Adaptive Learning: Summary and Opinion


Adaptive learning is a method of learning experience design which leverages technology and algorithms to deliver learning tailored to the individual’s unique needs. Some conditions are required to create such an experience:

Delivery technology: a learning management system (LMS) which tracks learner progress through the content

Modularised content: decomposed to “granular” learning objectives with matching assessments, enabling pinpointing of gaps in comprehension. A common example is pre-test to understand where to initially place the learner in the course.

Algorithms: predict which “probes” or problems the learner may be able to answer correctly and which are the next level of difficulty, guiding the learner to the next content. For example, vendors such as McGraw-Hill include attributes such as: response time, learner confidence in the answer, and accuracy in the calculations.

Adaptive learning includes some concepts of cognitive psychology:

  1. Deliberate practice: intentional focus on concepts the learner needs development in at the next level of skill
  2. Ebbinghaus “Forgetting Curve”: a theory of repetition, how concepts are encoded from short-term to long-term memory, and when is the best moment to influence this encoding
  3. Metacognition: the learner reflects on his or her own confidence in the concepts
  4. Gamification: introduction of fun and competition to stimulate engagement.

Potential impact on teaching and learning:

The benefits in an adult learning context:

  • Learners don’t waste time covering concepts they are already familiar with, which is more engaging for the learner and more efficient from a business perspective.
  • Learners get constant reinforcement and encouragement, building confidence.
  • Suitable for situations like “pre-boarding” in universities, where the instructor would like to ensure all students are at the same skill level before proceeding with the course content.

The potential drawbacks:

  • This subject reminds me of Skinner’s learning machines in the 1930’s and 40’s. Technology will never be a 100% substitute for a great teacher who facilitates a group of humans to interact with each other. A good helper to the instructor, yes. It’s important to remember that!
  • Adaptive learning as presented here requires significant  programming: of the learning objectives, “probes,” assessments, algorithms to make this approach work ideally.
  • The effort and investment required means it would work well for subjects in which the content is not changing constantly, such as subjects taught in K-12 or theoretical introductory courses. In a corporate scenario, I would imagine only compliance training or say, introductory leadership and management courses would justify such an investment.
  • Most organisations I have worked with say they want this type of approach, but when it comes down to committing resources, learning is not prioritised for investment.


Image Source:

Posner, Z. (2017, January 11). What is Adaptive Learning Anyway? Retrieved from