Think about your experiences both as a student & as a teacher. Identify instances in which

1. Think about your experiences both as a student & as a teacher. Identify instances in which you felt part of an inclusive, supportive classroom environment. you were not. Think about the factors that contributed to each of these situations.

2. Computational Thinking in K-12: Motivation

3. Projected STEM job growth is in CT

4. Plummeting CS degrees

5. By 2018, there will be 1.4 million computational thinking specialist job openings. • U.S. universities will have generated enough graduates to fill only about 1/3 of these.

6. The missing 70%

7. Schools with higher proportions of students from lower SES are less likely to offer higher level CS courses. • Specifically, affluent students attend schools that are… • 2x more likely to offer CS and web design courses • 3x more likely to offer AP CS • 7x more likely to offer AP CS-B • … than students attended by low-income students*. The Digital Divide * As indicated by the reduced/free-lunch program. Goode (2007) Journal of Educational Computing Research, Vol 36, 65

8. Mistaken Notions • “Even though students hold preconceived notions of who studies computer science, few of them are able to articulate what computer science is. Without … • knowing what computational thinking is • its interdisciplinary connections • relevance to student interests & every day reality • … few students not already enamored with computing end up pursuing these courses.” • Goode (2007) Journal of Education Computing Research, Vol 36 (1) 65-88

9. Lack of broad participation = lack of quality “I believe that engineering is a highly creative profession. Research tells us that creativity does not spring from nothing; it is grounded in our life experiences, and hence limited by those experiences. Lacking diversity on an engineering team, we limit the set of solutions that will be considered and we may not find the best, the most elegant solution” Wulf, Former president of American Academy of Engineers From Ladner (2009).

10. What are some of the national initiatives responding to this situation?[I.e., our CT workshop in context.]

11. National Science Foundation + CS Teachers Association + CT professional group + etc. Curriculum development. National Science Foundation http://delivery.acm.org/10.1145/1960000/1953193/p85-astrachan.pdf?ip=129.105.65.159&CFID=37415432&CFTOKEN=25413769&__acm__=1312841893_c81c85b2b0d6db63cdac2758584a9731

12. K-12 teacher professional development programs http://www.cs.cmu.edu/cs4hs/summer11/index.html http://gk12.ciera.northwestern.edu/

13. Developing the STEM-CS Education Pipeline: Classroom Culture and Climate CT Workshop, 08/11

14. Outline Personal experience Case studies Unconscious bias & stereotype threat Action items for recruitment & retention

15. Think about your experiences both as a student & as a teacher. Identify instances in which you felt part of an inclusive, supportive classroom environment. you were not. Think about the factors that contributed to each of these situations.

16. Read all 4 case studies. Consider the following. What are possible underlying causes for the teacher’s actions and comments? The students interactions? What is the role of preparatory privilege* in setting up these classroom dynamics & how can the teacher address this issue? What steps can the teacher take to: set up a classroom culture encouraging respect and tolerance? enable the feeling of inclusion and belonging for all students? What are the prevailing stereotypes about people who are interested in CS? How can teachers address these stereotypes and why is it important that we do? *Prep privilege: Long-term relative abundance and access to material and intellectual resources that create an out-of-school and home advantage.

17. Unconscious Bias • We have expectations or hypotheses about the characteristics of a person based on their group membership. • These influence our judgments of others (regardless of our own group).

18. These expectations are widely shared within a culture • Both men and women hold them about gender. • Both U.S. whites and people of color hold them about race/ethnicity. • We hold them about people in different jobs or disciplines. • People are often not aware of them. They are often applied in circumstances when there’s a lack of critical mass. Fiske (2002). Current Directions in Psychological Science, 11, 123-128.

19. Hiring, Assessments, and Salaries: Gender When evaluating identical applications: • male and female University psychology professors preferred 2:1 to hire “Brian” over “Karen” as an assistant professor. Karen Brian Steinpreis, Anders, & Ritzke (1999) Sex Roles, 41, 509.

20. Hiring, Assessments, and Salaries: Race Greg When evaluating identical applications: • Whites were invited for one interview for every ten resumes they sent, while black were invited for one interview for every 15 resumes they sent. Jamal Bertrand & Mullainathan(2004)

21. What Can We Do about Unconscious Bias? • Awareness • Practices • Policies • Accountability

22. Strategies for Mitigating Unconscious Bias • Increase conscious awareness of bias and how bias leads to overlooking talent • Implicit Association Test: https://implicit.harvard.edu/implicit/ • Broaden awareness in community • Increase sense of responsibility • Decrease probability of guilt and blame

23. Stereotype Threat “Stereotype threat is a situational threat. It can affect the members of any group about whom a negative stereotype exists (e.g., skateboarders, older adults, White men, gang members). Where bad stereotypes about these groups apply, members of these groups can fear being reduced to that stereotype.” Steele (1997)

24. Change Agents Action Items Recruitement Retention

25. Action Items Authenticity in interactions and advocacy Make explicit career path in terms of applied skills Student & (intensive with followup!) teacher training with tech tools Change stereotypes Career exposure, what CS really is Mentoring, Role models from the field coming in to the classroom After school club, have it part of the culture, personal invitations (with followup!) to specific students, think about the network model for recruiting students Authentic problems in class Encourage CT across the disciplines (english, history, etc)

26. Action Items Present CT w/in context of interdisciplinarity & relevance Confront ‘geek’ mythology (Margolis & Fisher ‘02; Denner ‘07) Value multiple perspectives Stress the expandability of intelligence. Recruit through personal invitations (Horwitz ‘09) Recruit cohorts -- critical mass effect (Margolis ’08) Support development of student learning communities and peer support (Margolis & Fisher ‘02; Denner ‘07) Provide role models from diverse backgrounds Incorporate culturally relevant pedagogy (Edd Taylor ’10) Communicate w/ guidance counselors: unconscious bias; gatekeeper vs. motivator (Goode ‘07)

27. Addressing Stereotype Threat Optimistic teacher-student relationships. Giving challenging work conveys respect for potential. Stress the expandability of intelligence. Affirm domain-belongingness. Important to do this when merited, and not haphazardly. Value multiple perspectives. Role models (i.e., stereotype threat is surmountable)

28. Culturally Relevant Pedagogy • http://homepages.rpi.edu/~eglash/csdt.html • http://sst.clas.asu.edu/compugirls

29. extras

30. Computational Thinking Education Week, ads: Series of videos, showing application of CT in different aspects of society. http://csta.acm.org/Advocacy_Outreach/sub/CSEdWeek.html

31. Hugh Grant: “… film acting is incredibly tedious, just by its nature. It’s incredibly, mind numbingly slow.” “Yet, few people think film acting is boring. Not because it isn’t, but because it’s never portrayed that way. Computer Science has the opposite problem.” Jill Ross -Slide from Jill Ross, Director, Image of Computing Taskforce

32. Comparing STEM-CS Fields

33. Projected Jobs vs Projected Bachelor’s Degrees through 2018

34. Projected Science and Engineering Growth in Occupations 2008-2018 http://www.cccblog.org/2010/01/04/where-the-jobs-are/

35. Schools with higher proportions of students from lower SES are less likely to offer higher level CS courses. Socioeconomic Disparities