Self-directedness, self-regulation, and self-control – inter alia– have all been around for decades. All such constructs embrace the quintessential element of “self” or “person” as a central point of departure from existing methods or theories. Nonetheless, research is conducted by using data from a “group of others'' to derive generalizable laws or norms. Data collected from others barely represents any single person, and therefore, the norms and laws always fail to bring tangible progress in our understanding of human behavior. A paradigm shift is needed to bring the person into research and practice. That is, a shift towards characterizing the individual using person-specific or idiographic methods. This presentation discusses the shortcomings of current methods of doing research, shows why they fail, and introduces idiographic methods.
Mohammed Saqr holds a PhD in learning analytics from Stockholm University. Currently, he works as a Senior Researcher at the University of Eastern Finland (UEF) and holds the title of Docent in Learning Analytics from the University of Oulu (Finland). His work experience includes working at Université de Paris Cité (France), Stockholm University and KTH Royal Institute of Technology (Sweden). Now, he's leading the lab of learning analytics at UEF, Europe’s most productive learning analytics lab in 2021 and 2022. He was awarded the most competitive funding in both Sweden (Swedish Research Council) and Finland (the Academy of Finland). Saqr has published extensively on learning analytics as well as computing education, the science of science and open science. Since September 2022, he has been working to develop artificial intelligence methods that can personalize education (idiographic analytics). In addition, he serves as an associate editor for IEEE Transactions on Learning Technologies, PLoS One, Frontiers in Computer Science and Frontiers in Big Data.
For an updated list of Mohammed Saqr's publications, please see ResearchGate.
