ABSTRACT
This reflection considers issues for researchers who study open, flexible, and distance learning (OFDL) systems. In particular, human learning is regarded as an emergent phenomenon occurring in educational complex systems, which may be non-digital or digital in nature. It is suggested the term learning in OFDL, such as learning analytics and machine learning, refers to computational techniques that help identify patterns in large datasets generated in OFDL systems. It is also proposed that OFDL systems are examples of complex systems, and an overview is provided of a set of relevant complexity conceptual principles. Issues are considered about types of learning data in OFDL systems and their lack of suitability for assessing higher-level explanatory and procedural understandings. Finally, an example is provided to illustrate how complexity ideas may be used with LA techniques to study an OFDL research topic. Implications of complexity theorizing for OFDL research are also discussed.
Acknowledgments
The research discussed in this reflection was funded in part by a grant to the author from the Australian Research Council (ARC) Discovery program DP150102144.
Additional information
Notes on contributors
Michael J. Jacobson
Michael J. Jacobson is a Professor and Chair of Education at the University of Sydney. His research explores learning with intelligent virtual worlds and agent-based modeling and visualization tools, as well as theoretical and methodological issues in education related to new scientific perspectives emerging from the study of complex systems.