Undergraduate programs in computer science (CS) face high dropout rates, and many students struggle while learning to program. Studies show that perceived programming ability is a significant factor in students' decision to major in CS. Fortunately, psychology research shows that promoting the growth mindset, or the belief that intelligence grows with effort, can improve student persistence and performance. However, mindset interventions have been less successful in CS than in other domains. We conducted a small-scale interview study to explore how CS students talk about their intelligence, mindsets, and programming behaviors. We found that students' mindsets rarely aligned with definitions in the literature; some present mindsets that combine fixed and growth attributes, while others behave in ways that do not align with their mindsets. We also found that students frequently evaluate their self-efficacy by appraising their programming intelligence, using surprising criteria like typing speed and ease of debugging to measure ability. We conducted a survey study with 103 students to explore these self-assessment criteria further, and found that students use varying and conflicting criteria to evaluate intelligence in CS. We believe the criteria that students choose may interact with mindsets and impact their motivation and approach to programming, which could help explain the limited success of mindset interventions in CS.
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Preliminary Findings on Students’ Beliefs about Intelligence
The goal of this project is to better understand the beliefs that undergraduate students hold about their own intelligence and how these beliefs change during their undergraduate engineering education. The research team has used the theoretical framework established by Carol Dweck on Mindset and how different fixed and growth mindsets affect success. Fixed mindset individuals believe that their intelligence is an unchanging trait, while people with a growth mindset believe that through effort they can grow and develop greater intelligence. Prior researchers have shown that individuals with a growth mindset respond to challenges with higher levels of persistence, are more interested in improving upon past failures, and value criticism and effort more than those with a fixed mindset. The team developed an interview protocol from the theoretical framework. Then the team piloted the protocol and subsequently modified the protocol multiple times to ensure that the interviews provided rich qualitative data. Analytic memos were used to analyze and modify the piloted interview protocols. Once the final protocol was established, first-year and senior students were recruited to provide cross-sectional insight. The team also recruited using purposeful sampling to ensure that women and underrepresented minorities were included. To date, 19 interviews have been conducted with the final protocol. Of these interviews, four have been coded in detail using the “Attitudes, Values, and Beliefs” coding system. A codebook has also been started to categorize and interconnect the themes in the interview transcripts. This paper provides details of the protocol and coding process as well as preliminary findings on the themes extracted from the student interviews.
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- Award ID(s):
- 1738209
- PAR ID:
- 10108324
- Date Published:
- Journal Name:
- ASEE Annual Conference proceedings
- ISSN:
- 1524-4644
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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