Abstract:

In this paper, we:
(a) introduce the rationale for and elements of the course redesign,
(b) describe our methodology,
(c) present our findings, and
(d) share recommendations for further research and promising practices.

Introduction:
Computer Science (CS) degrees are in high demand and a pathway to well paid jobs, however institutions of higher education in the United States are failing students of color and women. For example, 35.43%of Computer Science degrees were awarded to White students (6.81% to white women), 8.49% to Latino students (1.73% Latinas), and 3.74% to Black students (0.985% to Black women) (National Center for Education Statistics, 2022). Our project sought to iteratively develop, test, and refine learning materials to support the hybrid offering of introductory CS courses with the aims of providing diverse students with culturally responsive content based on their personal characteristics, background contexts, and learning experiences.

Methods:
Redesign courses occurred in Computer Science departments at a public university and a community college in San Diego, CA, USA. Redesigned courses were delivered 20 times to over 500 students from 2019-2022. To assess the impact of the course redesign, we conducted end-of-semester surveys (n=396) based on students’ efficacy, career interest, active participation, validation of students, and cultural relevance. Surveys were also administered to non-redesigned introductory computer science courses. We have a racially diverse sample that includes: 39% White, 32% Latino, 19% Asian/Pacific islander, 4.4% Black, and 2% American Indian/Alaskan Native; 3.2% preferred not to share. In terms of gender, there were 69% male students, 27% women, and 1% non-binary; 3% preferred not to share.

Findings:
We found statistically significant impacts of the course redesign for all measures except for career interest. Students in the redesigned and non-redesigned courses demonstrated high career interests. Students in redesigned courses were significantly more engaged by asking the professor questions in class (83% compared to 73%, p< .05). Students in CS redesigned courses were significantly (p< .05) more likely to feel validated compared to students in non-redesigned CS courses across all measures: “Comfortable asking CS instructors question on misunderstood concepts” (81% compared to 67%), “CS instructors understood students’ strengths” (60% compared to 38%), “CS instructors helped students improve class performance” (82% compared to 56%), and “Students felt they mattered to their CS instructor” (79% compared to 62%). Students were also significantly (p< .05) more likely to report cultural relevance in their CS redesigned courses compared to students in non-redesigned courses: “Students were able to share their life experiences/interests in CS classes” (59% compared to 29%) and “Representations of their cultural identity/ies were included in course material/class topics” (48% compared to 30%).

Conclusions:
The redesigned courses demonstrated an effective pedagogical approach that can work toward closing equity gaps in Computer Science. Our future research will explore the specific experiences of minority groups (race and gender) in the redesigned courses. Promising practices will include the student-centered, interactive curriculum created (available as open source) and the training for culturally responsive teaching in Computer Science.

Keywords:

Computer science education, STEM education, course redesign, diversity, culturally sustaining pedagogy, cultural validation theory, student engagement.