The limits of Learning Design


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In this session I present my side of a debate or discussion with Diana Laurillard regarding the Limits of Instructional Design. I approach the question from the perspective of LD as a language, and suggest that as such it abstracts in a certain way and consequently defines and imposes a particular perspective on the topic, a perspective that is either arbitrary or cannot be supported from available evidence. For audio, video and more please see

Published in: Technology, Education

The limits of Learning Design

  1. 1. The Limits of Learning Design Stephen Downes February 22, 2012
  2. 2. • Learning design - topic - types of LD • The concept of patterns (designs / models / rules / principles) in general: an abstract representation of something concrete.Images: What is Learning Design?
  3. 3. All crows are • Were thought to be black created by extrapolation or generalization (1,2,3, ... infinity) • But are in fact created This crow is through a process of black subtraction. "An X is Y". This crow is black • All language abstracts inThis crow isblack this way. Creating Abstractions
  4. 4. • The elements of a language are whatever is left over after theImage: subtraction • The grammar or syntax of the language is the set of rules for manipulating those elements.Image: Elements of a Language
  5. 5. • Purposes of a language: – to describe / communicate – to explain – to reason – to define • All languages perform all of these functions (and more!)Speaking in LOLcats Purpose of a Language
  6. 6. • You cant create a language and say this is just to communicate; the very act of creating a language invokes all four elementsImage: • George Lakoff: Frame Frames
  7. 7. • Also, you cant talk about LD by talking as though the language isnt there • LD is the languageImage: • Various pseudo- languages: – Pseudo-code – Globish Learning Design as a Language
  8. 8. • Languages are more or less abstract – Eg. greater or smaller set of elements – Greater or smaller set of rules / rule-base – Greater or Smaller expressivityImage: Levels of Abstraction
  9. 9. • In science, there is a methodological principle to prefer pure abstraction - fewer elements, fewer principles: – numbers - math - counting – properties - sets - groupingImage: – computability - boolean - inferring/moving Formalism & Pure Abstraction
  10. 10. • the world is fundamentally a mathematical entityImage: The World as Mathematical Entity
  11. 11. Pure interpretation interpretationReal world language Abstraction This crow is All crows are black blacknatural language process -- rules – objects binary code Interpretation
  12. 12. • Reusability paradox - theory & practice – can we bridge this with a language?practise ---- interpretation ---- language ------ interpretation ---- theory The Reusability Paradox
  13. 13. • Is there a functionally useful language that describes (teaching, learning, etc)?Image: Questions for Learning Design?
  14. 14. • If there is such a language, then we can use computers to teach • If there is not, then we need teachers, but at a certain point, LDs become meaningless • (and one wonders, what is this that teachers do?)Image: Dilemma of Learning Design?
  15. 15. • What are the elements and syntax of that language? • What will ground or give meaning to those elements (i.e., what is the interpretation)?Image: a Learning Design Language
  16. 16. • If these are your primitives - what are these primitives? - what is their role? • Interpretation: the logical foundations for... • eg. probabilityImage: Primitives & Their Interpretation
  17. 17. • 3 models: flowchart, rule-based, object-event basedImage: Locked into Processes
  18. 18. • Is there a directionality in the process? • Locked into objectives (?) – problem solving, discovery ... others? – development of capacitiesImage: vs development of knowledge Locked into Directionality
  19. 19. • What are the primitive objects? What are their properties? • Locked into roles – e.g. conversational framework - teacher - student - other student – want to look at the substructureImage: Locked into Roles / Entities
  20. 20. • Epistemology - what grounds your theories • Theories of truth and reference • other approaches: – coherence webs of belief‘ – world as will and representationImage: Meaning and Reference
  21. 21. • Positivism: saying there is some set of facts - even e.g. the existing theories • (Most people areImage: positivists - it takes real guts to be a coherentist, or a relativist) Hidden Positivism
  22. 22. • The general principle is - you dont want to build the interpretation into the language - keep the language stupid - put semantics at the edgesImage: • Thats why e.g. LD wanted to be theory- neutral Theory-Neutrality
  23. 23. Language? Design? • but your primitives dont have to be pure basic abstracts... Predicate Computation Calculus • We can ‘reach out’ from pure abstraction (via Set Theory Mathematics computability & decidability) The purely abstract 1011010101 The Nature of the Purely Abstract
  24. 24. • Cognitivist theories - where the pure abstraction is based in the pure elements of thought • These elements are mapped to a ‘language of thought’ which is used to express abstractions • The theory-theoryImage: Cognitivism
  25. 25. • Another version of the same framework Image: urnal/vol4/cs11/report.html This crow is All crows are black blackreal world ---- interpretation ---- language ------ interpretation ---- HUMAN The Human Equation
  26. 26. • Non-theory-based theory – What do we believe are elements of the world? connections – What do we believe are the fundamentals of human thought? connections • Humans are fundamentally connective entities (and not cognitive entities)Image: The Non-Theory Theory
  27. 27. • In LEARNING no langauge per se in between them – It is a process of directImage: recognition (JJ Gibson) • real world ---- pattern recognition ---- HUMANImage: Direct Representation
  28. 28. • We use language to talk about this, but we should not confuse the language with the learning process – How do people learn then? – How do you get a person toImage: know x‘? • I said it takes courage to not be a positivist Language and Learning
  29. 29. • To learn: – Not to remember a set of facts (and/or theories) – Becoming a good recognizer, a good patternImage: creator • These are based in the principles of effective networks Pattern Recognition
  30. 30. • Teaser argument to conclude: • How do we learn languages? – we dont create a language to learn a language – a language is learned via the direct recognition of the language • aka thinking in French -- vs thinking in physics, etc.Image: Direct Perception
  31. 31. • • stephen@downes.caStephen Downes