Online and blended learning environments have become increasingly popular in recent years, due to the flexibility and convenience they offer to learners. Scalable computing infrastructure is crucial for the success of these environments, enabling large-scale data processing, real-time analytics, and personalized learning experiences. However, implementing scalable computing infrastructure in online and blended learning environments comes with its own set of challenges and requires innovative solutions.

Recommended topics (but not limited to)

This special issue aims to bring together original research papers, case studies, and literature reviews that address the challenges and solutions related to scalable computing in online and blended learning environments. The scope of this special issue includes, but is not limited to, the following topics:

  • Scalable computing infrastructure for online and blended learning environments
  • Scalable computing for personalized learning in online and blended environments
  • Big data analytics for online and blended learning environments
  • Cloud computing and virtualization in online and blended learning environments
  • Artificial intelligence and machine learning for online and blended learning environments
  • Security and privacy issues in scalable computing for online and blended learning environments
  • Scalable computing for mobile learning and ubiquitous learning environments
  • Pedagogical approaches for leveraging scalable computing in online and blended learning environments
  • Challenges and solutions for effective implementation and delivery of scalable computing in online and blended learning environments
  • Case studies and best practices of scalable computing in online and blended learning environments

We welcome contributions from researchers, educators, instructional designers, and technology specialists who are interested in the latest developments and innovations related to scalable computing in online and blended learning environments. All submissions will undergo a rigorous peer-review process to ensure the quality and relevance of the articles published in this special issue.

Important dates

Submission deadline: 30 January, 2024

Authors notification: 31 March, 2024

Revision submission: 15 April, 2024

Final decision: 30 April, 2024

Completion of Special Issue: June, 2024

Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.

During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

Guest Editors

Lead: Mudasir Mohd, email:

Mudasir Mohd has a Ph.D. from the Department of Computer Science, University of Kashmir, India. He has been working on a substantive basis as an Assistant Professor in the Department of Computer Science, South Campus, the University of Kashmir, India, since August 2013. His research focuses on Human-Computer Interaction, Text analytics, Emotion and Opinion Mining of textual data streams, and Text Summarization. His goal is to explore the possibilities of integrating various modalities in the text, such as attributes, to learn from precise embeddings. He worked on various projects like data mining, pos-tagger, recommendation systems, and sentiment analysis. He has 15 research articles to his name, which are published in reputed, high-impact journals and indexed by SCI and Scopus. Besides this, He has attended numerous international and national conferences.

Napat Jitpaisarnwattana, email:

Napat Jitpaisarnwattana is a lecturer of Computer-assisted Language Learning at Silpakorn University, Thailand. He is also a postgraduate researcher at Homerton College, Cambridge University. He received his PhD from King Mongkut’s University of Technology Thonburi and multiple master degrees from Oxford University, Cambridge University and Lancaster University. His research interests include blended learning, educational data mining, learning analytics, machine learning, automated language assessment, massive open online courses (MOOCs) and computer-assisted language learning. He is editor of The Malaysian Journal of ELT Research (MaJER) and editorial board member of Online Learning Journal (OLJ) and CALL-EJ Journal.

Juhong Christie Liu, email:

Dr. Juhong Christie Liu is an Associate Professor and Director of Instructional Design at James Madison University (JMU). Dr. Liu leads programs and initiatives with the Instructional Design department (formed in 2022) in JMU Libraries. Her research interests include design for inclusive digital, online, and blended learning environments, educational design research, and cross-cultural collaborative research. Christie has a Ph.D. degree in Curriculum and Instruction/ Instructional Design and Technology from Virginia Tech. She is the JMU Madison Scholar 2022. Dr. Liu serves on editorial boards of TechTrends and Journal of Educational Technology Development and Exchange (JETDE), Editorial Review Board of Online Learning Journal, and as a guest editor of Educational Technology & Society special issue. Christie has published peer-reviewed journal articles and book chapters, edited IEEE CPS published international conference proceedings, and regularly presents at international, national, and regional conferences.

Mohamad Rahimi Mohamad Rosman, email:

Mohamad Rahimi Mohamad Rosman received his PhD in Information Management from Universiti Teknologi MARA, Shah Alam, Malaysia in 2020. He now is a senior lecturer at Faculty of Information Management, Universiti Teknologi MARA Cawnagan Kelantan, Malaysia. His research interest include information systems, user engagement, content management, digital library, web technologies, etc. He is passionate about his job and his personal contribution to the world of modern web design.