A dedicated forum for researchers, educators, and technologists advancing the frontiers of learning science and technology-enhanced education.
With the advent of the Internet and technology, the traditional teaching and learning have largely transformed into digital education. Teachers and students are significantly reliant upon the use of digital media in face-to-face classrooms and remote online learning. The adoption of digital media in education profoundly modif ies the landscape of education, particularly with regard to online learning, e-learning, blended learning and face-to-face digital-assisted learning, offering new possibilities but also challenges that need to be explored and assessed.
The use of Artificial Intelligence (AI) in modern education is rapidly expanding and transforming how teaching and learning are designed, delivered, and evaluated. This track explores the opportunities AI presents for advancing educational pedagogy, enhancing learning technologies, and enabling smart education systems.
We also invite contributions that examine innovative applications of AI to support personalized learning, adaptive assessment, intelligent tutoring systems, learning analytics, curriculum design, and data-driven decision-making in educational contexts. The track also welcomes research on the pedagogical foundations of AI-enhanced learning, ethical considerations, and the integration of AI within smart and digitally enabled educational environments.
Bookmark the following key dates:
We welcome original contributions covering, but not limited to, the following themes.
Our track chairs bring decades of combined expertise in educational technology research and practice.
All submissions must be original, unpublished, and not under review elsewhere.
We only accept full research papers (8-10 pages). All page counts exclude references.
Submissions must follow the Springer single-column conference format. Templates are available for LaTeX and Microsoft Word on the conference website (https://www.icita.world/archive/2023/). Papers must be submitted as PDF only.
All submissions undergo double-blind peer review by at least three members of the Programme Committee. Reviews are assessed on originality, significance, technical quality, and clarity of presentation.
Submissions must be fully anonymised. Remove author names, affiliations, and acknowledgements. Self-citations should be written in the third person (e.g., "Smith et al. [5] showed…").
Accepted papers will be published in the ICITA 2023 proceedings, Lecture Notes in Network Systems Series, and indexed in major databases.