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Improvement of Procedural Fidelity in Discrete-Trial Programs Using Computer-Based Instruction to Teach Skilled Observation
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Karen M. Lionello-DeNolf; David Eckerman; Rebecca Hise; Elizabeth Pinzino; Roger Ray – Journal of Applied Behavior Analysis, 2025
Procedural fidelity is an important component of behavioral intervention programs. The "Train-to-Code" software was used to teach skilled observation of implementation of three types of discrete-trial programs, and improvement to procedural fidelity was assessed. Participants completed a training package that involved coding video…
Descriptors: Fidelity, Computer Assisted Instruction, Applied Behavior Analysis, Behavior Modification
Using ChatGPT as a Tool for Training Nonprogrammers to Generate Genomic Sequence Analysis Code
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Haley A. Delcher; Enas S. Alsatari; Adeyeye I. Haastrup; Sayema Naaz; Lydia A. Hayes-Guastella; Autumn M. McDaniel; Olivia G. Clark; Devin M. Katerski; Francois O. Prinsloo; Olivia R. Roberts; Meredith A. Shaddix; Bridgette N. Sullivan; Isabella M. Swan; Emily M. Hartsell; Jeffrey D. DeMeis; Sunita S. Paudel; Glen M. Borchert – Biochemistry and Molecular Biology Education, 2025
Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how…
Descriptors: Artificial Intelligence, Technology Uses in Education, Training, Teaching Methods
Automated Coding of Communications in Collaborative Problem-Solving Tasks Using ChatGPT
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Jiangang Hao; Wenju Cui; Patrick Kyllonen; Emily Kerzabi; Lei Liu; Michael Flor – Journal of Educational Measurement, 2025
Collaborative problem solving is widely recognized as a critical 21st-century skill. Assessing collaborative problem solving depends on coding the communication data using a construct-relevant framework, and this process has long been a major bottleneck to scaling up such assessments. Based on five datasets and two coding frameworks, we…
Descriptors: Cooperative Learning, Problem Solving, 21st Century Skills, Automation
Qualitative Coding with GPT-4: Where It Works Better
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Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
Effects of Worked Examples with Explanation Types and Learner Motivation on Cognitive Load and Programming Problem-Solving Performance
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Chun-Ying Chen – ACM Transactions on Computing Education, 2025
This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…
Descriptors: Models, Learning Motivation, Cognitive Processes, Difficulty Level
Nurturing Code Quality: Leveraging Static Analysis and Large Language Models for Software Quality in Education
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Eman Abdullah AlOmar – ACM Transactions on Computing Education, 2025
Large Language Models (LLMs), such as ChatGPT, have become widely popular for various software engineering tasks, including programming, testing, code review, and program comprehension. However, their impact on improving software quality in educational settings remains uncertain. This article explores our experience teaching the use of Programming…
Descriptors: Coding, Natural Language Processing, Artificial Intelligence, Computer Software