Learning Analytics – Overcoming initial barriers

We could be looking at changing higher education over next 10-15 years as data becomes more & more available. More and more educational institutions are striving to leverage learning analytics to make better decisions, provide personalized learning to improve learning outcome of students and optimize resources. What is Learning Analytics? Learning analytics is the collection, analysis and reporting of data about students and their contexts for the purpose of understanding and optimizing learning and the environments in which it occurs.

It is found during a recent survey done by a well known agency that many participants from Universities do see the benefits of analytics but have serious concerns about privacy protection as well as quality of data. Concerns are around privacy, data ownership issue, who owns the data “data ownership” and unwillingness to share the data. Sometime the ethical issues seem to be enormous, ranging from who really owns the data, to what are the institutions’ stewardship responsibilities toward it, to moral considerations about what kinds of research questions are appropriate to study.

If we look at the Learning Analytics data, from where it is collected? This data is student data derived from their interactions with the institutions systems such as Learning Management System. Since it is student data, it is logical to say that data in a meaningful way should be accessible by each student so that they can understand and help themselves. In other words, learning analytics outcome should be made available to students so that they can benefit by it. If we don’t do it, why are we collecting data at the first place?

I don’t have any doubt that educational institutions need to have a framework for data standardization, data consistency, data federation along with balance security across the organization in order to realize maximum benefits from the analytics. “Garbage in – Garbage out” is known to everyone.  In addition, the data needs to “de-siloed” in order to reap the significant benefits of higher education analytics. As far as privacy protection is concerned, data can be masked to protect individual’s identities like the way it is done in healthcare or insurance industry. The payoff from learning analytics could be huge.

One of the key components for success of Learning Analytics efforts is to identify the right individuals such as various data owners on your campus to include in the whole process and work with these individuals to cultivate a balance approach towards it. Identify quick wins from a small analytics project first, rather than going for a big bang approach. Show the results, value and ROI to others, get their buy in and do the subsequent phased of the project.

Data can be collected in such a way that all the different data systems stored around a student’s education profile from kindergarten to higher education be available and easily accessible to the institution. Analytics on this data will help educators to have a better understanding of the students and their learning profile. The day is not too far, when all this data will be available to most of the educational institutions and probably to employers as well. I believe the analytics on this data must be shared with students as well so that they become aware of their own strengths and weaknesses. This will enable full personalization of the learning experience.

Educators will have responsibility to ensure that the power and potential of any new information produced as a result of learning analytics is used to benefit those students first, who are the most vulnerable to disengagement and disenfranchisement.