Important Dates
Early Bird Registration :9th December 2026
Paper Submission Deadline :14th December 2026
Last Date of Registration : 24th December 2026
Date of Conference : 8th - 9th January 2027
Conference Session Tracks
Aligned with
UN Sustainable Development Goals
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals.
SDG 4 — Quality Education
SDG 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
Track 01
Innovations in Computer Science Curriculum Design
This track focuses on the latest methodologies and frameworks for developing effective computer science curricula. Participants will explore innovative approaches to curriculum design that enhance student engagement and learning outcomes.
Track 02
Pedagogical Strategies in Software Engineering Education
This session will delve into pedagogical techniques specifically tailored for teaching software engineering concepts. Emphasis will be placed on project-based learning and collaborative approaches that foster practical skills.
Track 03
E-Learning Technologies in Computer Science Education
This track examines the integration of e-learning technologies into computer science education. Discussions will include the effectiveness of various digital platforms and tools in enhancing the learning experience.
Track 04
Learning Analytics for Improved Educational Outcomes
Participants will explore the role of learning analytics in assessing and improving educational practices in computer science. This track will highlight data-driven approaches to understanding student performance and engagement.
Track 05
Artificial Intelligence in Educational Contexts
This session will investigate the application of artificial intelligence in enhancing educational methodologies within computer science. Topics will include adaptive learning systems and AI-driven assessment tools.
Track 06
Deep Learning and Its Educational Implications
This track focuses on the pedagogical implications of deep learning technologies in computer science education. Participants will discuss how these advanced techniques can be effectively integrated into curricula.
Track 07
Feature Extraction and Anomaly Detection in Learning Systems
This session will address the significance of feature extraction and anomaly detection in the context of educational technologies. Emphasis will be placed on how these techniques can enhance personalized learning experiences.
Track 08
Assessment Methods in Computer Science Education
This track will explore innovative assessment methods that align with modern computer science curricula. Participants will discuss formative and summative assessment strategies that effectively measure student learning.
Track 09
Skill Development through Project-Based Learning
This session will highlight the importance of project-based learning in developing essential skills for computer science students. Discussions will focus on best practices for implementing projects that foster critical thinking and problem-solving.
Track 10
Computational Thinking in Engineering Education
This track will explore the integration of computational thinking into engineering education, particularly within computer science. Participants will discuss strategies for cultivating this essential skill among students.
Track 11
Digital Learning Platforms and Their Impact on Education
This session will investigate the effectiveness of various digital learning platforms in delivering computer science education. Participants will analyze case studies that demonstrate the impact of these platforms on student learning outcomes.