MANUSCRIPT: What data and analytics can and do say about effective learning
The collection and analysis of data about learning is a trend that is growing exponentially in all levels of education. Data science is poised to have a substantial influence on the understanding of
learning in online and blended learning environments. The mass of data already being collected about student learning provides a source of greater insights into student learning that have not
previously been available, and therefore is liable to have a substantial impact on and be impacted by the science of learning in the years ahead.1
However, despite the potential evident in the application of data science to education, several recent articles, e.g.,2, 3 have pointed out that student behavioural data collected en masse do
not holistically capture student learning. Rogers4 contends that this positivist view of analytics in education is symptomatic of issues in the social sciences more broadly. While there is
undeniable merit in bringing a critical perspective to the use of data and analytics, we suggest that the power and intent of data science for understanding learning is now becoming apparent.
The intersection of the science of learning with data and analytics enables more sophisticated ways of making meaning to support student learning.
Written by Brian S McGowan, PhD
Dr. McGowan has served in leadership positions in numerous medical educational organizations and commercial supporters and is a Fellow of the Alliance (FACEhp). He founded the Outcomes Standardization Project, launched and hosted the Alliance Podcast, and most recently launched and hosts the JCEHP Emerging Best Practices in CPD podcast. In 2012 he Co-Founded ArcheMedX, Inc, a healthcare informatics and e-learning company to apply his research in practice.
