This study investigated patterns in the development of computational thinking and programming expertise in the context of the Exploring Computer Science (ECS) program, a high school introductory CS course and professional development program designed to foster deep engagement through equitable inquiry around CS concepts. Prior research on programming expertise has identified three general areas of development — program comprehension, program planning, and program generation. The pedagogical practices in ECS are consistent with problem solving approaches that support the development of programming expertise. The study took place in a large urban district during the 2016–17 school year with 28 ECS teachers and 1,931 students. A validated external assessment was used to measure the development of programming expertise. The results indicate that there were medium-sized, statistically significant increases from pretest to posttest, and there were no statistically significant differences by gender or race/ethnicity. After controlling for prior academic achievement, performance in the ECS course correlated with performance on the posttest. With respect to specific programming concepts, the results also provide evidence on the progression of the development of programming expertise. Students seem to develop comprehension and planning expertise prior to expertise in program generation. In addition, students seem to develop expertise with concrete tasks prior to abstract tasks.
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Equal Outcomes 4 All: A Study of Student Learning in ECS
This study investigated patterns in the development of computational thinking practices in the context of the Exploring Computer Science (ECS) program, a high school introductory CS course and professional development program designed to foster deep engagement through equitable inquiry around CS concepts. Past research indicates that the personal relevance of the ECS experience influences students' expectancy-value towards computer science. Expectancy-value is a construct that is predictive of career choices. We extended our research to examine whether expectancy-value influences the development of computational thinking practices. This study took place in the context of two ECS implementation projects across two states. Twenty teachers, who implemented ECS in 2016–17, participated in the research. There were 906 students who completed beginning and end of year surveys and assessments. The surveys included demographic questions, a validated expectancy-value scale, and questions about students' course experiences. The assessments were developed and validated by SRI International as a companion to the ECS course. Overall, student performance statistically increased from pretest to posttest with effect size of 0.74. There were no statistically significant differences in performance by gender or race/ethnicity. These results are consistent with earlier findings that a personally relevant course experience positively influences students' expectancy for success. These results expanded on prior research by indicating that students' expectancy-value for computer science positively influenced student learning.
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- NSF-PAR ID:
- 10077365
- Date Published:
- Journal Name:
- SIGCSE Technical Symposium
- Page Range / eLocation ID:
- 50 to 55
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3159450.3159529
