Training Pitfalls & AI
Reflecting back on previous posts, we have discovered a 2018 blog about Using Training Analysis to Avoid Common Training Pitfalls. Why would this be relevant now? Due to COVID-19, employment and education locations shifted. At this time, 90% of corporations use eLearning for training. Knowing this, what did we consider the falls in 2018 and how could AI be applied to them now?
How AI Assists with Pitfalls
Pitfall #1: Assuming Training is Needed
Often, a trigger event occurs that leads us to develop and require training. But, is a training course required?
AI would provide a historical perspective on the event. Was it an isolated event (ex: Reply All vs Reply for email responses or timecard policy)? Is it occurring organization wide or isolated to department(s)? How long has the event been occurring?
The answers to these questions will help in establishing the best training solution, if needed.
Pitfall #2: Assuming Training is Supported by Leadership
By using AI, you can eliminate assumptions from the training program.
AI learning analytics can gather survey data from leadership for deep analysis. How?
Similar to previous, more time-consuming analysis methods, AI allows for organizations to filter, search and compare vast amounts of data. AI also allows for consistent, constant thematic searching of the data.
In the case of leadership, the thematic search can be used to determine leadership support or opposition to training while allowing for complete anonymity for the survey responders.
Pitfall #3: Assuming Training is the Best Solution
In a similar data gathering method used for the leadership, AI can gather survey data from employees. The employees can be guaranteed anonymity due to analysis being performed by AI.
Through the AI, themes can be set to search for training likes and dislikes (ex: training length, types, favorite instructors, etc.), course needs, or open suggestions for unknown ideas.
What About New “Pitfalls”?
The more AI is applied to your training program; the more you may uncover new ‘pitfalls’ or stumbling blocks that were never noticed. These may require only small adjustments to your overall training program.
For example, as you consider Pitfall #3, you may discover that the learners prefer training that takes no longer than 15 to 20 minutes at a time. This means you will need to go through your courses and break them down into smaller lessons or what is most commonly referred to as microlearning.
Conclusion
AI provides an analytics solution to training that once applied will continually improve as more data is added. As the AI searches through vast amounts of data, it only improves its ability to discern the needs of the current and possible themes. QAA has an example Learning Analytics Solution that is based on a university setting comparing two instructors. However, our Learning Analytics Solution may be adjusted to meet any learning analytics needs.