Recruitment of Invited Speakers and Track Chairs (PhD and above)
ICBDE 2026 sincerely invites scholars and experts in the fields of big data and education to serve as invited speakers or track chairs. If you are interested or would like to recommend candidates, please send your CV or their CVs to icbdeconference@163.com. All submitted CVs will be carefully reviewed and discussed. Information about invited speakers and track chairs will be featured on the ICBDE 2026 website and related promotional materials. We warmly welcome you to join us.
Publication:
Conference Proceedings: Accepted papers of ICBDE 2026 after proper registration and presentation will be published in the ICBDE 2026 conference proceedings. Conference content will be submitted for indexing by Ei Compendex and Scopus, as the previous years.
Submission Guidelines
1. Originality: Submissions must be original and should not have been published previously.
2. Language: English is the official language of the conference. The paper should be written and presented only in English.
3. Publication & Presentation: Full paper (4 full pages at least) submission is required for paper publication. One regular registration covers 5 pages, including tables, figures, and references. Additional pages will be charged at 70 USD/page.
4. Presentation Only: Abstract (200-300 words) submission is acceptable for presentation only and the abstract will not be published.
5. Paper Template: https://www.icbde.org/acm_template.docx
Submission Methods (Choose one of the two, no duplicate submissions)
1. Online System: https://www.zmeeting.org/submission/ICBDE2026
2. Email: icbdeconference@163.com
Call For Papers
Prospective authors are invited to submit high-quality original technical papers for presentation at the conference and publication in the conference proceedings. Please check the topics of ICBDE 2026. The topics are not limited to those as below:
Topic 1: Big Data Science
Novel theoretical models for educational data
Computational methods for educational data analysis
Data mining techniques in online learning
Predictive analytics for student performance
Big data visualization in education
Data-driven insights for curriculum improvement
Ethical considerations in big data science
Scaling data models for educational environments
Topic 2: Big Data Applications
Personalized learning through big data
Big data for intelligent tutoring systems
Data-driven strategies for course design
Adaptive learning technologies using big data
Big data in student assessment
Case studies of big data in online education
Real-time learning analytics applications
Leveraging big data for student retention
Topic 3: Big Data Management
Data governance frameworks in education
Cloud-based big data solutions for schools
Ensuring data privacy in educational systems
Real-time data processing for online education
Integrating multiple data sources in education
Data quality and consistency management
Data security protocols for educational data
Managing large-scale student data sets
Topic 4: AI in education
AI-driven analytics for personalized learning
Machine learning models for student success prediction
AI-based assessment tools in education
Detecting learning gaps with AI and big data
Automating curriculum design with AI
Ethical implications of AI in education
AI and big data for intelligent classroom management
AI-driven feedback systems for students
Topic 5:
Digital Learning
Enhancing digital classrooms with big data
Learning analytics for digital course delivery
Data-driven strategies for improving student engagement
Personalization of digital learning experiences
Gamification using big data insights
Big data for improving learning outcomes
Learning behavior analytics in digital platforms
Data visualization tools for digital education
Topic 6: STEM Education
Big data for STEM curriculum design
Predictive analytics in STEM education
STEM student engagement using big data
Data-driven teaching strategies in STEM
Big data to track STEM student performance
Enhancing STEM teaching with big data tools
Personalized learning paths for STEM students
Data applications in STEM-based assessments
Conference Schedule
Day 1 – December 02, 2026-Onsite Registration
Day 2 – December 03, 2026-Opening Ceremony & Keynote Speeches & Group Photo & Invited Speeches & Technical Sessions
Day 3 – December 04, 2026-Academic Visit
Organized By: Kasetsart University (KU), Thailand
Supported By: North China University of Technology, China
Contact Us
Conference Secretary: Ms. Lilith Lee
Email: icbdeconference@163.com
Phone: +86-136-6829-4879
Website: https://www.icbde.org/
