Learning Analytics – Where is it headed?


Big data and analytics have caught on like a wild fire in the area of business. Enterprises have either embraced or are in the process of embracing big data and analytics to remain competitive, tide over unforeseen bottlenecks and adjust to a rapidly changing business landscape. As enterprises get ready to face hectic competition,one of the major requirements is - talented resource pool with an analytical bent of mind hired from academic institutions.

And that brings about the question –

What new initiatives have academic institutions taken to ensure greater student learning?

As enterprises look for students with great skills and leadership abilities, academic institutions are looking to emerging technologies to help prepare and train students to succeed in their future endeavors. Big data and analytics in the form of Learning Analytics can help faculty mould students for their professional endeavors and other initiatives. In fact, the concept of Learning Analytics is just about taking shape and its value is found in two major areas –
a)      It can play a key role in guiding reform activities in higher education
b)      It can assist educators in improving teaching and learning

Implementation of Learning Analytics:

Learning Analytics as a subject and a technology is finding interest and attention but when it comes to implementation, itis finding few takers. The issue is not about lack of motivation to implement but rather about the practicality of implementing the concept.
Firstly, most academic institutions do not have the IT infrastructure (and fairly so) to integrate or implement. Next, since it’s fairly new concept the stakeholders (especially, faculty) are naturally reluctant and resistant to a new change. Finally, the key decision makers (Deans and Founders) are not entirely convinced that the concept can be implemented ‘’immediately’’ to witness the ‘’desired effect’’. For them, it’s all about outcomes and results; nothing but fair expectations.
And then of course, are the more technical factors hindering the implementation such as –quality issues, systems integration difficulties, etc.
But nevertheless, Learning Analytics has a future. It hasthe scope to be implemented to provide the desired result of helping faculty train students to do better through innovative learning techniques.

The future of Learning Analytics

Authors, George Siemens and Phil Long in their article – Penetrating the Fog: Analytics in Learning and Education, mention
‘’Learning analytics is essential for penetrating the fog that has settled over much of higher education. Educators, students, and administrators need a foundation on which to enact change. For educators, the availability of real-time insight into the performance of learners--including students who are at-risk--can be a significant help in the planning of teaching activities.’’

They go on to add that, students can be motivated and encouraged through analysis of their performance in relation to their peers and of course, through information on their progress. But they also admit that administrators and decision makers are confronted with uncertainty due to budget constraints andheavy competition amongst institutions.
But there is hope for learning analytics in the future with a good number of institutions seriously contemplating on having learning analytics as part of their academic courses, if not immediately, but definitely in the time to come.

So, how does Learning Analytics actually help?

Learning Analytics helps to collect, process, and utilize data to bring out meaningful and actionable insights -
Strategic use of data: Data exists digitally in the academic system but has not been used or harnessed in the manner expected. Data can be utilized in a much more meaningful manner to observe and learn a student’s behavior towards her education, her interests in certain subjects and her inclinations towards a type of learning (Classroom or Practical). Such strategic use of data can help profile learners and provide them with customized approaches to learning.
Human Interventions: Teaching is all about interactions and in that process building inter-relationships, for, these relationships up the level of teaching and boost the learning interests of students. Data through learning analytics is used to understand teaching patterns andmodes.This can help to increase or decrease human interventions, as and when necessary, in a bid to help students do better.
Actionable Insights: Perhaps, the best use of data is to have it bring about actionable insights that result in marked improvements in both – faculty teaching and student learning. Actionable insights on teachingand learning can bring about a remarkable difference to classroom atmosphere and galvanize both students and teachers towards a more progressive learning.

Treading the data path, carefully

Having said that, one must take care of how data is both gathered and used with respect to helping the two most important stakeholders—Students and Faculty. Data should not be used in an unfair manner, especially, when comparing and ranking of students and faculty, this will only build differences and disrupt an otherwise balanced learning atmosphere.
Data should also never be used for purposes that can lead to leaking of information about both students’ and teachers’ abilities and capabilities to external forces.It cannot also be used internally by decision makers to give out prejudiced and unfair judgements.

Learning analytics will definitely find prominence in the field of future education.But first, it has be perceived as a concept that aidslearning and then, as a tool that helps faculty do better (not threaten their existence) and finally, as a solution that can be easily implemented. 
Learning Analytics – Where is it headed? Learning Analytics – Where is it headed? Reviewed by Jitender Sharma on December 18, 2017 Rating: 5

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