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Nga Than; Leanne Fan; Tina Law; Laura K. Nelson; Leslie McCall – Sociological Methods & Research, 2025
Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using…
Descriptors: Artificial Intelligence, Coding, Qualitative Research, Cues
When Color Coding Backfires: A GuidanceĀ Reversal Effect When Learning with Realistic Visualizations
Skulmowski, Alexander – Education and Information Technologies, 2022
Digital learning increasingly makes use of realistic visualizations, although realism can be demanding for learners. Color coding is a popular way of helping learners understand visualizations and has been found to aid in learning with detailed visualizations. However, previous research has shown that color coding must not always be an effective…
Descriptors: Color, Coding, Visualization, Electronic Learning
Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence

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