Information Technology two of themost ubiquitous STEM fields in the 21 st century. No matter the discipline area, it is clear fromlooking at workplace trends that students’ studies and professional development would benefitfrom exposure to, and comfort with, computing skills such as programming, and increasedfacility in computational thinking. Introducing a broader range of students to coding andcomputational thinking practices has been used as a strategy for broadening participation incomputing (BPC) [1, 2]. There have been numerous calls to bring computational thinking intothe general K-12 curriculum to both improve computational literacy in the next generation andenhance general education (e.g., [3, 4]). A recommended approach to teachers
general concepts about com- noted. This was the third format in which the same CSputers, including key terms such as “algorithm”, “program”, concepts were presented (Fig. 1). During the last 20 minutes“programming languages” and so on. In this phase, we used of this segment, the students who needed help in reading were“making a peanut butter and jelly sandwich” as an example to released to participate in the reading activity for that week. Theemphasize the importance of precision in
-378[9] Gutsell, J. and Inzlicht, M. (2010). Empathy constrained: Prejudice predicts reduced mental simulation of actions during observation of outgroups. Journal of Experimental Social Psychology, 46(5), pp.841-845.[10] Johns, M., Inzlicht, M. and Schmader, T. (2008). Stereotype threat and executive resource depletion: Examining the influence of emotion regulation. Journal of Experimental Psychology: General, 137(4), pp.691-705.[11] Roussou, M. and Slater, M. (2017). Comparison of the Effect of Interactive versus Passive Virtual Reality Learning Activities in Evoking and Sustaining Conceptual Change. IEEE Transactions on Emerging Topics in Computing, pp.1-1.[12] Riva, G., Baños, R., Botella, C
size that is more reflective of the variedpersonnel in engineering will help us create a more inclusive and well-rounded dataset foranalysis. From this study, anecdotal evidence, at least, has been generated to show that peoplenavigating engineering environments do hold implicit bias. Further work is necessary tounderstand the ways in which eye-tracking can be used to accurately detect such biases.References[1] D. Chubin, G. May and E. Babco, "Diversifying the Engineering Workforce", Journal of Engineering Education, vol. 94, no. 1, pp. 73-86, 2005.[2] G. May and D. Chubin, "A Retrospective on Undergraduate Engineering Success for Underrepresented Minority Students", Journal of Engineering Education, vol. 92, no. 1, pp. 27