Root node

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PSLC theoretical hierarchy’s Root Node


PSLC research is primarily concerned with finding out what instructional environments, methods or activities causes students’ learning to be robust. Although normal learning can be measured with immediate, near-transfer post-tests, we measure robustness with three addition measures: retention, far transfer and preparation for learning.


PSLC General Glossary

Full Glossary

Glossary Knowledge component: A piece of information that can be used to accomplish tasks, perhaps with other knowledge components. �A generalization of everyday terms like concept, principle, fact, skill, and cognitive science terms like schema, production rule, facet. �A knowledge component relates features to a response where both the features and response(s) can be either external, in the world, like cues in a stimulus and a motor response or internal, in the mind, like inferred features and a new goal.

Research question

What instructional activities or methods cause students’ learning to be robust?

Dependent variables

Measures of basic learning (an immediate, near-transfer post-test) and measures of robust learning (retention, far-transfer and preparation for future learning)

Independent variables

Independent variables in PSLC are primarily instructional activities, methods, or treatments. Studies might also include independent variables that measure individual differences, like a language students' first language.


Learning will be robust if the instructional activities are designed to include appropriate paths, and the students tend to follow those paths during instruction.


Instructional activities influence the depth and generality of the students’ acquired knowledge components, the knowledge components’ strength and feature validity, and the student’s motivation. These in turn influence the students’ performance on measures of robust learning. That is, we take a cognitive stance, rather than a radically distributed or situated stance.

At the macro-level, instruction produces robust learning if it increases the frequency of:

  • sense-making processes: rederivation, adaptation and self-supervised learning
  • and foundational skill-building processes: strengthening, deep feature perception and cognitive headroom.

At the micro-level, instruction produces robust learning if:

  • The instruction is designed so that the learning event space has some target paths that would cause an ideal student to acquire knowledge that is deep, general, strong and retrieval-feature-valid.
  • Most students follow a target path most of the time. There are many factors outside the easy control of the experimenter or instructor, such as motivation and recall, that affect whether students actually follow the target paths designed into the instruction.


Annotated bibliography