How do you serve multiple masters? Very often instructional designers are tasked with the challenge of satisfying many stakeholders with different learning objectives or priorities. One SME may want more technical information, a manager may want to emphasize the sales aspects, while the support team wants to address recurring issues.
AI might be able to offer different learning paths or different content, but it could be challenging for a couple of reasons. First, it might not be easy to separate learning goals. How much technical information is too much for a salesperson? Is a support issue a technical one or sales? Secondly, the learner’s needs are fluid and are likely to shift during the learning process. For example, a salesperson may want more technical information part way through the course, but not for the entire course. This would be a daunting challenge for AI to detect in a timely fashion.
The question now arises, how does AI inform the instructional designer? How do you design a course with enough flexibility to satisfy multiple stakeholders? The answer is that AI systems are currently not a good design guide. However, the LI (Learner Intelligence) model provides the structure for dealing with multiple but related learning objectives. LI designs are also adaptive enough to respond instantly as the learner’s needs change.
The LI model is based on user choice. In the above example, every page or slide in the course would have options for the learner to choose from technical, sales, or support issues. The user may choose to learn from one, two, or all three perspectives, at any point in the course and in any order. At the point of need the relevant content is only one click away. The net result is that one course can simultaneously serve the needs of multiple stakeholders. For more information see A Three-Step Approach to Adaptive Design.