Today’s world is driven by data, and corporate training is no exception. At the end of the day, what really matters is if the training was worth the effort, time, and investment.
And learning analytics plays a major role in evaluating training and its effectiveness in your organization. So, let’s discover the know-hows of learning analytics:
Learning Analytics Defined
“Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.” – International Conference Learning Analytics and Knowledge
DATA
Collecting data that provides analytical insights
ANALYSIS
Applying research methodologies and adding intelligence to data
COLLECTION
Taking steps toward informing decisions, applying the insights gained and attaining the purpose
Types of Learning Analytics
Descriptive Analytics: What happened?
Descriptive analytics collate data from multiple sources to give insights about past performance. Your organization can use this to evaluate the data gathered through your LMS such as:
- Number of learners enrolled
- Number of hours spent on eLearning
- Average test scores
These data are often represented through real-time dashboards and reports that can help you understand the status of online training initiatives in your organization.
Diagnostic Analytics: Why did it happen?
This type of analytics is used to understand the reasons, trends, and outliers in your learning data. Moreover, it helps identify patterns and insights into a problem/opportunity; helping you determine the reason behind the lack of success of your learning programs.
DATA – More experienced salespeople have lower business course completion rates compared to new hires
SOLUTION – Course content was too basic for the senior executives, thus, the organization should roll out an advanced level course for them
Predictive Analytics: What can happen?
While this type of analytics doesn’t tell you what will happen in the future, it can forecast what might happen next; creating opportunities to provide targeted support.
In predictive reporting, analytics can be used to predict key future events for employees, including whether or not an employee will pass a course, and whether or not their engagement is about to drop. This allows L&D managers to offer solutions in advance to meet individual needs such as personalization and more directed learning goals.
Prescriptive Analytics: How can we make it happen?
Aside from finding solutions to what might happen, prescriptive analytics also helps you understand why it will happen. Moreover, it can provide recommendations on what can be done to further improve your L&D programs.
What the data says: I’m a finance professional taking communication courses. I wonder how can I apply this knowledge to my job?
What it really means: As a training manager, I should provide more personalized and industry-specific learning content.
Sources: eLearning Industry, Commlab India, goFLUENT Blog
