Artificial Intelligence for STEM Education Research: Advanced Methods and Applications. Advances in Technology-Rich Science Education. Volume 1

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Artificial Intelligence for STEM Education Research: Advanced Methods and Applications. Advances in Technology-Rich Science Education. Volume 1
Γλώσσα: English
Συγγραφείς: Xiaoming Zhai (ORCID 0000-0003-4519-1931), Gyeonggeon Lee
Πηγή: Springer. 2026.
Διαθεσιμότητα: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail:customerservice@springernature.com; Web site: http://www.springer.com
Peer Reviewed: N
Page Count: 258
Ημερομηνία έκδοσης: 2026
Intended Audience: Researchers; Teachers; Students
Τύπος εγγράφου: Book
Collected Works - General
Descriptors: Artificial Intelligence, Technology Uses in Education, STEM Education, Educational Research, Educational Innovation, Intelligent Tutoring Systems, Computer Assisted Testing, Automation, Scoring, Research Methodology
DOI: 10.1007/978-3-032-06565-0
ISSN: 3091-339X
3091-3403
Περίληψη: 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 tools--such as adaptive learning systems, automatic scoring, explainable AI, and intelligent tutoring--can 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.
Abstractor: As Provided
Entry Date: 2026
Αριθμός Καταχώρησης: ED680659
Βάση Δεδομένων: ERIC
Περιγραφή
ISSN:3091-339X
3091-3403
DOI:10.1007/978-3-032-06565-0