Artificial Intelligence in Stem Education: The Paradigmatic Shifts in Research, Education, and Technology

ISBN-13: 9781032009216 / Angielski / Twarda / 2022 / 460 str.

Ouyang, Fan

Opis

Artificial intelligence (AI) opens new opportunities for STEM education in K-12, higher education, and professional education contexts. This book summarizes AI in education (AIED) with a particular focus on the research, practice, and technological paradigmatic shifts of AIED in recent years.

Spis treści

Section I: AI-Enhanced Adaptive, Personalized Learning  1. Artificial intelligence in STEM education: current developments and future considerations  2. Towards a deeper understanding of K-12 students' CT and engineering design processes  3. Intelligent science stations bring AI tutoring into the physical world  4. Adaptive Support for Representational Competencies during Technology-Based Problem Solving in STEM  5. Teaching STEM subjects in non-STEM degrees: An adaptive learning model for teaching Statistics  6. Removing barriers in self-paced online learning through designing intelligent learning dashboards Section II: AI-Enhanced Adaptive Learning Resources  7. PASTEL: Evidence-based learning engineering methods to facilitate creation of adaptive online courseware  8. A Technology-Enhanced Approach for Locating Timely and Relevant News Articles for Context-Based Science Education  9. Adaptive learning profiles in the education domain Section III: AI-Supported Instructor Systems and Assessments for AI and STEM Education  10. Teacher orchestration systems supported by AI: Theoretical possibilities and practical considerations  11. The role of AI to support teacher learning and practice: A review and future directions  12. Learning outcome modeling in computer-based assessments for learning  13. Designing automated writing evaluation systems for ambitious instruction and classroom integration  Section IV: Learning Analytics and Educational Data Mining in AI and STEM Education  14. Promoting STEM education through the use of learning analytics: A paradigm shift  15. Using learning analytics to understand students’ discourse and behaviors in STEM education  16. Understanding the role of AI and learning analytics techniques in addressing task difficulties in STEM education  17. Learning analytics in a Web3D-based inquiry learning environment  18. On machine learning methods for propensity score matching and weighting in educational data mining applications  19. Situating AI (and Big Data) in the Learning Sciences: Moving toward large-scale learning sciences  20. Linking Natural Language Use and Science Performance  Section V: Other Topics in AI and STEM Education  21. Quick Red Fox: An app supporting a new paradigm in qualitative research on AIED for STEM  22. A systematic review of AI applications in computer-supported collaborative learning in STEM education  23. Inclusion and equity as a paradigm shift for artificial intelligence in education