Artificial Intelligence for STEM Education Research

This open access volume explores the transformative use of Artificial Intelligence (AI) as innovative methodologies in STEM education research. Featuring contributions from leading experts, it presents a rich collection of chapters that examine how AI toolssuch as adaptive learning systems, automatic scoring, explainable AI, and intelligent tutoringcan be applied to enhance educational outcomes. Designed for researchers, educators, and graduate students, the book provides in-depth insights into AI as a tool for cutting-edge research methods and its potential to revolutionize research practices. Through practical examples, case studies, and methodological details, it serves as an essential resource for those looking to push beyond conventional methods and embrace the possibilities offered by AI in educational research.

This book is open access, which means that you have free and unlimited access Focuses on applying Artificial Intelligence to STEM education research Introduces novel AI-driven approaches for personalized learning and assessment, Offers actionable strategies for researchers to implement AI tools effectively in their educational research

Autorentext

Dr. Xiaoming Zhai is an Associate Professor in Science Education and AI, serving as Directors of the AI4STEM Education Center and the National GENIUS Center at the University of Georgia, USA. He was a Humboldt Visiting Professor at IPN in Germany. His research focuses on leveraging AI for science and STEM education. He is the principal investigator on several federal-funded projects, and his research has been published in top-tier journals. He has win numerous awards in teaching and research and serves as a global leader in his area of research.

Gyeonggeon Lee is an Assistant Professor of Science Education at the National Institute of Education, Nanyang Technological University, Singapore. His research focuses on integrating artificial intelligence (AI) into science education, encompassing automatic assessment, human-AI collaboration, and visual question answering. Through the interdisciplinarity enabled by AI, he aims to establish multimodal science learning to fulfill whole-person science education.

Inhalt

Chapter 1. Introduction (XZ).- Chapter 2. GAI for STEM education research (XZ).- Chapter 3. Using GAI for Automatic Scoring (Ehsan, XZ).- Chapter 4. Adaptive Learning in STEM education research (Yizhu).- Chapter 5. Adaptive Testing for STEM Learning (ShiYU).- Chapter 6. Explainable AI in STEM education research (Ninghao).- Chapter 7. Computer Vision in STEM education research (GG, XZ).- Chapter 8. Intelligent Tutor for STEM Learning (Ehsan, Wenchao).- Chapter 9. Recommender Systems for STEM education research (Xuansheng).- Chapter 10. Sentiment Analysis for STEM Learning (Lehong, Shuchen).- Chapter 11. Automated Assessment Generation (Mathew, XZ).- Chapter12. Conclusion (XZ).