Altering the Vision of Who Can Succeed in Computing
It’s been exciting following the Twitter Chats and other social media buzz surrounding ‘Computer Science Education Week’ and ‘Hour of Code’. Yet with heavy classroom emphasis and all these interventions, computer science (CS) still fails to engage many students ‘beyond the hour’ and the technology workforce continues to suffer from a lack of diversity.
Oracle Academy and Couragion released a timely new research report this week entitled “Altering the Vision of Who Can Succeed in Computing” that helps to understand and address the engagement of underrepresented student populations in CS. This research shows that in thinking ‘beyond the hour’, we must frame coding skills within the context of careers in order to inspire students to pursue and thrive in CS. The timeliness of the insights can help to extend the momentum of ‘CS Education Week’.
The research report is an 'insider view' from the student's perspective about their perception of tech careers and which indicators influence their own quest for occupational identity. Key findings include:
After exposure to tech careers, students expressed positive or neutral sentiment about tech career pathways 75% of the time.
High numbers of students (aged 10 to 16) received a ʻBest Fitʼ for Data, Design, and Product careers. This is especially true for females and students of color, whereby 2 to 3.5x more students received ʻBest Fitsʼ for Data, Design, and Product careers compared to Programming careers.
Only 1/3 of students had affinity for the Software Developer career – landing at the bottom of the list of all tech careers explored, regardless of gender or race.
Educators, advocates and career influencers can leverage these research findings to improve their teaching and learning with respect to what inspires individuals and how they select careers. The findings establish that computing careers can be for everyone.
The full report is available at: www.couragion.com/cs-report.
This material is based upon work supported by the National Science Foundation under Grant No. 1660021. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
