February 13, 2014
Analytics has been around for a long time now. Many commercial websites utilise analytics to determine such things as visitor numbers, most popular pages, geographical location of visitors, and so on. More sophisticated systems analyse user activity in real-time and feedback tailored content. In specific relation to education, Learner Analytics is capbable of measuring student achievement, tracking student progress and assessing learning outcomes.
The analysis of this data can help organisations determine how users interact with their resources, ultimately aiding their decisions to shape the best course of future action. For instance, educators can make changes to the curriculum or adjust the content of their learning resources to help boost the effectiveness of their message. One of the most outstanding benefits of Learner Analytics is the ability to identify areas (either resources or student) whose learning outcomes are below expectations. Educators are then empowered to adjust their programme to help meet the needs of their students more effectively.
Learner Analytics is the process of gathering and analysing data, generating reports, and finally enabling evidenced-based interventions. The practical benefits are best realised through data reports that are well designed and easily digestible. Reports can come in various forms; the most effective facilitate a quick understanding of data through visual representations such as charts, graphs and maps. Real-time, dynamically generated views enable more accurate models of student activity.
The success of any analytics system is based on the ability of the system to expose meaningful patterns of data. This begins with the architecture of the system: Is it collecting the right data? Is the data being stored in an accessible and flexible database structure? How often is the data collected?
The next stage is identify how the data can be meaningfully displayed so as to expose and illustrate patterns. Now the responsibility moves from the system architects to the educators themselves, who are best placed assess the most appropriate analytics model. Designing the right analytics system is about planning
The ultimate stage in the process, and arguably the most important, is the course of action that is undertaken following the collection and viewing of data. The stages may be broken down as follows:
These preliminary thoughts on Learner Analytics indicate the size of the subject, and its newness. I hope here to have offered a glimpse into the potential breadth of application that Learner Analytics assumes. The future remains to be shaped; the plethora of discussion forums that take place in universities and educational organisations about the topic all pose essentially the same question: Does Leaner Analytics have the potential to change the landscape of educational practice.
The answer, I believe, is a cautious yes. What remains is the willingness of educators to embrace the technology and to create applications that have Learner Analytics built in from the start.
Tags: Learner Analytics