Most people are familiar with economies of scale, which we discussed in a recent post. The Network Effect sometimes called “Metcalfe’s Law”, is less well-known, but equally relevant if we want to understand how the unique economics of the Internet are influencing higher education.

The concept of economies of scale is concerned with the impact of increases in volume on cost – specifically, cost per unit. Network Effects, on the other hand, concerns the impact of volume on the perceived value of the good or product. When the Network Effect is present and positive, the value of the good or product increases as more people use it. Social media is the clearest example: the value of Instagram, Twitter, Facebook and other peer-to-peer technologies increases as more people participate. As participation rises, the volume of interactions, possibilities for new connections, and the range of available content increases – in turn, so does the value to each participant.

The Network Effect and Online Higher Education

At first glance, the Network Effect seems to have little relevance to higher education. The value of higher education is conventionally thought to correspond to low volume: smaller classes and more exclusive institutions, for instance. But the continued migration to Internet-based learning and services in higher education has the potential to change the dynamics between volume and value. Consider, for example, MOOCs. Critics argue that students won’t learn or persist with an educator-to-student ratio of 50,000 to one. But advocates point out that by using peer-to-peer learning in this context, we may be able to actually complement the traditional educator-student model. If properly designed, an increase in the number of students participating in the MOOC will actually increase its value to each student.

Ironically, the application of social media to higher education often fails to leverage the Network Effect, highlighting the importance of context on the value of technologies.  Social media thrives when there are thousands, if not millions, of users within a single, overarching community. The high volume of users provides online communities with enough activity and content to ensure that each user finds what and who they want with sufficient frequency to make participation worthwhile. Twitter and Linked In now have over 300 million active users. Higher education instruction, by design, typically restricts participation to a single class (e.g. 40–100 students per course). As mentioned, exclusivity and small class sizes are equated with quality.

When More is Better

Not surprisingly, the concept of Network Effects is most often associated with products and services that involve networks in which people or objects are connected in some fashion, such as telephone systems and, as mentioned, social media. But many writers expand the concept to include other types of product or services in which the value for each user increases as the number of users climbs – regardless of whether the people or objects are connected. As the number of people and organisations that use Microsoft Excel increases, for example, the application becomes more valuable for job-seekers.

Learning analytics is an example of this expanded use of the Network Effect. Learning analytics concerns the granular, real-time measurement and estimation of student learning. When guided by a deep understanding of learning theory, this use of technology generates new insights into what leads to better learning outcomes. The data our clients capture concern a single student. And this is the core of its value:  it provides the necessary insights needed for accurate customization and evidence-backed continuous improvement. But new kinds of insights can also be generated by aggregating data across a larger number of learners. By reviewing student performance data across a number of institutions we can identify patterns based, for example, on socio-economic status or high school GPA. This kind of information is an important aid to institutional strategy (e.g. recruiting tactics, financial support, student services), and better government policy and funding.


Keith Hampson, PhD is the founder of digital / edu / strategy, a research and consulting service that helps colleges, universities and education businesses develop better strategies for maximising value. 


  1. Thank you Keith for this insightful post. It highlights key issues around online learning that institutions like mine which are exploring the costs and benefits of migrating to online provision should consider. Where production in large volume may not often be associated with quality, the potential that the “network effect” of social media engagement could enable peer-to-peer learning might lead to deep learning en masse adding value to individual learner and the institution, is exciting. And I think here is where great analytics is needed, as you so rightly suggest, to provide the evidence to convince the skeptics. I’ve got one remaining question though. How much financial investment in technologies is needed upfront for an institution to benefit from the potential economies of scale of migrating to mass online provision?


  2. Great question, Ludmilla. Taking advantage of scale and economies of scale needed actually cost more. If we really want to take advantage of scale, then we will seek out technologies and services delivered by other organizations – university consortia or vendors, typically. My hope is that universities start to seek out the best value for students, regardless of the source.


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