Deep vs. Surface Learning


Conceptual vs. Procedural Knowledge
Relational vs. Instrumental Understanding


Contrasting attitudes and motivations around what it means to “know.”

Principal Metaphors

Deep Learning Surface Learning
  • Knowledge is … scope of current human possibility
  • Knowing is … meaning
  • Learner is … an integrator (active agent)
  • Learning is …  making meaning, integrating
  • Teaching is … engaging
  • Knowledge is … information
  • Knowing is … using/applying information
  • Learner is … a collector (passive recipient)
  • Learning is … taking in information, memorizing
  • Teaching is … transmission




Deep vs. Surface Learning highlights a fundamental divergence of opinion around what it means to know something. Deep Learning is associated with intrinsically motivated forms of engagement, characterized by making meaningful connections between new and previous understandings. With Deep Learning, the learner knows how concepts relate to each other and knows how to apply the concepts to solve problems. Surface Learning tends to be associated with extrinsic motivations and is focused on the memorization and recall of information for formulaic responses. With Surface Learning, the learner is imagined to acquire new information without connection to other ideas and with little personal investment. (See Expert–Novice for associated distinctions.) Associated constructs and discourses include:
  • Inert Knowledge (Alfred North Whitehead, 1920s) – a dismissive reference to decontextualized knowledge learned in formal settings (reminiscent of Surface Learning)
  • Conceptual Knowledge (Conceptual Learning; Conceptual Understanding) – learning focused on developing appreciations of the structure and logics of abstract ideas (contrast: Procedural Knowledge)
  • Procedural Knowledge (Procedural Learning; Procedural Understanding) – learning aimed at eventually performing a task automatically (contrast: Conceptual Knowledge)
  • Relational Understanding (Richard Skemp, 1970s) – knowing when, where, and why to apply a mastered rule or procedure (contrast: Instrumental Understanding)
  • Instrumental Understanding (Richard Skemp, 1970s) – knowing how to apply a mastered rule or procedure (contrast: Relational Understanding)
  • Heuristic (Cognitive Heuristic) – an experience-based strategy for tackling a problem that typically leads to a solution, often with efficiency (contrast: Algorithm)
  • Algorithm – a well-defined sequence of steps that can be used to generate a solution to a specific type of question (contrast: Heuristic)
  • Deep Active Learning – a mash-up of Deep vs. Surface Learning and Active Learning, thus emphasizing learner agency, active engagement, conceptual understanding, and intrinsic motivation. (Note: There’s also a Deep Active Learning associated with Machine Learning.)


Deep vs. Surface Learning might be viewed as a scaled-down and simplified version of the contrast between Correspondence Discourses and Coherence Discourses, as it foregrounds incompatible conceptions of learners (e.g., passive recipients vs. active agents), knowledge (e.g., external objects vs. emergent possibilities), and so on. However, although Deep vs. Surface Learning presents a contrast that has been useful for distinguishing between teacher-centered and learner-focused approaches to education, it lacks consistent theoretical underpinnings and robust conceptual development – owing in large part to the fact that it’s been taken up by educators across the spectrum of beliefs.

Authors and/or Prominent Influences

Ference Marton; Roger Saljö; Richard Skemp

Status as a Theory of Learning

Deep vs. Surface Learning is not a theory of learning because it does not offer new insights into the complex dynamics of learning.

Status as a Theory of Teaching

Deep vs. Surface Learning is a theory of teaching. That is, it is focused on modes of structuring lessons and manners of student engagement that are associated with different types of learning.

Status as a Scientific Theory

Deep vs. Surface Learning is more a principle to interpret an individual’s learning than a theory that invites a research program. As such, it doesn’t make much sense to consider its scientific status. That said, recent research in Neuroscience has demonstrated that there are observable differences in brain function between the two types of learning.


  • Algorithm
  • Conceptual Knowledge (Conceptual Learning; Conceptual Understanding)
  • Deep Active Learning
  • Heuristic (Cognitive Heuristic)
  • Inert Knowledge
  • Instrumental Understanding
  • Procedural Knowledge (Procedural Learning; Procedural Understanding)
  • Relational Understanding

Map Location

Please cite this article as:
Davis, B., & Francis, K. (2021). “Deep vs. Surface Learning” in Discourses on Learning in Education.

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