The Blind Side of Academia

While there is an burgeoning plethora of academic research about online learning and the history of educational technology as it relates to the internet, there is also a much larger online community of learners who access the internet for informal education. Everything from self-diagnosing a health issue to learning to play a musical instrument, from gardening tips to automotive repair, from recipe videos to photography tips, the internet is a playground for do-it-yourself learners who are no less valuable to the learning economy than those who register and pay individuals or institutions to gain some credential of education.

In a 0.50 second search by Google with the input parameter of “How to”, the engine generated over 25 billion results. This speaks to the nature of the internet in the sphere of practical-knowledge, about its propensity to give anyone with access the ability to share and exchange their own talents and knowledge with the wider world in a completely free and open environment. The internet in this regard costs its users only that amount that is determined by access providers and has established and rich and varied platform of learning opportunities that are by all accounts free of charge, generated by users with all kinds of previous formal and informal knowledge and skills. The notion that there is a vast and ever-growing body of online learning that is not of a formal nature is certainly within the awareness of academics, however, research gives little credence to this much larger education resource.

 

Broadening the Metrics

When conducting a cursory examination of the research literature on the history and evolution of online learning, it becomes clear that there is a tendency to use traditional metrics in the collection of data for academic researchers to make conclusions and statements that meet the standards of validity required to ensure credibility in academic literature. However, since the advent of the internet in 1983 and, in its more popular form,  since August 1991, the access to data and the ability to aggregate data has grown exponentially. Massive data sets are now generated by using sophisticated software that has begun to illuminate large demographic patterns in society, so much so that this kind of data mining research has become a credentialed academic pursuit in several learning institutions (e.g. Stanford, 20 Best Data Science Certificate Programs).

A growing body of research examines the more detailed aspects of online learning with specific attention to the behaviours of students registered in online courses. For example, Theile examines how online learners become more independent and self-disciplined by trusting their own judgement and going deeper into their content than when they enrolled in traditional lecture-driven courses (2003), Hung and Crooks used clustering analysis, association rule analysis, and decision tree analysis to mine data from a previous study published earlier in the same year (2009) and concluded there is value in using data mining techniques to support teaching and learning. The vast majority of online learning academic literature focuses on specific issues within the scope of the learner, the structure of delivery, and the teaching, however, little attention has been paid to the much broader question of online and open learning in its informal forms from online sources that are not accredited as learning institutions or offered by credentialed instructors. The question of value to the public comes to light when the sheer number of informal online learning opportunities is set against the number the formal learning opportunities, most of the latter of which are offered at a financial cost to the learner. Two questions come to light. First, “Is there a value bias built into education research that negates a much broader and richer pattern of learning?” Second, “If there is bias, can it be partly attributed to protecting traditional employment and economic frameworks upon which higher education and academic publishing rely?”

 

True Open Learning Already Dominates

Online distributed and open learning has been narrowly defined by academia. The reason for this is unclear but could be explained by the unspoken need to protect the economic interests of the institutions that sponsor their research and publishing means upon which their employment relies. There is an implicit quid pro quo relationship between publishers of academic literature and the institutions that generate such literature, perhaps to the detriment of advancing the rate in which our collective knowledge can grow.  The academic literature on online distributed and open learning relies on a rigorous definition rooted in ethical study practices. This definition shapes public perception of what online learning is, especially for those within the walls of academia, but it can also restrict academia from examining the wider online landscape of learning that is generated by users of all races, beliefs, interests and disciplines from all levels of novice to expert. Of course, we can turn to the 10,000 hour rule as an informal way to recognize what kind of expert can be relied upon to offer legitimate learning opportunities online, but in the reality of our deeper selves, there is the potential to learn from anything and anyone regardless of experience, age, or expertise. The way that a parent can learn from their own child is proof enough.

Learning itself is imagined by academia in narrow terms that can be easily labelled, measured, categorized, and analyzed to meet the conditions of scientific research, the standards required by peer-review and ethics boards, and to allow for other researchers to replicate, affirm or contradict hypotheses or findings made. As with any discipline, there are standards of practice that help to define it, however, when examining research in education, the methodologies by which research is conducted and the variety of venues for publications are expanding well beyond the traditional forms that learning institutions have used. Even publishers are having to find ways to maintain a profitable market share in academia. This expanding effect may be the result of an unconscious reverse-pressure wherein emerging technologies and the open and free collective knowledge that is accessible online influences how academia must adapt to a widening array of presenting well-studied knowledge.  Peter and Deimann infer a need for broader perspectives about academia’s understanding of open education, “There is a clear need to further theorise current open education” (2013).  This begs us to consider looking more broadly at learning in general and how the informal process has perhaps been informing the very institutions that have promulgated its more organised form and function in society.

Learning is inherently personal and dependent upon many psychological and social-economic factors. There is an inherent understanding that access to the internet is the first consideration when evaluating the equality of learning online for all people. Public libraries are perhaps the only venue that levels the playing field for offering online learning to everyone in civilized society equally. Additionally, the evolutionary trend of technology in becoming cheaper, smaller, and more ubiquitous has skewed the view that equal access to online learning is already a reality.  However, most technology rests only in the hands of those who can afford it. The question we are left with then is, “How can academic institutions validate and give credence to the silent majority of learners who are using the internet to improve themselves and the lives of others?”

 

References

Data Science Degree Programs Guide (2018). 20 best data science certificate programs 2018 [website]. Retrieved from https://www.datasciencedegreeprograms.net/rankings/certificate/

Hung, J.-L., & Crooks, S. M. (2009). Examining online learning patterns with data mining techniques in peer-moderated and teacher-moderated courses. Journal of Educational Computing Research, 40(2), 183–210. https://doi.org/10.2190/EC.40.2.c

Peter, S. and Deimann, M. (2013). On the role of openness in education: a historical reconstruction. Open Praxis,  5(1), 7-14. DOI: http://dx.doi.org/10.5944/openpraxis.5.1.23

Stanford University (2019). Mining massive data set graduate certificate [website]. Retrieved from https://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=10555807

Thiele, J. (2003). Learning patterns of online students. The Journal of nursing education. 42. 364-6.