Do learning styles exist?

learning styles

Generally known as “learning styles”, it is the belief that individuals can benefit from receiving information in their preferred format, based on a self-report questionnaire. This belief has much intuitive appeal because individuals are better at some things than others and ultimately there may be a brain basis for these differences. Learning styles promises to optimize education by tailoring materials to match the individual’s preferred mode of sensory information processing.

There are, however, a number of problems with the learning styles approach. First, there is no coherent framework of preferred learning styles. Usually, individuals are categorised into one of three preferred styles of auditory, visual or kinesthetic learners based on self-reports. One study found that there were more than 70 different models of learning styles including among others, “left v right brain,” “holistic v serialists,” “verbalisers v visualisers” and so on. The second problem is that categorising individuals can lead to the assumption of fixed or rigid learning style, which can impair motivation to apply oneself or adapt.

Finally, and most damning, is that there have been systematic studies of the effectiveness of learning styles that have consistently found either no evidence or very weak evidence to support the hypothesis that matching or “meshing” material in the appropriate format to an individual’s learning style is selectively more effective for educational attainment. Students will improve if they think about how they learn but not because material is matched to their supposed learning style. The Educational Endowment Foundation in the UK has concluded that learning styles is “Low impact for very low cost, based on limited evidence”.

 

References

  • Educators’ letter to the Guardian, No evidence to back idea of learning styles, In the Guardian, Sunday 12th March 2017, full article available here
  • The debate over learning styles, In Mosaico Blog, posted on 3rd of September 2017, full blog post available here

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Gagne’s conditions of learning

GAGNE

Gagne identifies five major categories of learning:

  • verbal information: facts of knowledge
  • intellectual skills: problem solving, discriminations, concepts, principles
  • cognitive strategies: meta-cognition strategies for problem solving and thinking
  • motor skills: behavioral physical skills
  • attitudes: actions that a person chooses to complete

Learning tasks for intellectual skills can be organized in a hierarchy according to complexity:

  • stimulus recognition,
  • response generation,
  • procedure following,
  • use of terminology,
  • discriminations,
  • concept formation,
  • rule application, and
  • problem solving

Each different type requires different types of instruction. The theory outlines nine instructional events and corresponding cognitive processes:

  1. Gaining attention (reception)/show variety of computer generated triangles
  2. Informing learners of the objective (expectancy)/pose question: “What is an equilateral triangle?”
  3. Stimulating recall of prior learning (retrieval)/ review definitions of triangles
  4. Presenting the stimulus (selective perception)/ give definition of equilateral triangle
  5. Providing learning guidance (semantic encoding)/ show example of how to create equilateral
  6. Eliciting performance (responding)/ ask students to create 5 different examples
  7. Providing feedback (reinforcement)/ check all examples as correct/incorrect
  8. Assessing performance (retrieval)/ provide scores and remediation
  9. Enhancing retention and transfer (generalization)/ show pictures of objects and ask students to identify equilaterals

 

Reference

Conditions of learning, Robert Gagne. In InstructionalDesign.org. Full text available here/ For more click here  or here or search: Gagne, R. (1985). The Conditions of Learning (4th.). New York: Holt, Rinehart & Winston.

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Kuhn’s concept of ‘incommensurability’

incommensurability

The term originally appeared in Kuhn’s “The Structure of Scientific Revolutions” book in 1962. He had been struggling with the word since the ’40s:

According to Kuhn, he discovered incommensurability as a graduate student in the mid to late 1940s while struggling with what appeared to be nonsensical passages in Aristotelian physics(…) He could not believe that someone as extraordinary as Aristotle could have written them. Eventually patterns in the disconcerting passages began to emerge, and then all at once, the text made sense to him: a Gestalt switch that resulted when he changed the meanings of some of the central terms. He saw this process of meaning changing as a method of historical recovery. He realized that in his earlier encounters, he had been projecting contemporary meanings back into his historical sources (Whiggish history), and that he would need to peel them away in order to remove the distortion and understand the Aristotelian system in its own right (hermeneutic history) (…) Kuhn realized that these sorts of conceptual differences indicated breaks between different modes of thought, and he suspected that such breaks must be significant both for the nature of knowledge, and for the sense in which the development of knowledge can be said to make progress.

Kuhn was influenced by the bacteriologist Ludwik Fleck who used the term to describe the differences between ‘medical thinking’ and ‘scientific thinking’ and Gestalt psychology, especially as developed by Wolfgang Köhler.

Kuhn’s original holistic characterization of incommensurability has been distinguished into two separate theses:

  • taxonomic involves conceptual change (…) no over-lap principle that precludes cross-classification of objects into different kinds within a theory’s taxonomy/ no two kind terms may overlap in their referents unless they are related as species to genus, in contrast to
  • methodological, which involves the epistemic values used to evaluate theories (…) it is the idea that there are no shared, objective standards of scientific theory appraisal, so that there are no external or neutral standards that univocally determine the comparative evaluation of competing theories

 

Reference

The Incommensurability of Scientific Theories, In Stanford Encyclopedia of Philosophy, first published Wed Feb 25, 2009; substantive revision Tue Mar 5, 2013, available here

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Types of learning in a connectivist course

 

typesofconnectivistlearning

  1. Aggregation – access to a wide variety of resources to read, watch, or play, along with a newsletter called The Daily, which highlighted some of this content;
  2. Remixing – after reading, watching, or listening to some content, it was possible to keep track of that somewhere (i.e., by creating a blog, setting up an account with Delicious and creating a new entry, taking part in a Moodle discussion, or using any service on the Internet);
  3. Repurposing – participants were encouraged to create something of their own; in these MOOCs, the facilitators suggested and described tools that participants could use to create their own content, and it was envisaged that with practice, participants would become accomplished creators and critics of ideas and knowledge; and
  4. Feed Forward – participants were encouraged to share their work with other people in the course and with the world at large.

 

Reference

Kop, R., Fournier, H., Man, JSF, 2011. A Pedagogy of Abundance or a Pedagogy to Support Human Beings? Participant Support on Massive Open Online Courses. In IRRODL, Vol 12, no 7, 201, full article available here

Image available here

 

Systems theory & Autopoiesis/ Society & Complexity

lee-bul-autopoiesis

Systems Theory or Systems Science: A system is an entity with interrelated and interdependent parts; it is defined by its boundaries and it is more than the sum of its parts (subsystem)/ n a complex system (having more than one sub-system.) a change in one part of the system will affect the operation and output of other parts and the operation and output of the system as a whole, systems theory attempts to find predictable patterns of behavior of these systems, and generalizes them to systems as a whole. The stability, growth or decline of a system will depend upon how well that system is able to adjust or be adjusted by its operating environment

Niklas Luhmann-Social Systems Theory: distinction between system and environment (inside/outside)/ it is the communications between people not people themselves, they are outside the system/ our thoughts make no difference to society unless they are communicated/ systems communicate about their environments, not with them/ the environment is what the system cannot control/ systems relate to the environment as information and as a resource/ society-encounters-organizations: the three types of social systems.

Autopoiesis: literally means self-creation/ a system capable of reproducing and maintaining itself; it is autopoietic if the whole produces the parts from which it is made/

Society:  is an autopoietic system whose elements are communicative events reproducing other communicative events/ this communication has content and relationship levels: what is communicated and how/ all communication is both communication and communication about communication/ communication is imaginary/ communication takes place when an observer infers that one possible behaviour has been selected to express one possible message or idea/ the meaning of the message is always inferred by the observer.

Complexity: a system becomes complex when it is impossible to relate every element to every other element in every conceivable way at the same time/ when we can observe it in non equivalent ways/ when we can discern many distinct subsystems/ complexity is a property of observing 

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