What is Generative Learning?

generative learning

Generative learning is a theory that suggests that the learning process is based on the memory that is already stored in our brains. As new data is added to our long term memory, it becomes part of our knowledge base. 

The theory of generative learning is based on the assumption that the human brain does not simply passively observe its environment or the events it experiences. Rather, it constructs its own perceptions about problems, scenarios, and experiences.

Generative Learning was founded by educational psychologist Merlin C. Wittrock, who suggested that new ideas must be integrated with preexisting mental schema. This schema may consist of personal experience, previously acquired knowledge, and learner cognitions. Wittrock believed that learners, in a process called “generation,” established relationships between stimuli and the information they’ve already stored in their memory. 

In other words, in order to learn, people need to make a connection between the new concept presented to them and what they already know. Connecting the dots in intuitive ways is the core of generative learning theory.

generative learning

The 4 Key Concepts of Generative Learning Theory

The Generative Learning Theory involves four key concepts that instructional designers can incorporate into their courses. Designers need not use all four; they can pick and choose depending on the needs of the learner and the learning materials involved.

  1. Recall occurs when the learner accesses information stored in long term memory. The primary goal is to encourage learners to acquire a concept that is based upon facts and information they already know. Examples of recall techniques might be having the learner repeat information or reviewing it until the concept is fully grasped.
  2. Integration involves the learner integrating new information with similar knowledge they already possess. The aim is to alter this information into a form, which the learner can more easily remember and access later on. Examples of an integration activity might be having the learner paraphrase the content or creating analogies to explain a concept.
  3. Organization involves learners linking knowledge they’ve already collected to new concepts in an efficient way that makes them remember. Examples of organization strategies may include creating lists and ranking certain items, or analyzing the main points of a concept.
  4. Elaboration involves asking the learner to connect new concepts to information that they’ve already collected in creative ways. Examples of elaboration techniques include imagining how the new information fits into their daily work or knowledge.

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How L&D Leaders Can Incorporate Generative Learning in eLearning

Take a Problem Solving Approach

Problem solving is one of the most effective generative learning activities. Problem solving requires that learners evaluate all of the circumstances surrounding the problem and assess it using the skills or information they have available.

Rather than have your learners watch a video or animation about someone else solving a problem, actively encourage your learners to solve a problem given a life-like scenario. They can solve the problem alone or in small groups. 

Develop Branching Scenarios That Facilitate Active Recall

Active recall involves accessing information from long-term memory. Rather than simply using information they recently learned, branching scenarios force learners to utilize ideas and concepts they’ve encountered in the past. Not only does this reinforce preexisting information by refreshing the memory, but it connects new information to old ideas to construct new meaning.

L&D leaders can facilitate active recall by creating problem solving scenarios that goes one step further and is more immersive. If there is a bit of stress or pressure in the situation, learners will be forced to use active recall to draw on resources they already have. 

Provide Real-World Examples

For generative learning to occur, learners must be able to relate to the new information. The learner is more likely to retain new concepts if they demonstrate relevance to an on-the-job task. When the skill is used in real life, the learner is much more likely to retain the knowledge.

Give Learners Some Autonomy

Self-regulation and motivation are two of the driving forces behind the generative learning theory. While a course may not overtly indicate as such, learners must be able to take control of the process and actively form a meaningful connection if the concepts are going to stick. 

For seasoned employees and professionals, L&D leaders can offer learner-centered online training paths to give people the opportunity to set their own goals and choose the ideal online training activities based on their own awareness of preexisting knowledge. Such autonomy may not work for new employees or younger professionals but eventually it will. 

Trigger Attention

Though a longstanding component in instructional design, it is actually part of generative learning theory: keep your learners engaged. Whether it’s interesting images, exciting video, or unusual language, your learners will take notice. Such stimuli help learners acquire and retain knowledge.

Help Learners Connect the Dots

Sometimes corporate learners may not be able to see the connection between new ideas and the knowledge they’ve already acquired. Structure the knowledge to help them identify relationships, as well as compare and contrast concepts. 

Your subject matter experts, with whom you’ve worked to develop course content, can step in here to help organize the information intuitively. A visual map or path of the concepts can ease the learning process.

In sum, generative learning is about forming connections between the old and the new. Learners can effectively assign meaning to new concepts if they can associate them with preexisting knowledge or experiences. 

Oftentimes, creating immersive and challenging learning experiences force employees to recall old knowledge while incorporating the new.

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What is Generative Learning?