DEI Teaching Resources

Goal/Mission Statement

These resources are intended to support the development of an inclusive environment in the Department of Statistics.  Resources are grouped by topic – Inclusive Teaching, Inclusive Classroom, etc. – to facilitate easy access to the most relevant materials.

Have a resource you’d like to suggest? Find one of these resources particularly useful? Let us know by contacting either Emily Griffith (eghohmei@ncsu.edu) or Jonathan Duggins (jwduggins@ncsu.edu)

What is inclusive teaching?

Inclusive teaching recognizes that students and instructors bring their identities, backgrounds, and experiences into the classroom. This recognition impacts the way that we teach and the way that students learn. The social constructivist theory of learning and teaching posits students learn by making meaning for themselves through active engagement with ideas and through social interaction with others. (https://www.inclusivestemteaching.org/)

Interested in learning more?

Readings:

• Gannon, K (2018), “The Case for Inclusive Teaching,” The Chronicle of Higher Education. https://www.chronicle.com/article/the-case-for-inclusive-teaching/?cid=gen_sign_in
• Witmer, J (2021), “Inclusivity in Statistics and Data Science Education,” Journal of Statistics and Data Science Education, 29:1, 2-3, DOI: 10.1080/26939169.2021.1906555

Courses/Certificates:

• Inclusive STEM Teaching Project: https://www.inclusivestemteaching.org/ 
• NC State’s Inclusive Excellence Certificate: https://diversity.ncsu.edu/inclusive_excellence_certificate/ 

What is an inclusive classroom?

When designing and teaching a course, we as faculty can create an inclusive classroom by recognizing our own privilege when developing courses, acknowledging and confronting our implicit biases, and working to mitigate stereotype threat in our classrooms. (Killpack and Melón 2016). 

Interested in learning more?

Readings on course design and class activities:

• Killpack, TL and LC Melón (2016), “Toward Inclusive STEM Classrooms: What Personal Role do Faculty Play?,” CBE Life Sciences Education, 15:es3, 1-9. https://www.lifescied.org/doi/10.1187/cbe.16-01-0020 
• Pittman, C and TJ Tobin (2022), “Academe Has a Lot to Learn About How Inclusive Teaching Affects Instructors,” Chronicle of Higher Education. https://www.chronicle.com/article/academe-has-a-lot-to-learn-about-how-inclusive-teaching-affects-instructors 
• Tanner, KD (2013), “Structure Matters: Twenty-One Teaching Strategies to Promote Student Engagement and Cultivate Classroom Equity,” CBE Life Sciences Education, 12, 322-331. https://www.lifescied.org/doi/10.1187/cbe.13-06-0115

Readings on cultivating a sense of belonging:

• Gardner, S. K., (2008). “Fitting the Mold of Graduate School: A Qualitative Study of Socialization in Doctoral Education,” Innov High Educ, 33:125–138. DOI 10.1007/s10755-008-9068-x
• Hariharan, J. (2019), “I felt lost in a new academic culture. Then I learned about the hidden curriculum.” Science, 364(6441): 702. doi: 10.1126/science.caredit.aay0523
• LaLonde, D, W Martinez, J Miller, M Ott, and S Thornton (2019), “LGBT+ resources for statisticians and data scientists,” Significance Magazine. https://www.significancemagazine.com/culture/624-lgbt-resources-for-statisticians-and-data-scientists?highlight=WyJnZW5kZXIiXQ==
• Thornton, S, B Green, and E Benn (2019), “Friends and allies: LGBT+ inclusion in statistics and data science,” Significance Magazine. https://rss.onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2019.01280.x 

What are inclusive datasets?

The history of statistics is closely tied with the eugenics movement. Reckoning with that fact and preventing it in the future may involve stepping away from the idea that statistics and data are purely objective. Context matters, and context is key to statistics. Introducing critical thinking, rationales, and the “big picture” are important aspects of statistical thinking.

Interested in learning more?

Readings on the history of statistics

Clayton, A (2020), “How Eugenics Shaped Statistics,” Nautilus. https://nautil.us/how-eugenics-shaped-statistics-9365/

Readings on statistical ethics:

• American Statistical Association’s Ethical Guidelines for Statistical Practice https://www.amstat.org/your-career/ethical-guidelines-for-statistical-practice
• Baumer, BS, RL Garcia, AY Kim, KM Kinnaird, and MQ Ott (2022), “Integrating Data Science Ethics Into an Undergraduate Major: A Case Study,” Journal of Statistics and Data Science Education, 30:1, 15-28, DOI: 10.1080/26939169.2022.2038041
• Boenig-Liptsin, M,  A Tanweer, and A Edmundson (2022), “Data Science Ethos Lifecycle: Interplay of ethical thinking and data science practice,” Journal of Statistics and Data Science Education, DOI: 10.1080/26939169.2022.2089411

Readings on inclusive datasets:

• Liao, S (2022), “SCRATCH to R: Toward an Inclusive Pedagogy in Teaching Coding,” Journal of Statistics and Data Science Education, DOI: 10.1080/26939169.2022.2090467 
• National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, and Sexual Orientation. Washington, DC: The National Academies Press. https://doi.org/10.17226/26424. https://nap.nationalacademies.org/catalog/26424/measuring-sex-gender-identity-and-sexual-orientation
• Smith, N, A Reid, and P Petocz (2009), “Representations of Internationalisation in Statistics Education,” Journal of Statistics Education, 17:1, DOI: 10.1080/10691898.2009.11889506
• Rossman, A and F Simpson (2022), “Interview with Felicia Simpson: Statistics at an HBCU,” Journal of Statistics and Data Science Education, 30:1, 75-81, DOI: 10.1080/26939169.2022.2033561

Thank you to the Department Diversity Committee for supporting the development of this resource.