{"id":8061,"date":"2026-08-18T15:04:10","date_gmt":"2026-08-18T15:04:10","guid":{"rendered":"https:\/\/iccies.tdtu.edu.vn\/2027\/?page_id=8061"},"modified":"2026-08-26T04:03:04","modified_gmt":"2026-08-26T04:03:04","slug":"ai-driven-intelligent-digital-education","status":"publish","type":"page","link":"https:\/\/iccies.tdtu.edu.vn\/2027\/ai-driven-intelligent-digital-education\/","title":{"rendered":"AI-Driven Intelligent Digital Education"},"content":{"rendered":"\n<h2 class=\"wp-block-heading has-text-align-center\">AI-Driven Intelligent Digital Education: Agentic Systems, Learning Analytics, and Smart Learning Environments &#8211; AIDE<span style=\"font-size: medium; font-weight: 400; white-space: normal;\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">I. Objectives<\/h3>\n\n\n\n<p>Artificial intelligence is rapidly reshaping digital education through generative models, intelligent tutoring, learning analytics, adaptive systems, multimodal interfaces, connected devices, and autonomous agents. These advances create new opportunities to personalize learning, support educators, automate feedback and assessment, and strengthen data-informed educational governance. At the same time, they raise significant engineering and societal challenges related to system reliability, privacy, security, fairness, transparency, interoperability, human oversight, and responsible deployment.<\/p>\n\n\n\n<p>The proposed special session, \u201cAI-Driven Intelligent Digital Education: Agentic Systems, Learning Analytics, and Smart Learning Environments,\u201d will provide an interdisciplinary forum for researchers, engineers, educators, data scientists, technology developers, and policy-oriented scholars working at the intersection of computational intelligence and education. The session is aligned with ICCIES 2027 through its emphasis on intelligent computing, information technology, IoT-enabled ecosystems, and deployable engineering solutions for education.<\/p>\n\n\n\n<p>The session particularly welcomes technically rigorous and empirically validated work on AI-based educational systems, agentic and generative AI, adaptive learning, learning analytics, educational data mining, smart classrooms, AI\u2013IoT integration, and trustworthy AI. Contributions should make a clear computational, methodological, system-design, evaluation, or implementation contribution rather than treating technology only as a contextual variable. The session aims to connect foundational computational research with real educational needs across K\u201312, higher education, vocational education, teacher education, and lifelong learning. It also seeks to promote international collaboration and responsible innovation, with particular attention to scalable solutions for diverse, multilingual, and resource-constrained contexts.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">II. Scope<\/h3>\n\n\n\n<p>The primary objectives of this special session are:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>To advance computational intelligence methods and system architectures for digital education.<\/li>\n\n\n\n<li>To explore the design, orchestration, and evaluation of generative and agentic AI for teaching, learning, assessment, and educational management.<\/li>\n\n\n\n<li>To promote robust learning analytics and educational data mining for prediction, personalization, intervention, and decision support.<\/li>\n\n\n\n<li>To investigate AI\u2013IoT and cyber-physical solutions for smart classrooms, laboratories, campuses, and STEM\/STEAM learning environments.<\/li>\n\n\n\n<li>To address trustworthiness, privacy, security, fairness, explainability, human oversight, and governance in AI-enabled education.<\/li>\n\n\n\n<li>To connect researchers, educational institutions, technology providers, and public-sector stakeholders around scalable and evidence-based digital education solutions.<\/li>\n<\/ul>\n\n\n\n<p>We invite original research papers, systematic or scoping reviews with a strong computational contribution, datasets and benchmarks, system and prototype papers, experimental studies, and evidence-based case studies. Topics of interest include, but are not limited to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Generative and Agentic AI for Education<\/strong><ul><li>Educational large language models and domain-adapted foundation models<\/li><\/ul><ul><li>Agentic AI, multi-agent systems, and AI orchestration for learning<\/li><\/ul><ul><li>Retrieval-augmented generation and knowledge-grounded educational assistants<\/li><\/ul><ul><li>Intelligent tutoring systems, conversational tutors, and pedagogical agents<\/li><\/ul><ul><li>Automated feedback, question generation, assessment, and rubric-based scoring<\/li><\/ul><ul><li>Multimodal generative AI for educational content and interaction<\/li><\/ul>\n<ul class=\"wp-block-list\">\n<li>Teacher\u2013AI and learner\u2013AI collaboration, human-in-the-loop learning systems<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Adaptive Learning, Learning Analytics, and Educational Data Mining<\/strong><ul><li>Learner modeling, knowledge tracing, and competency modeling<\/li><\/ul><ul><li>Personalized and adaptive learning algorithms<\/li><\/ul><ul><li>Learning analytics dashboards and intelligent decision-support systems<\/li><\/ul><ul><li>Early warning, dropout prediction, and learning-risk detection<\/li><\/ul><ul><li>Process mining, sequence modeling, and multimodal learning analytics<\/li><\/ul><ul><li>Causal inference, experimentation, and impact evaluation in digital learning<\/li><\/ul>\n<ul class=\"wp-block-list\">\n<li>Educational recommender systems and adaptive resource allocation<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Smart Learning Environments and AI\u2013IoT Ecosystems<\/strong><ul><li>AI\u2013IoT integration in smart classrooms, laboratories, and campuses<\/li><\/ul><ul><li>Edge AI, wearable and sensor-based learning technologies<\/li><\/ul><ul><li>Robotics, computer vision, and intelligent interfaces for education<\/li><\/ul><ul><li>Virtual, augmented, mixed-reality, and digital-twin learning environments<\/li><\/ul><ul><li>Cloud\u2013edge architectures and interoperability for digital education platforms<\/li><\/ul>\n<ul class=\"wp-block-list\">\n<li>AI-supported STEM\/STEAM education, maker education, and programming learning<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Trustworthy, Secure, and Inclusive AI in Education<\/strong><ul><li>Explainable, transparent, accountable, and auditable educational AI<\/li><\/ul><ul><li>Fairness, bias detection, and equitable algorithmic decision-making<\/li><\/ul><ul><li>Privacy-preserving learning analytics and federated learning<\/li><\/ul><ul><li>Cybersecurity, identity, consent, and data governance in educational systems<\/li><\/ul><ul><li>Reliability, hallucination mitigation, robustness, and safety evaluation<\/li><\/ul><ul><li>Accessible, inclusive, culturally responsive, and multilingual AI systems<\/li><\/ul>\n<ul class=\"wp-block-list\">\n<li>Academic integrity, authentic assessment, and responsible use of generative AI<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Digital Competence, Teacher Development, and System Adoption<\/strong><ul><li>AI literacy and digital competence modeling and assessment<\/li><\/ul><ul><li>Technology acceptance, sustained use, and human factors in educational AI<\/li><\/ul><ul><li>AI-supported teacher education and professional development<\/li><\/ul><ul><li>Institutional readiness, digital transformation, and smart education governance<\/li><\/ul>\n<ul class=\"wp-block-list\">\n<li>Scalable deployment and evaluation in developing and resource-constrained contexts<\/li>\n\n\n\n<li>Standards, policy, ethics, and quality assurance for AI-enabled education<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">III. Submission link: <a href=\"https:\/\/iccies.tdtu.edu.vn\/2027\/how-to-submit\/\" data-type=\"page\" data-id=\"6712\">click here<\/a><\/h3>\n\n\n\n<p>Please select the Track\/Session: \u201cAI-Driven Intelligent Digital Education<strong>:<\/strong> Agentic Systems, Learning Analytics, and Smart Learning Environments &#8211; AIDE\u201d during submission<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">IV. <strong>Session Organizers<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Hung Tran Van, The University of Danang \u2013 University of Science and Education, Vietnam, tvhung@ued.udn.vn<\/li>\n\n\n\n<li>Nguyen Thanh Hung, The University of Danang \u2013 University of Science and Education, Vietnam, nthung@ued.udn.vn<\/li>\n\n\n\n<li>Dinh Thi My Hanh, The University of Danang \u2013 University of Science and Education, Vietnam, dtmhanh@ued.udn.vn<\/li>\n\n\n\n<li>Le Thanh Huy, The University of Danang \u2013 University of Science and Education, Vietnam, lthuy@ued.udn.vn<\/li>\n\n\n\n<li>Nguyen Thi Trieu Tien, The University of Danang \u2013 University of Science and Education, Vietnam, ntttien@ued.udn.vn<\/li>\n\n\n\n<li>Le Thi Thanh Tinh, The University of Danang \u2013 University of Science and Education, Vietnam, ltttinh@ued.udn.vn<\/li>\n\n\n\n<li>Ngo Thi Hoang Van, The University of Danang \u2013 University of Science and Education, Vietnam, nthvan@ued.udn.vn<\/li>\n\n\n\n<li>Emmanuel Dupl\u00e0a, University of Ottawa, Canada, eduplaa@uOttawa.ca<\/li>\n\n\n\n<li>Arun Patil, Curtin University Singapore, Singapore, Arun.Patil@curtin.edu.au<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI-Driven Intelligent Digital Education: Agentic Systems, Learning Analytics, and Smart Learning Environments &#8211; AIDE I. Objectives Artificial intelligence is rapidly reshaping digital education through generative models, intelligent tutoring, learning analytics, adaptive systems, multimodal interfaces, connected devices, and autonomous agents. These advances create new opportunities to personalize learning, support educators, automate feedback and assessment, and strengthen &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/iccies.tdtu.edu.vn\/2027\/ai-driven-intelligent-digital-education\/\" class=\"more-link\">Read more<span class=\"screen-reader-text\"> &#8220;AI-Driven Intelligent Digital Education&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/no-title.php","meta":{"footnotes":""},"class_list":["post-8061","page","type-page","status-publish","hentry"],"featured_media_urls":[],"_links":{"self":[{"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/pages\/8061"}],"collection":[{"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/comments?post=8061"}],"version-history":[{"count":4,"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/pages\/8061\/revisions"}],"predecessor-version":[{"id":8114,"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/pages\/8061\/revisions\/8114"}],"wp:attachment":[{"href":"https:\/\/iccies.tdtu.edu.vn\/2027\/wp-json\/wp\/v2\/media?parent=8061"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}