Mohammed Saqr

Mohammed Saqr is an Associate Professor of Computer Science at the School of Computing, University of Eastern Finland, where he leads UEF's Learning Analytics Unit. His research spans learning analytics, artificial intelligence, big data, network science, and interdisciplinary applications in education and medicine. His work has positioned UEF's Learning Analytics Unit as Europe's most productive learning analytics lab according to Scopus and Web of Science (2019-2023).

Dr. Saqr earned his PhD in Learning Analytics from Stockholm University, Sweden, followed by a postdoctoral position at Université Paris Cité, France. He later obtained the title of Docent in Learning Analytics from the University of Oulu, Finland. His academic journey reflects a strong foundation in both European research institutions and interdisciplinary approaches to educational technology.

His research focuses on understanding student engagement, self-regulated learning, and collaborative learning processes through advanced analytical methods. Dr. Saqr champions person-specific and person-centered approaches that recognize individual differences among learners, challenging traditional group-level analysis methods. His work demonstrates that online engagement at any single time-point is not a consistent indicator for high achievement, and that it takes more than a single point of time to reliably forecast academic performance throughout a program. He has pioneered the application of complex dynamic systems theory, idiographic methods, and network analysis to uncover nuanced learning patterns that remain hidden in conventional approaches.

Dr. Saqr's extensive publication record reveals a consistent trajectory toward more sophisticated and individualized analytical techniques in learning analytics. His recent work increasingly emphasizes the limitations of group-level analysis and the necessity of person-specific modeling for truly personalized education. He has made significant contributions to understanding how engagement evolves over time, how self-regulation operates as a dynamic system, and how collaborative learning roles persist across extended periods.

• Best PhD thesis award
• Best paper awards at LAK, ICCE, SITE, and TEEM conferences
• University of Michigan Office of Academic Innovation fellowship
• SOLAR Europe's Emerging Scholar Award (2023) for "Noteworthy research leading to significant knowledge and understanding of learning analytics and the impact of research on learning analytics application, adoption, and professional development in Europe"

Dr. Saqr has successfully secured research funding as Principal Investigator from the Academy of Finland and as Co-Principal Investigator from the Swedish Research Council. He actively supervises graduate students, with Ramy recently defending his thesis in learning analytics. His extensive collaboration network spans over a hundred researchers across multiple countries, reflecting his international impact in the field. Dr. Saqr serves on the editorial boards of Transactions of Learning Technologies, British Journal of Education Technologies, and PLOS ONE, contributing to the scholarly community through peer review and journal leadership.

As leader of UEF's Learning Analytics Unit, Dr. Saqr directs a vibrant research team that has emerged as Europe's most productive learning analytics lab. His unit focuses on developing innovative methodologies for understanding learning processes at individual and group levels, with particular emphasis on longitudinal analysis and person-specific approaches. The unit's work bridges theoretical advances with practical applications in educational settings, contributing to both scholarly knowledge and real-world educational improvements.