Datafication and Digitization

I found another important thought from Big Data: A Revolution - the concept of datafication and digitization. Datafication is making information about the world into a reusable, reviewable form. In old days, it was book keeping, logs, and journals. Nowadays, it includes logs of user behavior with systems stored in electronic databases. Digitization is taking hard copy forms of information and making them electronic. This would include Google's efforts to scan the world's books and store them in electronic format. This effort becomes datafication when Google OCRs the books so that people can search for words and patterns between words.

We are digitizing learning. We put the syllabus and needed files online so we no longer have to worry about printing costs. We ask learners to turn things in online, to watch videos made available online, or participate in an online discussion. We datafy this when we have information about these objects and interactions--where things are stored, how it was used, how many times it was used, who used it.

The power of Big Data is when we have lots of data to analyze. Being able to do Big Data in education, however, is limited. We have digitized a lot of learning, but have barely scratched the surface of what data is currently available and what data could yet be made. It is common to be able to access page views, and loggin counts, and number of messages sent from the LMS, but more could be done. Length of time learning, mouse tracking, and capturing information about on-task and off-task behavior could be harnessed. Woolf et al. (2009) describe efforts to capture learner's emotions using mouse pressure, seat pressure, facial recognition, and other biosensor systems. The challenge of our day is to continue to find ways to datafy the learning experience.

Learning Management Systems are trying to datafy more and more of the interactions of users and make that data available to others; however, not all of learning is taking place in an LMS. School administrative systems contain useful learner data, such as GPA, course completion statuses, exam scores, and final grades for courses. Tin Can is a service that tries to collect data from LMSs, website visits, and other online interactions and makes all that data available in useful ways. Still, a challenge is that much of learning is not taking place online. We can not get the true value of Big Data analysis on learning until we have lots of data about the full range of the learning experience. Finding ways to capture data about face-to-face interactions is key.

A final challenge, of course, is student privacy rights. Who should have access to student data? How should it be ethically used? How should it be stored. What can students do about access to their data? As more and more data becomes available, and using that data becomes more widespread, these privacy questions will demand more attention.

  

Woolf, B., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., & Picard, R. (2009). Affect-aware tutors: Recognising and responding to student affect. International Journal of Learning Technology, 4(3/4), 129–164.