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Direct linkRoger Young; Emily Courtney; Alexander Kah; Mariah Wilkerson; Yi-Hsin Chen – Teaching of Psychology, 2025
Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…
Descriptors: Item Response Theory, Multiple Choice Tests, Psychology, Textbooks
Mickael Antoine Joseph; Jansirani Natarajan; Omar Al Zaabi; Srinivasa Rao Sirasanagandla – Anatomical Sciences Education, 2025
Anatomy and physiology courses are foundational in nursing education but are often perceived as challenging due to heavy content load. Innovative teaching methods, including social media platforms like Instagram Reels, may enhance student engagement and learning. In this quasi-experimental pre-post-test design with a control group, we examined the…
Descriptors: Student Motivation, Anatomy, Physiology, Science Instruction
Yangqiuting Li; Chandralekha Singh – Physical Review Physics Education Research, 2025
Research-based multiple-choice questions implemented in class with peer instruction have been shown to be an effective tool for improving students' engagement and learning outcomes. Moreover, multiple-choice questions that are carefully sequenced to build on each other can be particularly helpful for students to develop a systematic understanding…
Descriptors: Physics, Science Instruction, Science Tests, Multiple Choice Tests
Download full textQiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests
