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IEEE TALE 2026: International Conference on Teaching, Assessment, and Learning for Engineers

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IEEE TALE
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投稿締切日:
2026-07-26 Extended
通知日:
2026-09-01
開催日:
2026-12-02
開催地:
Pattaya, Thailand
開催回数:
閲覧: 27257   フォロー: 1   参加: 2

論文募集

IEEE TALE 2026 (International Conference on Teaching, Assessment, and Learning for Engineers) is an academic conference held in Pattaya, Thailand on 2026-12-02. The paper submission deadline is 2026-07-26 (extended). Acceptance notifications are sent on 2026-09-01.

Conference Overview IEEE TALE is the flagship Asia-Pacific conference of the IEEE Education Society. In 2026, hosted by the IEEE Thailand Section, we gather in the coastal city of Pattaya to explore how modern technologies—with a spotlight on Artificial Intelligence—are reshaping the pedagogical landscape. We invite researchers, educators, and industry practitioners to share innovations that move education from universal access to personalized, AI-driven excellence. In 2026, IEEE TALE returns as a leading international forum dedicated to advancing innovation and excellence in engineering, technology, and computing education across the Asia-Pacific region and beyond. IEEE TALE 2026 brings together academic, industry, and government professionals to explore emerging trends, research, and practical applications related to technology-enhanced learning, engineering education, artificial intelligence in education, digital transformation, and future learning environments. The conference provides an inclusive platform for collaboration, networking, and the exchange of ideas focused on improving teaching, learning, and educational accessibility in an increasingly connected world. Recognized as a premier international conference in the field of educational innovation and technology-enhanced learning, IEEE TALE fosters interdisciplinary dialogue among educators, researchers, instructional designers, policymakers, and industry leaders. The conference aims to promote impactful research, share innovative practices, and encourage global partnerships that contribute to the future of education and workforce development. Special Focus How AI Affects Education This year’s conference specifically examines the “AI Inflection Point.” We seek papers that explore the dual nature of AI as both a tool for empowerment and a challenge to traditional academic integrity. Key areas of impact include: Generative AI and LLMs: Impact of AI on curriculum design, personalized tutoring, and automated feedback. AI-Enhanced Assessment: Automated grading, plagiarism detection in the age of AI, and shift toward authentic, AI-resistant assessment. Adaptive Learning Systems: Intelligent tutoring systems (ITS), recommendation engines for student learning paths, and hyper-personalization. Ethical AI & Governance: Bias in educational datasets, data privacy, student security, and institutional policy for AI use. Learning Analytics: Educational data mining to predict student performance and enhance retention. Human-AI Collaboration: The evolving role of the teacher as an “AI co-pilot” and building AI literacy for students and faculty. Technical Tracks Special Track: AI for Education (Conference Spotlight) Generative AI & LLMs: AI-Enhanced Assessment: Adaptive Learning Systems: Ethical AI & Governance: Learning Analytics: Human-AI Collaboration: Core TALE Tracks Online, Open, and Flexible Learning: Emerging Learning Technologies: Curriculum, Assessment, and Learning Sciences Learner Experience and Outcomes Credentials, Ethics, and Educational Systems Entrepreneurship and Innovation in Education
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関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
IEEE Computer2.3IEEE0018-9162
IEEE Software3.3IEEE0740-7459
IEEE Intelligent Systems6.1IEEE1541-1672
IEEE Network6.3IEEE0890-8044
IAENG International Journal of Computer ScienceInternational Association of Engineers1819-656X
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X

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