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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
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Harpreet Auby; Namrata Shivagunde; Vijeta Deshpande; Anna Rumshisky; Milo D. Koretsky – Journal of Engineering Education, 2025
Background: Analyzing student short-answer written justifications to conceptually challenging questions has proven helpful to understand student thinking and improve conceptual understanding. However, qualitative analyses are limited by the burden of analyzing large amounts of text. Purpose: We apply dense and sparse Large Language Models (LLMs)…
Descriptors: Student Evaluation, Thinking Skills, Test Format, Cognitive Processes
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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