Designing for assets of diverse students enrolled in a freshman-level computer science for all course

Vanessa Svihla, Woong Lim, Elizabeth Ellen Esterly, Irene A. Lee, Melanie E. Moses, Paige Prescott, Tryphenia B. Peele-Eady

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


Proficiency in computer science skills is crucial for today's students to succeed in science, technology, engineering and mathematics (STEM) fields and the modern workforce. Despite this fact, few universities count computer science (CS) classes toward the core curriculum. Our university, a Hispanic- and minority-serving research-intensive university located in the American Southwest, recently began counting CS towards fulfilling the laboratory science requirement in the undergraduate core curriculum. This allowed us to consider the characteristics of the students who enrolled in a freshman-level CS course (N=31 students) to identify assets they bring from their diverse life experiences that we might build upon in teaching them. We sought student perceptions of existing curricular modules, in terms of ownership and creativity. Students completed pre-course surveys about their CS interests, beliefs, prior knowledge and experiences, along with demographics. They completed a brief survey to evaluate some of the modules. We examined descriptive statistics, then conducted tests of difference to identify students' assets. We explored contrasts between 1) first-generation college students and their traditional peers; and 2) students from historically underrepresented and well-represented groups in computer science. Students who were first in their family to attend college were significantly likelier to agree that CS is important for everyone to study, but also likelier to acknowledge being nervous. This finding suggests that creating a supportive learning environment that enables students to experience relevant CS is integral to retaining first-generation college students in CS. Students from underrepresented groups were significantly likelier to agree that CS is important for solving science problems and for helping people understand problem solving using technology. This finding suggests that our approach, which combines programming and modeling to solve science problems, may be a particularly productive fit for these students.

Original languageEnglish
JournalASEE Annual Conference and Exposition, Conference Proceedings
Publication statusPublished - 2017 Jun 24
Event124th ASEE Annual Conference and Exposition - Columbus, United States
Duration: 2017 Jun 252017 Jun 28

Bibliographical note

Funding Information:
Dr. Vanessa Svihla is a learning scientist and assistant professor at the University of New Mexico in the Organization, Information & Learning Sciences program, and in the Chemical & Biological Engineering Department. She served as Co-PI on an NSF RET Grant and a USDA NIFA grant, and is currently co-PI on three NSF-funded projects in engineering and computer science education, including a Revolutionizing Engineering Departments project. She was selected as a National Academy of Education / Spencer Postdoctoral Fellow. Dr. Svihla studies learning in authentic, real world conditions; this includes a two-strand research program focused on (1) authentic assessment, often aided by interactive technology, and (2) design learning, in which she studies engineers designing devices, scientists designing investigations, teachers designing learning experiences and students designing to learn.

Publisher Copyright:
© American Society for Engineering Education, 2017.

All Science Journal Classification (ASJC) codes

  • Engineering(all)


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