Call for Papers
Special Issue on the Role of Interactive Social Robots in Personalized and Adaptive Learning
Summary:
With the advancement of technology, there has been an increased interest in using social robots for educational purposes. Interactive social robots have the potential to offer personalized and adaptive learning experiences to students, enhancing their engagement and motivation in learning. Innovative robots and interactive social robots have the potential to facilitate personal and adaptive learning by enhancing students' engagement, motivation, and performance. The responsive nature of Interactive Social Robots can allow the user to control the robot through speech and text. Using such technology can provide a learning environment that is individually tailored and personalized for each learner based on their available resources, interests, and learning needs.
Adaptive learning is a paradigm of teaching and learning that promotes the student-centered theory-based practice. Adaptive learning aims to help students develop the knowledge, skills, and dispositions needed to practice in an increasingly complex world. With the increasing use of technology and mobile devices, there is an ongoing need for adaptive learning. Adaptive learning has become essential to support the learner's needs and bring lessons more closely aligned with his or her interests. Social robots are an effective, affordable, and realistic way to provide personalized and adaptive learning. With social robots, learners can experience the interactions they want while they develop important life skills such as problem-solving and collaboration. The development of social robots has been limited because many challenges still need to be solved in understanding users' needs and how to comprehend human emotions. To address this issue, more research is needed to enhance adaptive learning for robots. Social robots are an effective, affordable, and realistic way to provide personalized and adaptive learning. With social robots, learners can experience the interactions they want while they develop important life skills such as problem-solving and collaboration.
This special issue aims to bring together research and development in this area, exploring the current state of the field and its future directions. This special issue aims to bring together researchers and practitioners from different fields to advance our understanding of the role of interactive social robots in personalized and adaptive learning. We look forward to receiving high-quality submissions contributing to this growing field.
List of Interested topics include, but are not limited to, the following:
- Social robot hardware and software design for personalized and adaptive learning.
- Human-robot interaction in personalized and adaptive learning.
- Learning with interactive social robots in different contexts, such as classrooms, homes, and social robotics labs.
- New research on human-robot interaction for personalized and adaptive learning.
- Interactive social robots for educational purposes: design principles, pedagogical frameworks, and evaluation methods.
- Characteristics of interactive social robots that support personalized and adaptive learning.
- Uses of interactive social robots in personalized and adaptive learning settings.
- Social interaction, multimodal communication, and human-robot interaction in educational settings.
- Designing and implementing interactive social robots for personalized and adaptive learning.
- The design, development, and evaluation of interactive social robots for personalized and adaptive learning.
- The use of artificial intelligence and machine learning in social robots to support personalized and adaptive learning.
- The impact of interactive social robots on student engagement, motivation, and learning outcomes.
- Ethical and privacy considerations in using social robots for personalized and adaptive learning.
- Future directions for research in interactive social robots for personalized and adaptive learning.
Dr. Mahmud Iwan Solihin
Associate Professor at Faculty of Engineering,
UCSI University, Malaysia.
Emai: mahmudis@ucsiuniversity.edu.my, mahmud.iwan@proton.me
https://scholar.google.com.my/citations?user=BlBZJPUAAAAJ
Dr. Lin Guoping
Professor of Department of Engineering,
Department of Industrial Engineering and Enterprise Information,
Tunghai University, Taiwan.
Emai: kplin@thu.edu.tw
https://scholar.google.co.uk/citations?user=OyWUYLAAAAAJ
Dr. Slamet Riyadi
Associate Professor, Department of Information Technology,
Universitas Muhammadiyah Yogyakarta, Indonesia.
Emai: riyadi@umy.ac.id
https://scholar.google.com/citations?user=bl1BHx8AAAAJ&hl=en
Deadlines:
Article Submission Deadline - [10.10.2024]
Authors Notification Date - [20.12.2024]
Revised Papers Due Date - [25.2.2025]
Final notification Date - [20.04.2025]