In 2024, as the world continues its recovery from the impact of the COVID-19 pandemic, we find ourselves immersed in the post-COVID-19 era, shaped by the lessons learned and advancements made over the past few years. The pandemic has profoundly transformed various aspects of our lives, including education and the way we acquire knowledge. The adoption of online, blended, and hybrid learning models during the pandemic has accelerated the development of e-learning content and infrastructure, making education more accessible than ever before.
As we embrace the opportunities of the post-COVID-19 era, we recognize the increasing significance of large language models (LLMs) in the education domain. These advanced models, exemplified by the groundbreaking GPT-based models such as ChatGPT, have revolutionized natural language processing and have the potential to reshape the way we teach and learn. By leveraging the capabilities of LLMs, we can unlock new possibilities in personalized and adaptive e-learning environments that cater to the diverse needs and preferences of learners. The integration of LLMs in education holds tremendous promise. These models can analyze vast amounts of educational content, generating tailored materials that adapt to individual learners' requirements, knowledge gaps, and learning styles. They act as virtual tutors, providing instant and accurate responses to learners' questions, explanations, and guidance. The application of LLMs in education represents a significant breakthrough that enhances the learning experience, fosters engagement, and promotes knowledge retention.
At the Intelligent E-learning at Post-COVID19 Era (IEPCE) conference in 2024, we aim to bring together researchers, educators, and industry professionals to explore the transformative potential of LLMs in the education domain, together with the integration of information and communication technologies, artificial intelligence (AI), augmented and virtual reality (AR/VR), and gamification, which will take on a higher weight in school learning. This conference serves as a platform to discuss the latest advancements, innovative practices, and case studies that highlight the significance of LLMs in intelligent e-learning. We encourage submissions on a range of topics, including but not limited to
- LLM application in education.
- AI application in education.
- AR/VR and gamification for intelligent e-learning.
- Online education in the post COVID-19 era.
- MOOC’s innovative development in the post-COVID-19 era.
- Deep neural networks for smart e-learning.
- Hybrid or blended e-learning.
- Teaching and learning evaluation in the post COVID-19 era.
- Integration of offline learning and e-learning in the post COVID-19 era.
- Technology proficiency development.
- Scalable and easily adaptable e-learning models.
- Collaborative and inclusive e-learning.
- Student modeling for intelligent e-learning.
- Challenges and opportunities for e-learning in the post COVID-19 era.
- E-learning adaptation and optimization to unexpected crises.
Important Dates
- Special Session Papers Submission: 01 May 2024
- Acceptance Notification: 01 June 2024
- Camera-Ready Submission: 15 June 2024
- Author Registration: 18 June 2024
- Conference Date: 16-18 August 2024
Paper submission instruction
Paper submission system is available at: https://easychair.org/conferences/?conf=besc2024.
All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to BESC 2024, originality, significance and clarity.
Please note:
- All submissions should use IEEE two-column style. Templates are available from here.
- All papers must be submitted electronically through the paper submission system in PDF format only. BESC 2024 accepts special session papers (6 pages). The page count includes the references.
- Paper review will be double-blind, and submissions not properly anonymized will be desk-rejected without review.
- Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings.
- Papers must be clearly submitted in English and will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation.
- Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work.
- Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements and indexed by EI. Top quality papers after presented in the conference will be selected for extension and publication in several special issues of international journals, e.g., World Wide Web Journal (Springer), Web Intelligence (IOS Press), Social Network Analysis and Mining (Springer), Human-Centric Intelligent Systems (Springer), Natural Language Processing (Elsevier), etc.
- The use of artificial intelligence (AI)–generated text in an article shall be disclosed in the acknowledgements section of any paper submitted to an IEEE Conference or Periodical. The sections of the paper that use AI-generated text shall have a citation to the AI system used to generate the text.
Organizing Committee
General ChairZongxi Li, Lingnan University, Hong Kong
Technical Programme Co-Chairs
Xieling Chen, Guangzhou University, China
Fan Su, Shanghai Normal University, China
Wei Chen, Chinese Academy of Agricultural Sciences, China
Steering Committee Co-Chairs
Gary Cheng, The Education University of Hong Kong, Hong Kong
Tak-Lam Wong, Douglas College, Canada
Haoran Xie, Lingnan University, Hong Kong
Di Zou, Lingnan University, Hong Kong
Honorary Co-Chairs
Gwo-Jen Hwang, National Taiwan University of Science and Technology, Taiwan
Fu Lee Wang, Hong Kong Metropolitan University, Hong Kong
Program Committee Members
Xinhong Chen, City University of Hong Kong, Hong Kong
Xianming Li, Ant Group, China
Yang Li, Hong Kong Metropolitan University, Hong Kong
Yuzhang Liu, Xiaohongshu, China
Han Zhang, Chinese University of Hong Kong, Hong Kong
Ruofei Zhang, The Education University of Hong Kong, Hong Kong