Applying Machine Learning in Science Education Research When, How, and Why?

• Main Authors: Wulff, Peter, Kubsch, Marcus, Krist, Christina
• Format: eBook
• Language: English
• Published: Cham Springer Nature 2025; Springer
• Edition: 1
• Series: Springer Texts in Education
• Subjects: Artificial intelligence; artificial intelligence in Science education; big data; complex systems theory; computational grounded theory; Computer science; computer-aided tutoring; Computing and Information Technology; deep neural networks; Education; human-machine interaction; Human-machine interactions; Machine learning; Machine learning models; Mathematics and Science; multimodal learning; Natural language processing; Pattern recognition; Probabilistic modeling; qualitative and quantitative research methods; reinforcement learning; science education research; Science: general issues; Society and Social Sciences; Study and learning skills: general; supervised and unsupervised learning; Teaching of a specific subject; transfer learning
• ISBN: 9783031742279; 3031742265; 3031742273; 9783031742262
• DOI: 10.1007/978-3-031-74227-9

This open access textbook offers science education researchers a hands-on guide for learning, critically examining, and integrating machine learning (ML) methods into their science education research projects. These methods power many artificial intelligence (AI)-based technologies and are widely ad...