Learning Analytics is a terminology that has been gaining steady momentum in the pedagogic universe. Like most other concepts in the social space, it is void of a universally acceptable definition. Therefore, before I proceed to defining learning analytics in my own words, I will like to note the meaning of each individual term.
I start with analytics. Analytics refer to the “science of analysis”. According to the Business Dictionary (2012), “Analytics often involves studying past historical data to research potential trends, to analyse the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario”. The overall goal of all this is improving the subject of the analysis which in our own case is learning. More recently, the term has also been linked to the application of computer technology in the analysis of data.
Learning on the other hand “is an enduring change in the mechanisms of behaviour involving specific stimuli and/or responses that result from prior experience with those stimuli and responses” (Domjan & Burkhard, 1993 cited in Udoisang, 2011). Learning has also been defined as “a process that brings together cognitive, emotional, and environmental influences and experiences for acquiring, enhancing, or making changes in one's knowledge, skills, values, and world views” (Generic Definition cited in Udoisang 2011).
A universally acceptable definition for learning is not also available however, in my recent MSc project in University of Manchester (which won the Outstanding Dissertation Award in School of Computer Science, 2012), I came to the conclusion that “Learning is a product of the interplay between the cognitive, the emotional and the environmental” (Udoisang, 2011). However, I also noted that “the environment can affect both emotion and cognition, positively or otherwise” (Udoisang, 2011). The environment therefore becomes a very important factor in Learning.
Having looked at both words, I can now submit in my own words that “Learning Analytics is the process of gathering and analysing data about learners in a given context for the purpose of improving learning”. In order to be able to gather such data, there has to be a fundamental understanding of learning and learners. A research into learning theories can provide the required understanding. However, I also came to discover in my MSc project work that the learning theories and learning styles are greatly influenced by the learning environment. In other words like I said earlier, the environment is one single factor in learning that can influence the emotion as well as the cognition. It therefore shapes to a greater degree the reason, direction and outcome of learning.
It is my opinion and belief (for the time being) that for learning analytics to be effective, we will have to rely on a 3-dimensional view of data aggregation and analysis (The emotional view, cognitive view and environmental view). To further develop my interest in learning analytics, I have signed up for the “open online course on learning analytics, 2012” (#LAK12). I believe my interaction via this course with renowned experts in the field such as George Siemens, Diana Oblinger, etc, will enable me gain a better perspective of the topic and therefore expand my theories on it and also contribute to it. One area I hold very dear to my heart as I proceed is to find out at the end of the course “how learning analytics can improve learning in Africa”.