Understanding Learning Analytics

Training, and the way it is delivered is constantly changing. Today, trainers and learning and development professionals have more access than ever to data. With so much training moving digital and e-learning becoming such a popular training tool, learning management systems (LMS) are becoming highly sophisticated. This means training professionals and business leaders can use analytics to ensure the training they’re offering is effective.

What are learning analytics? 

Learning analytics is the measurement, collection, analysis, and reporting of data about learners, their learning experiences, and the programs and processes that deliver the training. This data can be used to optimise learning and maximise its impact on the organisation’s performance and outcomes.

What can learning analytics show us? 

There are arguably endless ways that learning analytics can be used. Different organisations have different learning needs, meaning they can draw various things from the data and make use of them in numerous ways. However, the following summarises some of the most common things shown in analytics provided by learning systems.

Assessment Data. The most obvious type of data shown with learning analytics is assessment data. Many e-learning courses involve, multiple-choice questions, quizzes or increasingly simulation games, which are used to assess whether learners have successfully learnt the knowledge or skill that the course was intending to transfer. 

Individual Interaction Data. Most LMS systems can monitor all interactions a learner has with a course. This means being able to see how long an individual spent on a course, whether they took the quiz at the end multiple times, what choices they made during scenario-based simulated situations and so forth. Essentially, individual learning profiles can be created to understand different learners’ styles and the different ways that they engage with a course. 

Optional Course take-up. Some organisations offer optional training materials. Alongside mandatory courses, learners can benefit from optional opportunities to upskill (there is a range of benefits of offering upskilling opportunities). Analytics can highlight which courses are being taken and by who. 

Speaking of optional course take-up, optional courses can be costly. An organisation that offers optional training (most often in soft skills such as leadership or personal development) is spending money on creating or outsourcing materials which may or may not be used. Monitoring which courses are popular (or perhaps more importantly, which ones have a positive and recognisable impact on organisational performance) allows training professionals to adapt their offerings and ensure they are not wasting money on unnecessary materials. Analytics can therefore be used to ensure an ROI when it comes to selecting which training to offer.

Analytics gathered from individuals’ interactions with a course help an organisation ensure that learners are engaging as they are supposed to with learning. E-learning puts learning in the hands of the learners themselves in many ways, and whilst this offers a variety of benefits, it also means organisations are trusting learners to absorb information as required. For example, courses can be rushed through and so individual data can show how much time learners spend on a course. Another key metric from e-learning analytics is how often, and which, sessions or lessons are abandoned by learners.

There are several reasons learners may not engage well with courses. Organisations may decide to revamp their courses visually. Or they may be forced to consider what elements of their courses best suit their learners and their needs. Analysis of data may show that certain teams, such as the sale team, respond well to simulated scenarios. Content can be added or removed based on analytics.

As well as monitoring time spent or how often lessons are abandoned, overall engagement can be monitored. Learners may complete a course but not make use of comments sections, for example. This can highlight a lack of knowledge transfer, despite an individual making it through the entirety of the materials.

Analytics offers data at all times, meaning organisations have constant access to how their training is being engaged with. Knowing as soon as possible whether a course is too “easy” for a learner, or if it is extremely difficult, can help trainers and moderators take remedial action to ensure a better outcome for learners.

How are learning analytics useful?

So, to put it simply, analytics help organisations keep tabs on their learning to ensure they are getting a return on investment. Analytics highlight whether courses are successful, whether skills and knowledge are being transferred, whether they are of interest to employees and so forth. This allows organisations to make changes to their programs, whether that be modifying elements of individual courses or offering different courses altogether, and the quality and efficiency of the training program is improved.

Without analytics, training professionals would be much less equipped to make decisions regarding changes for individual employees, teams, or the organisation as a whole.

The growth of online learning is not only inevitable, but also desirable, and it’s already happening around us in almost every industry across the globe. It offers so many unique benefits, including the ability to collect valuable data which can shape a training program and improve the productivity of an entire business.

Interested in e-learning materials or the impact of a powerful LMS? Trainer Bubble offer a wide range of training course materials, including but not limited to e-learning courses. Explore our full range here, or contact us to find out how we can help your organisation succeed in offering the best training for your learners.