My daughter was highly interested in learning to play piano. She undertook classes for a year and was doing quite well. However the instructor got changed thereafter. Within just a few months of that, she decided that she no longer wants to continue with learning piano. We suggested looking for another instructor but unfortunately she had lost interest permanently.
Was the second instructor to blame? Well, in my view the second instructor was not necessarily bad given that some of his students were actually doing quite well. Moreover, he was following a standardized curriculum from a respectable university to deliver the course. However, we can see that something indeed went wrong in this case. I tried to analyze the situation and am sharing my views that may be useful in guiding learning design and delivery.
One of the biggest challenges that learning designers and instructors face is to ensure that the learners continue to remain motivated and engaged throughout the process. It is known that learning is not easy and often a painful activity depending on the nature and complexity of the knowledge and skills involved. In worst case, motivated learners can become disinterested and drop out which is a result of their personal learning experience.
Instructional designers have the responsibility for designing learning solutions that include the course coverage, courseware resources, and instructional delivery techniques to be used for successful achievement of the intended learning outcomes. Designers use their expertise on learner characteristics, domains of learning, taxonomies of learning and good principles of instruction and learning when designing learning solutions. Some of these theories also cover conditions of learning. However I must point out that this alone is not sufficient.
More recently a role titled Learning Experience Designers has gained popularity. This is a very thoughtful title and Instructional designers must not just change the title but understand and transform themselves to fit into this broader role. Learning Experience Design is a better representation of the task at hand. It clearly broadens the scope of designing and building learning solutions. It expands the focus to cover the entire learning process whether it is directed or self-directed, regulated or self-regulated. It goes beyond the coverage of content, its format and mode of delivery.
An important reference for learning experience designers is the Flow Model and associated research . You may want to consider applying it when developing learning solutions. At the heart of the Flow Model is what is referred to as the “optimal experience” that not only keeps the person deeply involved and engaged but also produces “emergent motivation” to continue learning.
Rather than focusing on the person, abstracted from context (i.e personal traits), flow research has emphasized the dynamic system composed of person and environment, as well as the phenomenology of person-environment interactions,
A distinctive aspect of the Flow Model is that it views “experience” from a wider perspective as explained here:
- The experience is shaped by both the person and the environment
- Emphasizes conditions both “before” and “during” the actual experience that determine if the person is expected to experience “flow”.
- Emphasis on pre-existing intentional structure within a person that has a significant influence on the “drive” or “motivation”.
It is also useful for those trying to solve performance issues with training and looking for ROI on learning. They will be able to understand why the same course can have different outcomes when taken by different individuals. And why the connection between actual performance and the quality of training cannot be strongly correlated.
It is not just the instructional method that results in the outcomes but also on consciousness of the learners, their attention and awareness, their past experience, and goals or aspiration for the future that has influence on their behavior associated with the learning activity and the ultimate learning outcomes.
My daugther’s instructor was delivering the right lessons and guidance however not paying as much attention to the environment and the role that learner’s personal traits, prior experience and other factors played in the entire experience. Despite this face-to-face instructor led training, lack of sensitivity to some critical factors and following a set standard and instructional techniques led to a serious negative outcome. While it is important to cover the right lessons and use good instructional methods as a teacher, it is important to be a good coach and a mentor too.
This is exactly why in a massive online open course (MOOC) millions of learners may register for the course but less than a few thousand complete it and even fewer who successfully apply the acquired knowledge and skills to work. It is also why most eLearning courses have very poor completion rates.
With advancements in technology such as use of Artificial Intelligence in learning platforms and systems, serious opportunity exists on building features that are aimed at management of learner consciousness, their subjective experience and their attention. Artificial Intelligence can be leveraged for mass customization of learning experiences. Considering that each learner participating in the learning experiences is different and their environment is also variable, it can become possible to improve the quality and quantity of outcomes at scale with appropriate use of AI.
Online learning is growing rapidly and on its way to disrupt both formal and informal education and training systems. While it has been adopted widely, the need to build systems that are not just scalable but also equally or more effective is large and critical. AI holds the potential to strongly influence the learning experience and the outcomes.