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Cognitive Constraints in Students’ Performance: Analysis and Tentative Solution Dr Sanjoy Sanyal Associate Professor Seychelles 2006 Presented at a staff seminar in a medical college in Seychelles in 2006
Problem ,[object Object],[object Object],[object Object],[object Object]
Identification and Assessment ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Temporal considerations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Temporal considerations  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Textual magnitude ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Information load ,[object Object],[object Object],[object Object],[object Object],[object Object]
Information load ,[object Object],[object Object],[object Object],[object Object]
Information overload From Rudolph Hanka, University of Cambridge 10 14  synapses Connectivity formula   n(n-1)/2 Skull capacity = 400 cc to 1400 cc over 5 mill years But no change over several thousand years Doubling x 3 mill yrs Doubling x 1.5 mill yrs 10 11  neurons 5 x 10 21  synapses
Information overload From Rudolph Hanka, University of Cambridge Logarithmic scale Information doubling every 33 years 1 st  century 2 0 ->2 1 -> 2 2 -> 2 3   2 nd  century -> 2 4 ->  2 5   -> 2 6
Information overload From Rudolph Hanka, University of Cambridge No change in  Information doubling every 33 years over several 1000 years
500 years ago ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Leonardo da Vinci
200 years ago ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Andreas Vesalius
Depth vs. width trade-off IC IC IC IC IC IC IC IC “ We are learning more and more of less and less; One day we would know everything about nothing” Leo Ves Now
Cognitive load ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Cognitive load ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Cognitive load Adapted from Odell, King’s College, London
Cognitive load Adapted from Odell, King’s College, London
Cognitive load Adapted from Odell, King’s College, London
Cognitive load Adapted from Odell, King’s College, London
Cognitive load Adapted from Odell, King’s College, London
Memory Adapted from Dix & Finlay
Memory Adapted from Dix & Finlay
Learning Curve ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Learning curve Adapted from Wikipedia Exponential decay Plot shows decay for decay constants of 25, 5, 1, 1/5, and 1/25.   Large decay constants make the quantity vanish almost immediately; smaller decay constants lead to almost-imperceptible decrease.  Rate of decrease of ‘time taken’ or ‘effort required’ with each iteration
Learning styles ,[object Object],[object Object],[object Object],[object Object]
Learning styles and cognition Adapted from JISC, UK Adapted from Bendigo Senior Secondary College, Aus
Learning style models ,[object Object],[object Object],[object Object]
Learning style models ,[object Object],[object Object],[object Object],[object Object],Adapted from Memletics
Brain paradigms ,[object Object],[object Object]
Brain paradigms ,[object Object]
Brain paradigms Ned Herrmann:  4 (whole)-brain model
Personality Types ,[object Object],[object Object],[object Object],Guardian Artisan Rationalist Idealist
Personality Types ,[object Object]
Multiple Intelligence ,[object Object]
Cognitive Psychology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Framework for determining learning outcomes Attitude Skills Knowledge Affective Psychomotor Cognitive
Tentative Solution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tentative Solution  ,[object Object],[object Object]
Conclusion Adapted from Bendigo SS College, Australia 'Whole brain learning'
References ,[object Object],[object Object]
References ,[object Object],[object Object],[object Object]
References ,[object Object],[object Object],[object Object]
References ,[object Object],[object Object]

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Cognitive Constraints In Students’ Performances

  • 1. Cognitive Constraints in Students’ Performance: Analysis and Tentative Solution Dr Sanjoy Sanyal Associate Professor Seychelles 2006 Presented at a staff seminar in a medical college in Seychelles in 2006
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. Information overload From Rudolph Hanka, University of Cambridge 10 14 synapses Connectivity formula n(n-1)/2 Skull capacity = 400 cc to 1400 cc over 5 mill years But no change over several thousand years Doubling x 3 mill yrs Doubling x 1.5 mill yrs 10 11 neurons 5 x 10 21 synapses
  • 10. Information overload From Rudolph Hanka, University of Cambridge Logarithmic scale Information doubling every 33 years 1 st century 2 0 ->2 1 -> 2 2 -> 2 3 2 nd century -> 2 4 -> 2 5 -> 2 6
  • 11. Information overload From Rudolph Hanka, University of Cambridge No change in Information doubling every 33 years over several 1000 years
  • 12.
  • 13.
  • 14. Depth vs. width trade-off IC IC IC IC IC IC IC IC “ We are learning more and more of less and less; One day we would know everything about nothing” Leo Ves Now
  • 15.
  • 16.
  • 17. Cognitive load Adapted from Odell, King’s College, London
  • 18. Cognitive load Adapted from Odell, King’s College, London
  • 19. Cognitive load Adapted from Odell, King’s College, London
  • 20. Cognitive load Adapted from Odell, King’s College, London
  • 21. Cognitive load Adapted from Odell, King’s College, London
  • 22. Memory Adapted from Dix & Finlay
  • 23. Memory Adapted from Dix & Finlay
  • 24.
  • 25. Learning curve Adapted from Wikipedia Exponential decay Plot shows decay for decay constants of 25, 5, 1, 1/5, and 1/25. Large decay constants make the quantity vanish almost immediately; smaller decay constants lead to almost-imperceptible decrease. Rate of decrease of ‘time taken’ or ‘effort required’ with each iteration
  • 26.
  • 27. Learning styles and cognition Adapted from JISC, UK Adapted from Bendigo Senior Secondary College, Aus
  • 28.
  • 29.
  • 30.
  • 31.
  • 32. Brain paradigms Ned Herrmann: 4 (whole)-brain model
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39. Conclusion Adapted from Bendigo SS College, Australia 'Whole brain learning'
  • 40.
  • 41.
  • 42.
  • 43.