An important – though often overlooked – component of instructional design and eLearning development is learning and adapting to the behavior of your learners through eLearning analytics.
Big data and its technologies have become such a major factor driving eLearning and continuing education that 80 percent of large businesses and 63 percent of smaller businesses were using or planning to use big-data solutions, according to an IDG research study.
And for employee training, data can be analyzed to increase training efficiency and efficacy to optimize skill development.
ELearning analytics are the collection of data gathered while learners are engaged in eLearning, as well as the analysis and reporting of such information. For eLearning specifically, critical pieces of data are recorded throughout the course – such as a learner’s score on a test, how quickly they progress through a module, how many times they’ve logged in, if they’ve participated in a discussion board and more.
As such, eLearning analytics offer facilitators and instructors a comprehensive, holistic view of how a learner performs, specifically if they’re struggling with a particular lesson or subject, and if they are likely to pass or fail.
With such information, it can then be determined which learning materials are appropriate, useful or relevant based primarily upon learner’s performance, skill level, and personal interests.
The data collected through analytics enables instructional designers and eLearning professionals to better cater to learners at a more intimate level than ever before. Here are a few ways learning analytics can improve eLearning.
• Predict learners’ performance. Analytics can provide insight into future performances throughout the eLearning course by determining if learners will benefit from additional supporting materials or peer/instructor aid to ensure comprehension and retention.
• Provide learners personalized eLearning. Analytics provide the ability to tailor each eLearning experience to the individual learner. Since no two learners are alike, learning analytics give eLearning professionals the ability to highly customize their approach to reflect a learner’s intellectual and academic individuality.
• Increase retention rates. As analytics adapt to each learner, success rates are, in turn, much greater and as such, fewer learners are likely to drop out or fail. If a learner fares well throughout the eLearning course, then they are more likely to be motivated to complete the course successfully.
• Help improve future eLearning courses. Learning analytics can help to shape future courses, too. If, for example, the data shows that a majority of learners find an aspect of the course too challenging, then developers can adjust content and levels of difficulty accordingly.
• Increase cost efficiency. By understanding how eLearning courses and resources are being leveraged, how learners consume information, and what course elements succeed and fail, users can allocate resources accordingly to maximize their ROI.
For a real-world application, let’s look at the case for evidence-based training for the International Civil Aviation Organization (ICAO).
According to the Evidence-based Training (EBT) Foundation, Evidence-based Training (EBT) is ‘ … a new approach, developed on behalf of the International Civil Aviation Organisation (ICAO), led by a large group of airline industry experts with the goal to increase the effectiveness of pilot training and meet the challenges of airline operations in the 21st Century. It arose from the need to develop a new paradigm for competency-based training and assessment of airline pilots, based on evidence.’
In order to reduce the airline accident rate, it was determined that a strategic review of recurrent and type-rating training for airline pilots was necessary. And, just as with many other industries, the international standards and regulations for airline pilot training are based largely on the evidence of accidents.
With the availability of data provided by flight operations, training activity, flight data analysis, flight observations and air safety reports, developers were given detailed insight into the threats, errors and undesired aircraft states encountered in modern airline flight operations in order to adapt and evolve training to allow – and even precipitate – pilot errors in a controlled environment in order to create effective, safety-conscious learning.
By leveraging such data to make improvements in training programs, businesses benefit from happier, more capable employees with better skills contributing to the bottom line.
“Some of the most exciting … ways in which we might use data [is] to understand every student much more deeply,” said Tim McKay, Professor of Physics, Astronomy and Education and faculty director the University of Michigan’s Digital Innovation Greenhouse. “Students benefit because we can change the course of their learning throughout their experience starting from the very beginning by helping them make course corrections, understand best practices and to become better students.”
Ultimately, eLearning analytics can help train and engage learners – with long-term sustainability. These improvements will empower business owners to more effectively and efficiently advance employee skill sets in order to meet new workforce demands and developments, and adapt to business changes more fluidly and efficiently. Learn how our solutions can provide you necessary data for your course optimizations.
By: Victoria Zambito, SVP of Content and Communications