Deconstructing Conceptions of Rigor in Computer Science Education
Saved in:
| Title: | Deconstructing Conceptions of Rigor in Computer Science Education |
|---|---|
| Language: | English |
| Authors: | Jayne Everson (ORCID |
| Source: | ACM Transactions on Computing Education. 2026 26(1). |
| Availability: | Association for Computing Machinery. 1601 Broadway 10th Floor, New York, NY 10119. Tel: 800-342-6626; Tel: 212-626-0500; Fax: 212-944-1318; e-mail: acmhelp@acm.org; Web site: http://toce.acm.org/ |
| Peer Reviewed: | Y |
| Page Count: | 25 |
| Publication Date: | 2026 |
| Sponsoring Agency: | National Science Foundation (NSF) |
| Contract Number: | 1539179 1703304 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Secondary Education Higher Education Postsecondary Education |
| Descriptors: | Computer Science Education, Difficulty Level, Teacher Attitudes, Student Attitudes, Secondary School Teachers, College Faculty, College Students, Postsecondary Education, Foreign Countries, Definitions |
| Geographic Terms: | Canada, United States |
| DOI: | 10.1145/3776542 |
| ISSN: | 1946-6226 |
| Abstract: | Objectives: In calls for excellent and equitable Computer Science (CS) education, the word "rigor" often appears, but it often goes undefined. The goal of this work is to understand how CS teachers, instructors, and students conceive of rigor. Research Questions: (1) What do CS instructors think rigor is? and (2) What do students think rigor is? Methods: Using the principles of phenomenological research, we conducted a semi-structured interview study with 10 post-secondary CS students, 10 secondary CS teachers, and 9 post-secondary CS instructors, to understand their conceptions of rigor. Results: Analysis showed that no participants had the same understanding of rigor. We found that participants had abstract "Principles of Rigor" which included: Precision, Systematic Thought Process, Depth of Understanding, and Challenge. They also had concrete "Observations of Rigor" that included Time and Effort, Intrinsic Drive, Productive Failure, Struggle, Outcomes, and Gatekeeping. Participants also shared "Conditions for Rigor" which included Expectations, Standards, Community Support, and Resources. Implications: Our data support prior work that educators are using different definitions of rigor. This implies that each educator holds different expectations for students, without necessarily communicating these expectations to their students. In the best case, this might confuse students; in the worst case, it reinforces hegemonic norms which can lead to gatekeeping which prevents students from fully participating in the CS field. Based on these insights, we argue that to commit to the idea of quality CS learning, the community must discard the use of this concept of rigor to justify student learning and re-imagine alternate benchmarks. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1497383 |
| Database: | ERIC |
| Abstract: | Objectives: In calls for excellent and equitable Computer Science (CS) education, the word "rigor" often appears, but it often goes undefined. The goal of this work is to understand how CS teachers, instructors, and students conceive of rigor. Research Questions: (1) What do CS instructors think rigor is? and (2) What do students think rigor is? Methods: Using the principles of phenomenological research, we conducted a semi-structured interview study with 10 post-secondary CS students, 10 secondary CS teachers, and 9 post-secondary CS instructors, to understand their conceptions of rigor. Results: Analysis showed that no participants had the same understanding of rigor. We found that participants had abstract "Principles of Rigor" which included: Precision, Systematic Thought Process, Depth of Understanding, and Challenge. They also had concrete "Observations of Rigor" that included Time and Effort, Intrinsic Drive, Productive Failure, Struggle, Outcomes, and Gatekeeping. Participants also shared "Conditions for Rigor" which included Expectations, Standards, Community Support, and Resources. Implications: Our data support prior work that educators are using different definitions of rigor. This implies that each educator holds different expectations for students, without necessarily communicating these expectations to their students. In the best case, this might confuse students; in the worst case, it reinforces hegemonic norms which can lead to gatekeeping which prevents students from fully participating in the CS field. Based on these insights, we argue that to commit to the idea of quality CS learning, the community must discard the use of this concept of rigor to justify student learning and re-imagine alternate benchmarks. |
|---|---|
| ISSN: | 1946-6226 |
| DOI: | 10.1145/3776542 |
