Data Analysis + Training Analysis = Complete ROI ‘Picture’
9 October 2018
With today’s data analysis tools, why would anyone need further training analysis to determine if the training was worthwhile? To answer this question, we need to consider two more questions:
- What does data analysis provide?
- What does training analysis provide?
The answer to these questions will answer the first question of why training analysis is needed in conjunction with data analysis.
What Data Analysis Provides?
Data analysis offers good insights about your learners and their habits while performing the training. Depending on the data analysis tools you use, SCORM or xAPI, your data may be minimum or robust.
For example, with SCORM data, you may track that your learners log into an LMS to take online training or to register for a virtual live training. The LMS tracks their completion or pass/fail of the test. If there are media, it will track the media was engaged.
However, if xAPI data is used, you may track how often a user logs in to a course. The incorrect answer(s) chosen before the correct answer was chosen. If a media was selected, how long the media was played. For each page, you may know if it was reloaded, how long a learner stayed on the page, etc. These details are valuable for designing and updating the training.
What Training Analysis Provides?
While the data analysis is critical to the design and update of the training for the learner, it is not the only requirement for determining the overall worth of the training. An analysis must be done of the learner in their environment to determine if the training had a impact.
Does the learner use the training? Has it become part of their repeated task performance? Also, how does leadership respond to the training? Do they encourage and reinforce the behaviors or are they ambivalent?
These factors cannot be measured or collected by data analytics, but must be observed and shared in focus groups and surveys. In the best situation, an experienced instructional designer reviews the training goals, objectives, and any enterprise goals before performing an unscheduled to the learner observation. The data gathered during the observation can then be compared to the data analysis from the LMS for a full report.
Conclusion
Data analysis tools provide good insights for instructional designers. However, we should never forget about the personal attention required through observation, interviews, and surveys which provide the full analysis report. These together will help determine if the training program is an investment which should continue as is or needs restructuring.
Beyond these, our customized AI solution paired with analyst reviews provides a complete ROI view to clients. QAA’s clients are presents with training recommendations based on data insights found in the analysis supported by the customized AI solution.