Instructor-Led Training: A Guide to the ILT & vILT Data You Need

What are instructor-led training and virtual instructor-led training (ILT/vILT)?

Instructor-led training (ILT) is in-person training that’s run by an instructor at a scheduled time and location, often in a classroom setting. When this training happens remotely, it’s known as virtual instructor-led training (vILT).

ILT may or may not use technology, such as digital whiteboards or quizzing apps. vILT is usually conducted either with specialist virtual classroom technology—which may feature breakout rooms, virtual whiteboards, and other features—or with standard video conferencing tools such as Google Meet, Microsoft Teams, FaceTime, or Zoom.

Specialist vILT software may capture some valuable data relating to when learners join and leave the session. If the software also includes functionality—such as quizzing—you also can capture learner responses to questions.

vILT conducted via basic video conferencing platforms and in-person ILT may not generate any data at all. This means that tracking learning in an ILT/vILT context requires additional interactions with technology specifically to create data.

For example, you can use the following methods to capture data in ILT and vILT:

• The instructor records attendance in the LMS. This provides data about which learners attended which ILT sessions.
• The instructor uses a checklist app to rate learners for various tasks. This provides data about the learner’s level of participation and proficiency.
• Learners complete a quiz or assessment via an e-learning course or within the LMS. This provides data about knowledge gained during the course and is especially useful for comparing assessments completed before and after.
• Surveys are sent to learners and/or their managers and colleagues. You can use surveys to capture data about what the learner has applied from the training in their work.

ILT/vILT data requirements and what to ask your vendor

The most common data collected concerning ILT/vILT relates to enrollment and attendance on a course. This data can be combined to calculate no-shows—those who enroll in the session but do not attend.

You may find there are patterns in your attendance and non-attendance data. For example, as illustrated in the example below, one of our clients found that people were more likely to no-show at the end of the week because they often had work deadlines that were a conflicting priority.

Data about learner attendance is vital in telling you who has or has not attended the training. This information is critical for compliance training or any training where it is essential that a particular group of learners complete the training.

Reporting on attendance data also can generate lists of people who need to complete the training while providing a high-level view of completion segmented by parts of the organization.

These pie charts for different segments of the organization show what percentage of people have completed their required training versus those who have not, and those who are currently up to date but their certifications expire in the next 30 days, and will need to repeat the training.

We also recommend capturing data about engagement in the session, skills development, knowledge obtained, and application of those skills and knowledge beyond attendance.

This chain of evidence illustrates the impact of attending the training through to improvements in work. In addition, where learners apply the training in their work, this data can provide good evidence that the training led to that change.

For training where you can’t see an impact, you can use data to identify where issues arose. For example, did learners attend but not engage? Or did they engage, but the learning did not land? Or did they learn but fail to apply that learning in the workplace?

Understanding where the issues arose can guide the design and implementation of further interventions to improve the success of the ILT/vILT sessions.

If you want to purchase a new system to support ILT or vILT or capture ILT/vILT data from existing systems, ask questions about what helpful data you might capture and available for extraction.

However, as discussed earlier, the primary data source about learner activity and progress within an ILT or vILT session will likely not be the software used to facilitate the session.

So instead, you should focus on what tools you want to use to capture that L&D data—whether that’s a checklist app, assessment platform, survey tool, and/or something else.

ILT/vILT and your learning ecosystem

The LMS typically manages registration, session assignment, and attendance for ILT and vILT sessions. If you integrate the vILT tool with the LMS, you can launch the vILT sessions in the LMS. You also can launch vILT sessions from the LXP or via a link in an email or calendar invite.

Good ILT sessions should be designed with an awareness of the learning ecosystem. They may incorporate or signpost online learning content hosted on various ecosystem platforms as part of the session.

Online content may also be recommended for completion before and after the session. This approach of mixing self-paced online content with ILT/vILT is known as blended learning.

Combining data from ILT/vILT training with data from other learning activities may help you understand the impact that other learning activities—especially those intended to be completed before or after the ILT session—have on the success of the training session. For example, some of the questions you might ask are:

• Do learners who watch the pre-session videos engage with and perform better in session activities?
• Do learners working towards a particular skill enroll for this session?
• Are learners who engage with the follow-up quiz more likely to apply the learning in their work?

These answers can inform the blend of learning activities placed around the ILT session and the ILT session itself—leading to more effective learning programs.

To combine ILT/vILT data with data about learning activities completed around the ILT/vILT session, you must use a common learner identifier for all the activities or use identifiers that can be mapped together in the LAP.

You will also need to identify which activities relate to specific ILT/vILT sessions, but you typically do this mapping as part of the report configuration.

You can generate ILT/vILT data with a combination of checklist apps, assessment tools, and surveys; as a result, changing these tools can impact the ILT/vILT data. Therefore, don’t forget the ILT/vILT data when considering changes to these tools.

Changes to tools that provide the learning experiences around the ILT/vILT session as part of your blended approach may also impact reports relating to ILT/vILT. So make sure you consider the impact on all reports that use data from a platform or tool before replacing it.

The role of the ILT/vILT in skills and compliance

At a basic level, ILT/vILT data will show evidence that learners attended the required compliance training.

However, to show that compliance training has an impact, you may want or be required to show evidence from other tools—such as checklist apps, assessments, and surveys—that learners are engaging with and learning from the session and applying that knowledge in the workplace.

ILT/vILT data can be helpful for skills reporting in illustrating what skills learners are spending time developing. After the ILT/vILT session, data from assessments, surveys, and observations recorded in checklist apps can also prove skills gained and applied.

Up Next: What are AR/VR data requirements?

In contexts where practical training in realistic situations or with real equipment is dangerous or expensive, augmented reality and virtual reality can provide a cheaper and safer way for learners to experience something close to the real thing before they experience reality.

And while instructor-led training may not generate a lot of data by default, with AR and VR simulations the challenge is selecting which data is most relevant and useful from a wealth of possible data points. In our next post, we explore what sort of data you should look to get from AR and VR experiences and the data questions to discuss with your vendors.