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AIET 2027: International Conference on Artificial Intelligence in Education Technology

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AIET
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投稿締切日:
2027-02-20 残り 147 日
通知日:
2027-03-20
開催日:
2027-07-28
開催地:
Cologne, Germany
開催回数:
閲覧: 7860   フォロー: 0   参加: 0

会伴インデックス (CP-I)

49.4 / 100
全 5,687 件中 第 1,725 位 · 上位 31%

教育・学習テクノロジー 分野 139 件中 第 34 位 人工知能・機械学習 分野 741 件中 第 177 位

学術的評価 (35%) データなし — 中立の基準値 50 点として算入 —
投稿の選択性 (20%) データなし — 中立の基準値 50 点として算入 —
開催回数 (20%)
59
コミュニティの注目度 (10%)
19
公開情報の充実度 (15%)
55

使用した入力: 確認できる開催回数：8 · 過去 24 か月にこのページを開いた研究者：11 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 最優秀論文の記録 (+2.3)
主催者は会議を認証申請したうえで、このページから直接追加できます。スコアは毎晩再計算されます。このスコアを上げるには

信頼度 45% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.1 · 算出日 2026-09-25

論文募集

AIET 2027 (International Conference on Artificial Intelligence in Education Technology) is an academic conference held in Cologne, Germany on 2027-07-28. The paper submission deadline is 2027-02-20. Acceptance notifications are sent on 2027-03-20.

We sincerely invite contributions to 2027 8th International Conference on Artificial Intelligence in Education Technology (AIET 2026). AIET 2026 conference will take place in Cologne, Germany during July 28-30, 2027. Topics of interest for submission include as following: Learning Contexts and Informal Learning: Educational games and gamification; Collaborative and group learning; Social networks; Inquiry learning; Social dimensions of learning; Communities of practice; Ubiquitous learning environments; Learning through construction and making; Learning grid; Lifelong, museum, out-of-school, and workplace learning Inequity and inequality in education: socio-economic, gender, and racial issues. Intelligent techniques to support disadvantaged schools and students. Ethics in educational research: sponsorship, scientific validity, participant’s rights and responsibilities, data collection, management and dissemination Design, Use, and Evaluation of human-AI hybrid systems for learning: Research that explores the potential of human-AI interaction in educational contexts; Systems and approaches in which educational stakeholders and AI tools build upon each other’s complementary strengths to achieve educational outcomes and/or improve mutually Online and distance learning: massive open online courses; remote learning in k-12 schools; synchronous and asynchronous learning; mobile learning; active learning in virtual settings Evaluation in the Context of Education Technologies: Studies on human learning, cognition, affect, motivation, and attitudes; Design and formative studies of AI education systems; Evaluation techniques relying on computational analyses Innovative Applications: Domain-specific learning applications (e.g. language, science, engineering, mathematics, medicine, military, industry); Scaling up and large-scale deployment of AI education systems Intelligent and Interactive Technologies in an Educational Context: Natural language processing and speech technologies; Data mining and machine learning; Knowledge representation and reasoning; Semantic web technologies; Multi-agent architectures; Tangible interfaces, wearables and augmented reality Intelligent Techniques to Support Disadvantaged Schools and Students, Inequity and Inequality in Education: Socio-economic, gender, and racial issues. Ethics in educational research: sponsorship, scientific validity, participant's rights and responsibilities, data collection, management and dissemination Learning Contexts and Informal Learning: Educational games and gamification; Collaborative and group learning; Social networks; Inquiry learning; Social dimensions of learning; Communities of practice; Ubiquitous learning environments; Learning through construction and making; Learning grid; Lifelong, museum, out-of-school, and workplace learning Modelling and Representation: Models of learners, including open learner models; facilitators, tasks and problem-solving processes; Models of groups and communities for learning; Modelling motivation, metacognition, and affective aspects of learning; Ontological modelling; Computational thinking and model-building; Representing and analyzing activity flow and discourse during learning Models of Teaching and Learning: Intelligent tutoring and scaffolding; Motivational diagnosis and feedback; Interactive pedagogical agents and learning companions; Agents that promote metacognition, motivation and affect; Adaptive question-answering and dialogue, Educational data mining, Learning analytics and teaching support, Learning with simulations
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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
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
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536
AIEEE Transactions on Dependable and Secure Computing7.5IEEE1545-5971

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