Calls for papers

 

International Journal of Mobile Learning and Organisation

 

Special Issue on: "Artificial Intelligence-supported Adaptive and Self-regulated Learning in the Mobile Era"

Guest Editors:
Dr. Chiu-Lin Lai, National Taipei University of Education, Taiwan
Dr. Yun-Fang Tu, University of Wenzhou, China
Dr. Niwat Srisawasdi, Khon Kaen University; Digital Education and Learning Engineering Association, Thailand
Dr. Shao-Chen Chang, Yuan Ze University, Taiwan

Scholars have recognised that adaptive learning and self-regulated learning strategies are two important and potential issues in future education. Adaptive learning customises learners' learning experience by diagnosing learners' learning process and dynamically providing learners' feedback; it tailors the learning process for every student and focuses on improving students' learning. On the other hand, self-regulated learning pays attention to students' awareness of cognitive, emotional, and behavioural engagement in learning. It emphasises the value of students evaluating, planning, and monitoring their own learning approach in order to reach higher-level learning results. Researchers believe that by empowering the learning tools and learning strategies, teachers can bring students' learning to a higher one.

The application of artificial intelligence (AI, including generative AI) is rapidly increasing; it can not only provide personalised content for users but also create text, images, or drawings based on user requests or recommendations. Because of the ease of use of these applications, educators are gradually accepting AI as part of their teaching tools, especially now that mobile devices have been well-implemented into the classroom. This emergence of technology allows students to query, collect, compile, and even produce conclusions on the same platform, accelerating the efficiency of students' access and integrating knowledge in the classroom. The combination of cutting-edge generative AI enables to transformation of the learning process by gathering and analysing students' learning information, personalising their learning experience, and facilitating effective collaboration.

This special issue discusses the effectiveness of AI-supported adaptive and self-regulated learning in the mobile era. We aim to provide various teaching evidence findings and provide educators with more specific guidelines for empowering AI-supported mobile learning contexts. We also welcome authors from all disciplinary backgrounds to share their success cases and experiences. This special issue will enhance our understanding of applying AI-supported mobile learning by sharing adaptive and self-regulated learning strategies in the learning context. Together, we will move towards teaching in the AI era.

Subject Coverage
Suitable topics include, but are not limited, to the following:

• Adaptive/ self-regulated learning theories and models of AI-supported mobile learning
• Adaptive/ self-regulated learning strategies integrated in AI-supported mobile learning
• Applications and effectiveness of integrated AI in mobile-based adaptive/self-regulated learning in school settings
• Applications and effectiveness of the combination of AI technology and adaptive/self-regulated learning in professional training
• Innovative research focuses on using AI in mobile learning settings
• Mobile-based AI applications for interdisciplinary education
• Effects of roles of AI on students' mobile learning performances
• Fusion of various AI tools for mobile-based adaptive/self-regulated learning

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our Submitting articles page.

Important Dates

Manuscripts due by: 31 December, 2024

Notification to authors: 28 February, 2025

Final versions due by: 31 August, 2025