3rd Special Session on the Future of Learning with Smart Technologies: Unlocking Potential through Smart Education

Short description

Following the success of the Workshop at the 9th IEEE International Smart Cities Conference in Bucharest, Romania, 2023, and the Special Sessions at the 2nd International Conference on Sustainability: Developments & Innovations in Riyadh, Saudi Arabia, 2024, the organisers propose the 3rd event in this series as a Special Session.

Advanced technologies and data-driven strategies are transforming urban environments and various sectors of society. By utilising these technological advancements, smart education creates new opportunities and challenges for the educational sector. Integrating smart education within the framework of smart technologies and urban systems equips learners with the abilities they need to thrive in a globally connected society.

This special session focuses on how the next generation of learners can be empowered by technological breakthroughs such as Artificial Intelligence (AI), the Internet of Things (IoT), cloud computing and smart devices, virtual/augmented reality (VR/AR), and data analytics, using advanced Information and Communication Technology (ICT) infrastructure. The increasing adoption of smartphones, wearable technology, and the rapid uptake of AI and IoT has heightened learners’ expectations for enhanced educational experiences.

This session will bring together educators, policymakers, industry experts, and researchers to discuss novel approaches, best practices, and strategies for implementing smart education projects. Participants will collaborate to share knowledge and develop actionable plans to strengthen educational systems and prepare a future-ready generation.

Session Scope and Aim

Smart technologies play a vital role in learning development by fostering innovation, collaboration, and the integration of advanced digital solutions. They create a conducive environment for smart education systems, boosting learners’ performance and readiness for future challenges. Through robust digital frameworks, smart technologies enable the seamless integration of tools such as AI, IoT, VR/AR etc., significantly enhancing educational outcomes.

These technologies form the foundation for smart education, delivering personalised and adaptive learning experiences tailored to individual learner needs. Smart devices and systems gather and analyse data to provide insights into learning trends, student performance, and instructional practices. The integration of smart education systems, supported by advanced technologies, also drives continuous improvement in teaching methodologies, curriculum development, and educational policies. By applying data analytics and evidence-based approaches, educators and policymakers can refine their strategies to address evolving student needs and workforce demands. Despite these advancements, smart education systems face challenges such as stimulating learner engagement, improving communication channels, ensuring reliable technology infrastructure, and accommodating diverse learning needs. Adopting digital technologies can address these issues, enhancing learner satisfaction and providing more effective educational experiences.

This session will provide a platform for experts and researchers to exchange findings and identify challenges and opportunities in smart education practices enabled by smart technologies. Researchers are invited to contribute innovative research papers or insightful review papers. Topics of interest include, but are not limited to, the following areas:

List of topics

• Designing smart classrooms and learning environments for enhanced learner engagement
• Innovative solutions to address educational challenges and provide personalised learning experiences
• IoT applications in smart education
• AR and VR for immersive and interactive learning experiences
• Learners’ emotional states and their mapping to teaching methodologies
• Intelligent tutoring systems (ITS) to support lifelong learning and skill development
• AI-enabled adaptive and personalised learning systems to cater to diverse needs and preferences
• Data analytics and insights to improve teaching and learning outcomes
• Predictive analytics using AI to forecast learner success and guide interventions
• AI-enabled virtual assistants and content recommender systems for personalised, context-aware learning experiences
• Ethical and privacy considerations in collecting and utilising learner data in smart education systems
• Best practices and success stories in integrating smart education technologies

Co-Chairs

Ikram Ur Rehman
e-mail: Ikram.Rehman@uwl.ac.uk
School of Computing and Engineering, University of West London, United Kingdom

Moustafa Nasralla
e-mail: mnasralla@psu.edu.sa
Communications and Networks Engineering Department, Prince Sultan University, Riyadh, Saudi Arabia

Nagham Saeed
e-mail: Nagham.Saeed@uwl.ac.uk
School of Computing and Engineering, University of West London, United Kingdom

Muazzam Ali Khan Khattam
e-mail: muazzam.khattak@qau.edu.pk
Department of Computer Sciences, Quaid-i-Azam University, Islamabad, Pakistan

Julie Wall
e-mail: Julie.Wall@uwl.ac.uk
School of Computing and Engineering, University of West London, United Kingdom

Program Committee

• Sara Paiva, Instituto Politécnico de Viana do Castelo, Portugal
• Bilyaminu Auwal Romo, University of East London, UK
• Ijaz Ul Haq, University De Lleida, Spain
• Bilal Qureshi, University of Lakki Marwat, Pakistan
• Danish Mehmood, SZABIST, Pakistan
• Muhammad Imran Aslam, NED University of Engineering and Technology, Pakistan
• Muhammad Zeeshan Shakir, University of West Scotland, UK
• Muhammad Khurram, NED University of Engineering and Technology, Pakistan
• Naveed-ul-Hassan, Lahore University of Management Sciences, Pakistan
• Sunila Akbar, NED University of Engineering and Technology, Pakistan
• Aamir Anwar, University of West London, UK
• Parisa Saadati, University of West London, UK
• Maged Abdullah Esmail, Prince Sultan University, Saudi Arabia
• Sagar Mahajan, Prince Sultan University, Saudi Arabia
• Umashankar Subramaniam, Prince Sultan University, Saudi Arabia
• Zeeshan Sattar, Ericsson, Canada
• Muhammad Kamran Naeem, Research Fellow, University of Wolverhampton, UK
• Shakeel Ahmad, Associate Professor, Solent University, UK
• Sérgio Lopes, Instituto Politécnico de Viana do Castelo, Portugal