Adaptive Learning

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Adaptive Learning in its fundamental form is a learning methodology that changes the pedagogical approach toward a student based on the student’s input and a predefined response. Adaptive learning more recently is being associated with a large-scale collection of learning data and statistically based pedagogical responses and can be seen as a subset of personalized learning that includes such approaches as affective and somatic computing.[1]

A key component in creating an adaptive learning solution is leveraging big data to target all types of learners. By using big data to understand past experiences and develop best learning practices, it becomes easier to analyze specific behavioral patterns that can be used to improve learning systems and enhance learner success.[2]

Adaptive Learning
source: Dreambox

Adaptive Learning - History[3]
Adaptive learning has been with us for a while, with its history of adaptive learning rooted in cognitive psychology, beginning with the work of behaviorist B.F. Skinner in the 1950s, and continuing through the artificial intelligence movement of the 1970s. Now, technologies once confined to research laboratories are being adopted by progressive industries, including online services that drive consumer sites like Amazon and Netflix to anticipate preferences, and forward-thinking organizations. As a proven learning modality, it’s being used in many different environments to teach and train more effectively. For example, adaptive learning technology is used by NASA for simulation training, safety models, and has been used in various branches of the U.S. military, including the Army Learning Concept 2015, that trains and educates soldiers for asymmetric warfare.

Adaptive Learning - Technology and Methodology[4]
Adaptive learning systems have traditionally been divided into separate components or 'models'. While different model groups have been presented, most systems include some or all of the following models (occasionally with different names):

  • Expert model – The model with the information which is to be taught
  • Student model – The model which tracks and learns about the student
  • Instructional model – The model which actually conveys the information
  • Instructional environment – The user interface for interacting with the system

Best Practice Requirements for Adaptive Learning[5]
Adaptive learning is incredibly exciting, but it has some unique requirements to make it work well. They are:

  • Accurate definition of core competencies and standards. Functional training, by definition, enables the development of employees’ skills and knowledge so that they can successfully perform a job. Therefore, having a constructive relationship with the business process owners to define the right competencies to learn is important. Training business partners who have instructional design expertise and understand business processes and requirements can ensure employees learn the right content and measure by the right standards.
  • Strong training design capabilities. Having access to robust training design capabilities is an important component for success.
  • Robust assessments and metrics and a culture of critical thinking. Assessment and feedback loops are a critical part of adaptive learning. Becoming effective at assessing skill gaps can ensure learners don’t think they know more than they actually do.
  • Strong governance to support investments and commitment. In a global enterprise, managing the training function is a tricky business. Adaptive learning holds incredible potential in centralized models, in which all training-related functions and activities are managed by a centralized organization, especially when supported by a group of senior business leaders who preside over key training decisions and can support them with significant financial and technical expertise. In this type of model, it’s easier to both invest in and implement IT and systems infrastructure with senior executive support for the adaptive learning model.
  • Strong expertise in organizational development (OD), particularly in competencies modeling and assessments. While OD skills can be out-tasked with external vendors, having in-house capabilities retains knowledge and enables an organization to adapt to requirement changes quickly, efficiently, and effectively.
  • Strong partnerships with credible partners. CLOs need to do due diligence to scope out the right vendors whose products and services fit the specifications and requirements uncovered early in the process. Consultative vendors you can trust make the journey to a new learning model less perilous.

Product and services companies, especially those that have a more “centralized learning infrastructure,” are better positioned to take on the challenge of moving toward a more fully leveraged adaptive learning model.

Adaptive Learning - Opportunities and Challenges[6]

  • Adaptive learning works well where it’s not just information transfer but where concepts are to be taught. So, it may not work very well in programs such as, say Induction or Product Trainings, but can work very well for competency development programs, or for building skills such as Project Management etc.
  • But these soft skill or competency related trainings are generally smaller part of training budget pie, with most of the budget going to functional, sales, and compliance trainings. And since except compliance, other topics are generally very organization specific, it would fall on the shoulders of SME’s (Subject Matter Experts) to create content that’s suitable for adaptive framework. Now, we all know, that would be easier said than done.
  • So, the opportunity really is in creating adaptive framework ready e-courses that can be consumed by corporate learners across verticals (such as Project Management), and for someone to create an adaptive LMS (Learning Management System) itself. Now, since there are no standards for creating an adaptive framework, for an OTS (off-the-shelf) content developer, it would mean not only creating courses but also creating adaptive LMS and bundling them together – which would mean difficult sales, as many customers would already have a LMS or may not like the lock-in. Other solution to avoid creating a full-blown adaptive LMS would then be to create an extension to an LMS – an LRS (Learning Record Store) of some sorts, which will track data in parallel to the LMS on which content is hosted, and share that data back with content modules for dynamic sequencing/feedback etc.


  1. Adaptive Learning - Definition Gartner
  2. The Role of Big Data in Adaptive Learning Training Industry
  3. History of Adaptive Learning? DreamBox
  4. Adaptive Learning Models Wikipedia
  5. Best Practices to Use Adaptive Learning Programs in Corporate Training American Management Association
  6. Adaptive eLearning in Corporate Space – Opportunities and Challenges [^ Manish Gupta]

Further Reading