The effectiveness of pair programming: A meta-analysis
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Such interaction modes may arguably make output evaluation more challenging due to the need to infer the intent behind systems' suggestions.
“In fact, such interaction modes may arguably make output evaluation more challenging due to the need to infer the intent behind systems' suggestions [74].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [74]
Self-evaluation interventions can help users reflect on their task goals and approaches to task decomposition.
“self-evaluation interventions can help users reflect on their task goals and approaches to task decomposition [74].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [74]
By developing systems that are context-aware, users can be served AI-generated content or prompts at opportune moments during their workflows.
“By developing systems that are context-aware, users can be served AI-generated content or prompts at opportune moments during their workflows [74].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [74]
In a data science context, GenAI tools can offer a 'think' mode for specific planning suggestions, a 'reflection' mode for connecting decisions and highlighting potential missed steps, and an 'exploration' mode for higher-level planning suggestions.
“In a data science context, Gu et al. [74] propose that GenAI tools can offer “a 'think' mode for specific planning suggestions, a 'reflection' mode for connecting decisions and highlighting potential missed steps, and an 'exploration' mode for higher-level planning suggestions”.”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [74]
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References 69 · Cited by 268
- Authors
- Hannay, J. E., Dybå, T., Arisholm, E., & Sjøberg, D. I. K.
- Affiliations
- University of Oslo (NO)
- SINTEF (NO)
- Corresponding author
- Hannay, Jo E.
- Venue
- Information and Software Technology
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 51
- Issue
- 7
- Pages
- 1110-1122
- ISSN
- 0950-5849 (ISSN-L)
- OpenAlex
- W2141767681
- Cited by
- 268
- References
- 69
- Citations by year
- 2026: 17 · 2025: 18 · 2024: 24 · 2023: 13 · 2022: 16 · 2021: 17 · 2020: 17 · 2019: 12 · 2018: 9 · 2017: 15 · 2016: 13 · 2015: 15 · 2014: 22 · 2013: 14 · 2012: 26
- FWCI
- 5.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information and Software Technology (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Keywords
- pair programming, solo programming, software productivity, code quality, programming effort, task complexity, publication bias, moderators
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