04278nam a22005895i 4500 978-3-031-71232-6 DE-He213 20251030114559.0 cr nn 008mamaa 241202s2024 sz | s |||| 0|eng d 9783031712326 978-3-031-71232-6 10.1007/978-3-031-71232-6 doi TA345-345.5 UN bicssc COM018000 bisacsh UN thema Artificial Intelligence in Education: The Intersection of Technology and Pedagogy [electronic resource] / edited by Peter Ilic, Imogen Casebourne, Rupert Wegerif. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. VI, 315 p. 90 illus., 70 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Intelligent Systems Reference Library, 1868-4408 ; 261 Introduction:Constructive dialogue between technology and pedagogy -- AI-Enhanced Ecological Learning Spaces -- Reimagining Learning Experiences with the Use of AI -- Generative AI integration in education: challenges and approaches -- Navigating AI in Education–Towards a System Approach for Design of Educational Changes -- AI in the Assessment Ecosystem: A Human–Centered AI Perspective -- The role of AI language assistants in dialogic education for collective intelligence -- AI powered adaptive formative assessment: Validity and reliability Evaluation -- Decimal Point: A Decade of Learning Science Findings with a Digital Learning Game -- Leveraging AI to Advance Science and Computing Education across Africa: Challenges, Progress and Opportunities -- Educating Manufacturing Operators by Extending Reality with AI -- Pedagogical Restructuring of Business Communication Courses: AI-Enhanced Prompt Engineering in an EFL Teaching Context -- AI in Language Education: The Impact of Machine Translation and ChatGPT. This book offers a multidisciplinary perspective on the ways in which the careful integration of AI might enhance learning outcomes. By inviting dialogue between engineering (what is possible) and pedagogy (what might be desirable), the book offers a holistic view of AI's potential for education. Offering both case studies of practical implementation and pedagogically informed frameworks, it focuses on appropriately integrating technology for educational benefit, presenting a uniquely broad view. The contributors, who are both educators and technically proficient, bring insights into teaching and assessment approaches, research questions, and technological affordances or constraints. Essential for researchers, educators, and policymakers navigating the rapidly evolving educational technology landscape as AI becomes increasingly prevalent in every aspect of life. Engineering Data processing. Computational intelligence. 64052 Machine learning. 55059 Artificial intelligence. 58441 Data Engineering. 66059 Computational Intelligence. 64052 Machine Learning. 55059 Artificial Intelligence. 58441 Ilic, Peter. editor. edt http://id.loc.gov/vocabulary/relators/edt 88438 Casebourne, Imogen. editor. edt http://id.loc.gov/vocabulary/relators/edt 88439 Wegerif, Rupert. editor. edt http://id.loc.gov/vocabulary/relators/edt 88440 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031712319 Printed edition: 9783031712333 Printed edition: 9783031712340 Intelligent Systems Reference Library, 1868-4408 ; 261 67034 https://doi.org/10.1007/978-3-031-71232-6 ZDB-2-INR ZDB-2-SXIT 65422 65422