Using attendance data to improve training programmes

Digital attendance tracking is now widely used within training organisations to monitor learner attendance. It is a new management solution that goes beyond a simple administrative tool; it enables you to generate verifiable documents for your funding bodies or other regulatory bodies, thereby allowing you to demonstrate the quality of your training programmes.

Data from attendance records and course registers are used for training management, as they enable the precise monitoring of learners’ attendance by analysing absenteeism rates and their attendance in class, and allow for personalised support to be offered if needed during a training course. In the same vein, it will play a key role in ensuring training quality, as it will enable us to assess whether the content provided is effective and to gauge learner engagement; finally, it serves to meet regulatory requirements, particularly in relation to OPCO funding or certifications such as Qualiopi. Furthermore, analysing learner engagement data offers avenues for improvement.

Not all attendance data is equally useful. Its usefulness will depend on your objectives and the indicators you wish to analyse.

The first data to analyse in the context of attendance tracking is learners’ attendance, absence and lateness. This allows for better monitoring of their attendance, particularly in situations where your learners are following a learning pathway or a training course funded by an external body. This body therefore requires a certain level of attendance and proof of attendance for the sake of those funding it.

There are also indicators relating to dropouts, when a learner stops participating in a course, and attendance data for a specific group or session.

Once collected and analysed, this data will help identify the causes of absence, lateness or dropouts, enabling you to adapt the course accordingly and achieve better results.

To maximise the effectiveness of your training programmes and offer relevant improvement solutions tailored to your course, you must first select the metrics that are right for you.

• Firstly, as you may have realised, the most important metric will be the attendance rate, to track the learner’s overall engagement throughout a learning path.
• Next, we have the rate of repeated absences. This helps to identify learners. This metric should act as a warning sign to prevent and anticipate dropouts.

By correlating these attendance indicators with learners’ progress indicators, such as their results, it is then possible to see the true performance of your course, as the aim is not simply to collect these indicators, but to measure their real impact on improving your training programmes.

Once you have analysed the data, you need to be able to take action to achieve tangible results.

By analysing data such as attendance and lateness rates during a session, you can gauge enthusiasm for a course and gauge its popularity among learners. If attendance is very low, even though attendance has been high throughout the course as a whole, this may mean that the module has not met expectations.

Proper monitoring of learners remains the most important step to take when attendance drops. When this happens, it is not enough to send reminder or warning emails; you must take the time to speak with the learner to identify their sticking points and understand their situation.

To quickly adapt training courses with low attendance rates, it is essential to conduct immediate satisfaction surveys (surveys carried out straight after a training session) and to set up a follow-up process with learners and trainers to identify areas for improvement.

Now that we have determined the importance of analysing the indicators and the attendance data. We need to know how to make the best use of this data.

First, the reliability of the collection: ensure that the data collected comes from reliable sources and that it has not been erroneous. For this, prioritise reliable sources such as satisfaction surveys or direct collection through face-to-face interaction. Next, centralise your data within a single management software, as this improves tracking and analysis.

To effectively utilise this data, we recommend using management software like SoWeSoft, which will allow you to collect all attendance data and centralise it within a single space. Moreover, this allows you to visualise all the data and cross-reference it with other educational data, enabling you to analyse it.

As you may have understood, the exploitation of your attendance data represents a major challenge for your training organisations. The analysis of this data will allow your teams to better manage your training programmes, identify the bottlenecks encountered by your learners and trainers during a course, and propose coherent corrective improvements in order to have a real impact on your training programmes.

The issue is also regulatory if you have a certification like Qualiopi or funders to whom you must justify the proper functioning of your training programmes. Good data management then allows you to prove the authenticity and legitimacy of your training programmes and to establish your credibility.

And don't forget that in this context, a single piece of data is not usable! You need to give it meaning and purpose in order to achieve your goals.