Past

The Dawn of Big Data

The widespread adoption of digital technology has created an explosion of data. In fact, every time you use digital technology, you’re leaving a digital footprint of your activity. Over the past couple decades it has become possible to collect, aggregate, analyze, categorize, and learn from all of this data. This was the dawn of big data, and it allowed institutions and organizations to learn from the behaviors of people using digital technology.

Before the rise of big data, educators had to rely on periodic tests and assessments to judge the progress of their learners. Often, struggling learners were identified too late, and the work to catch up would often require enormous effort. But as educational data mining spread to every strata of education and training, analysts and educators began to recognize the opportunities analytics provided for improve learning experiences. This use of big data to improve online learning is called learning analytics.

The brief video below outlines the three phases in the evolution of Big Data in regards to learning analytics.

Evolution of learning Analytics

The above video suggests the evolutionarily timeline for Learning Analytics can be split into three phases whose periods are closely related to the research and developments milestones reached by both academia and industry. The diagram below highlights those advances in both innovation and literature and describes the evolution as the genealogy of Learning Analytics.

(Peña-Ayala, 2018, p. 7)

Progress in Learning Analytics

The New Media Consortium (NMC) Horizon Report: 2013 K-12 Edition, a publication widely cited by the EdTech community, highlighted the emerging trend toward adoption of learning analytics. The authors of that report predicted that learning analytics would surpass the 20% penetration point by 2020, a milestone that would suggest mainstream practice. Do you think this prediction has come true?

In retrospect it appears that preliminary uses of learning analytics were focused on helping "at-risk learners" in order to improve student success and retention in middle school and high school. For British Columbia, in the previous decade there was a strong focus on six-year completion and graduation rates as indicators of school district success. Was this an application of Learning Analytics, or Academic Analytics?

In 2015, Kenneth Cukier, data editor for the Economist and Viktor Mayer-Schönberger, of Oxford University, published an eBook entitled "Learning with Big Data: The Future of Education" where they suggest education as a whole has been oblivious to the advances in analytics. Please take a few minutes to watch The Economist interview below with Kenneth Cukier and share your thoughts below on the causes for the delayed adoption of learning analytics described by Kenneth.

Discussion - Learning with Big Data (Responses)

"Let’s not forget:
Learning Analytics are about Learning "

In 2015, Dragan Gašević, Shane Dawson, George Siemens, published a paper that examined a growing set of "issues that if left unaddressed, could impede the future maturation of learning analytics." One key issue they observed was that with almost every predictive model a "dashboard" is used to provide feedback and to aid in sensemaking for the student by visualizing the learning analytics results. They also found that "the design of dashboards can lead to the implementation of weak and perhaps detrimental instructional practices as a result of promoting ineffective feedback types and methods."

This takes us to our first activity. We would like to hear your thoughts on dashboards and interactive graphics. Please click the "Activity 1" button below to continue.