Tailored Learning Experiences Via AI
Telephone switchboard
I've been thinking about the LMS of the future and jotting down a few thoughts. The ideas harken back to my time as a Methods and Procedures engineer.
I will focus on an organizational call center training program delivered and implemented via an LMS, with access to the tools call centers typically utilize. The first scenario below assumes that the organization requires agents to be cross-trained and able to resolve all types of customer issues (billing, tech support, sales, etc.). The second assumption is that an organization prefers agents to develop and hone their skills to serve the customer better.
I view AI as pivotal in creating personalized learning programs tailored to individual students. If a student struggles with an assessment multiple times after course delivery, AI can personalize an eLearning or mLearning course catered explicitly to that learner via the LMS. The organization will determine if eLearning or mLearning is appropriate or available. To further hone in on the student’s learning needs, the customer relationship management (CRM) software can track how often an agent transfers a call to another department to solve the customer’s problem—a problem the agent should have been able to fix given the courses they have taken, as tracked and logged in the LMS. AI can also capture data when a customer must call back, track the agent via the CRM, and use this data to suggest further actions or tailor a custom learning program for that agent through the LMS.
Another use of AI and the LMS relies on assessment results. For instance, if an agent takes courses on troubleshooting and consistently excels on the assessments, the LMS tracks this. The same student, on the other hand, regularly struggles with handling billing issues as tracked by the CRM (transfers the call to another agent, the customer’s problem isn’t resolved the first time, and has to call back), AI can cross-reference information in the LMS on how the agent performed on billing course assessments. If AI identifies a trend, it can then work with the integrated voice response system (IVR) to route customer technical issues to the relevant agent, improving first-call resolution and reducing unnecessary transfers. As the CRM tracks agent success with these call types, the LMS can then suggest more advanced personalized courses in a particular subject matter. If the agent continues to succeed, the organization can flag that agent as a potential candidate for promotion or generate automated parts of the agent’s performance review.
The impact on instructional designers is significant. Rather than having a learner take all the courses in a full curriculum where everyone must take all the classes, AI can formulate a personal learning experience, eliminating subjects that the learner has proven to be proficient via assessment results. This enables a better designer by utilizing AI and the LMS to deliver a personalized learning experience. Sustainability and maintenance of courses consume a significant portion of a designer’s time (I once managed a team of designers and oversaw a 10-week onboarding curriculum, and I can attest that maintenance can be a substantial time drain). AI can also assist with this workload. AI can search the LMS and its courses for a specific course number and subject matter. If, for any reason, the organization decides to change the course number or title, AI can perform this task for the designer, saving time.
