.com/blog/2018/12/where-do-data-scientists-come-from.Google Scholar
McIlwain, Charlton D. 2020. Black Software: The Internet and Racial Justice, from the AfroNet to Black Lives Matter. New York: Oxford University Press.Google Scholar
Mengel, Friederike, Sauermann, Jan, and Zölitz, Ulf. 2018. “Gender Bias in Teaching Evaluations.” Journal of the European Economic Association. https://doi.org/10.1093/jeea/jvx057.Google Scholar
Mitchell, Kristina M. W., and Martin, Jonathan. 2018. “Gender Bias in Student Evaluations.” PS: Political Science & Politics 51 (3): 1–5. https://doi.org/10.1017/S104909651800001X.Google Scholar
National Association of Colleges and Employers. 2020. “Job Outlook 2020.” www.naceweb.org/talent-acquisition/candidate-selection/key-attributes-employers-want-to-see-on-students-resumes.Google Scholar
Nguyen, An, and Lewis, Colleen M.. 2020. “Competitive Enrollment Policies in Computing Departments Negatively Predict First-Year Students’ Sense of Belonging, Self-Efficacy, and Perception of Department.” In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 685–91. SIGCSE ’20. New York: Association for Computing Machinery. https://doi.org/10.1145/3328778.3366805.Google Scholar
Papastergiou, Marina. 2008. “Are Computer Science and Information Technology Still Masculine Fields? High School Students’ Perceptions and Career Choices.” Computers & Education 51 (2): 594–608. https://doi.org/10.1016/j.compedu.2007.06.009.CrossRefGoogle Scholar
Shugars, Sarah. 2021. “Dr. Sarah Shugars: Data Science Is for Everyone.” NYU Center for Data Science. https://nyudatascience.medium.com/dr-sarah-shugars-data-science-is-for-everyone-54f7a3bc4229.Google Scholar
Singer, Natasha. 2019. “The Hard Part of Computer Science? Getting into Class.” New York Times, January 24.Google Scholar
Uttl, Bob, and Smibert, Dylan. 2017. “Student Evaluations of Teaching: Teaching Quantitative Courses Can Be Hazardous to One’s Career.” PeerJ 5 (May 9): e3299. https://doi.org/10.7717/peerj.3299.CrossRefGoogle ScholarPubMed
Ying, Kimberly Michelle, Pezzullo, Lydia G., Ahmed, Mohona, Crompton, Kassandra, Blanchard, Jeremiah, and Boyer, Kristy Elizabeth. 2019. “In Their Own Words: Gender Differences in Student Perceptions of Pair Programming.” In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 1053–59. Minneapolis: ACM. https://doi.org/10.1145/3287324.3287380.CrossRefGoogle Scholar