Today, eLearning has gained immense popularity due to the technological shifts and emergence of sudden shocking events like the COVID-19 pandemic. The way organizations function and deliver training to employees has undergone a huge change. eLearning was initially restricted to the education sector, but now it has made inroads, even in the corporate world. As more and more companies have switched to online training, the eLearning market is expected to grow even further. The eLearning market is flooded with various learning management systems or LMS software that have eased the work of organizations.
As companies are embracing eLearning, the importance of learning analytics is increasing too. After all, “data is the new oil”. eLearning professionals and the L&D team are engaged in mining and analyzing data of users that can help them provide the best training for their employees.
Let us now try to understand what learning analytics is, why is it important and what mistakes eLearning professionals should avoid while dealing with it.
What Is Learning Analytics?
Learning Analytics is a process of measuring, collecting, analyzing, and reporting data about learners. This data comprises all the learning activities of employees and hence is used by organizations to optimize learning or training for employees.
eLearning makes data mining, collection, and analysis much simple and makes learning analytics more effective in evaluating learning outcomes. Moreover, the use of big data and learning analytics can be more useful in capturing the learning experiences and learning activities of online learners.
Learning analytics opens up doors of opportunities for the eLearning professional. It helps determine what events occurred during an eLearning session, why a particular event occurred, and patterns of occurrences of such events.
You can collect various types of data using learning analytics. For example-
- User data
- Engagement data
- Performance data
What Is the Importance Of Learning Analytics?
Learning analytics is important for your business in the following ways:
- Collect user data like their qualification, experience, job role, eLearning courses opted, etc.
- It collects the engagement data of users, i.e., the data that reflects the interaction of users with their eLearning courses. This includes-
- The number of times an eLearning module was opened and for how long was it accessed
- How many users started an eLearning course?
- How many users completed an eLearning course?
- How many users visited a course more than once?
Such data helps you to understand the training program from the employees’ perspective. For instance, if an eLearning module isn’t accessed much by the users means there is something wrong with that module.
- It helps in analyzing the performance of the learners. For instance, this data tells us whether online learners were able to recall topics and content during assessments. Through this, you can understand the usability of your eLearning content.
- It helps in continuously collecting data that can be used for learning and development purposes.
- It helps eLearning professionals to restructure their online training programs in case they find any voids.
What Mistakes To Avoid While Dealing With Learning Analytics?
Since the eLearning market is growing rapidly, more and more data is generated by businesses. This has raised challenges in managing learning analytics.
Here are some mistakes that all eLearning professionals must try to avoid while dealing with learning analytics.
- Make sure your learning analytics strategy is aligned with your business goals
For an online training program to be successful, you need to align your learning analytics with business goals. A well thought and goal-oriented approach will help eLearning professionals to prioritize different kinds of learning data. Without a proper plan or approach, eLearning professionals won’t be able to collect fruitful data.
When learning analytics strategy is not aligned with business goals, then eLearning professionals will keep collecting similar kinds of data and hence ignore other relevant information.
For instance, the success of a training program cannot be solely decided by the course completion or assessment scores. Other data that measure their engagement is also important. Hence, you must look at the bigger picture that takes into account the individual and business goals. Thus, identify business and eLearning program goals and map them to data that your eLearning platform can track.
You must determine which data you want to collect and analyze, and what metrics are the most important from a business perspective.
Here are some examples of metrics that you should not avoid collecting:
- Frequency of visits to the program
- Time spent on the course and each module
- Time to complete a course
- Employee satisfaction with the training program
- Comments and use of different types of content
- Grades in the different evaluations
- Make sure you analyze data comprehensively
Learning analytics has become a key to making the right decisions for the business. It has been found that eLearning programs’ success directly affects your business growth.
For instance, you’re restructuring your product design team and introducing new eLearning courses. It is advised to use learning analytics to find out the engagement and performance of employees in product designing and whether they can practically apply that knowledge in the real life. A few months later, you witness a jump in your product’s sales. The clients and customers loved your product design. Thus, any growth in your business can be linked to the success of your eLearning programs. Such links are established through learning analytics.
- Avoid using complicated tools for collecting data
You must try to find out a tool that can ensure quick, accurate, and detailed access to data. This is essential for a successful learning analytics strategy.
If you choose a simple tool, anyone from the L&D team can use the information or data in reports and analytics. If the tool is complicated, then data collection and analysis can be hampered or misinterpreted leading to wrong analysis.
- Not being a part of data culture
Today, we all are witnessing a data revolution and many companies have joined the league of learning analytics. However, some organizations are not embracing the data culture. Some eLearning professionals in the L&D team resist change and don’t focus much on learning analytics. They keep introducing new eLearning courses or resources without checking the efficacy of previous ones. This simply throws them out of the race as they fail to gauge the outcomes of their training programs.
- Not taking any action despite the collection of data
Some organizations collect data, yet fail to take any action. For instance, the L&D team collects a lot of data on the efficacy of their sales training programs, but when they decide to refresh their eLearning courses, they don’t revisit such data and simply launch new courses. This can significantly impact your business growth.
However, organizations that have properly used such data have reported an increase in profits.
Conclusion
After understanding the utility of eLearning data and learning analytics, you must tap this opportunity to give new life to your training programs. But make sure you collect accurate and relevant data to measure the effectiveness of your training programs.
