Cognitive Constraints In Students’ Performances
 

Cognitive Constraints In Students’ Performances

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Describes aspects of students' cognition, Learning styles and cognitive overload

Describes aspects of students' cognition, Learning styles and cognitive overload

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Cognitive Constraints In Students’ Performances Cognitive Constraints In Students’ Performances Presentation Transcript

  • 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
    • Acceptance of problem
    • Identification of further problem
    • Assessment of problem
    • Solution to problem
  • Identification and Assessment
    • Information load
    • Information overload
    • Cognitive load
    • Memory
    • Learning curve
    • Learning styles/preferences
    • Brain paradigms
    • Psychological personality types
  • Temporal considerations
    • Theoretically 16 weeks
    • Deduct ESExam and Prep weeks
    • Available 14 weeks
    • Available 98 days
      • 14 Saturdays & 14 Sundays
      • 70 weekdays
    • Deduct 1 weekday off each week
    • Available 56 weekdays
  • Temporal considerations
    • Consider:
      • 5 hours on weekdays
      • 8 hours on Saturdays
      • 10 hours on Sundays
    • 5 h x 56 weekdays = 280 weekday-hrs
    • 8 h x 14 Saturdays = 112 Saturday-hrs
    • 10 h x 14 Sundays = 140 Sunday-hrs
    • Total = 532 hours
  • Textual magnitude
    • Anatomy = 1155 pages
      • Less 10% = 1155 – 115 = 1040 pg
    • Histology = 407 pages
      • Less 10% = 407 – 41 = 366 pages
    • Embryology = 348
      • Less 10% = 348 – 35 = 313 pages
    • Medical Terminology = 922 pages
      • Less 10% = 922 – 92 = 830 pages
  • Information load
    • Anatomy : 1040/532 = 1.95 pg/hour
    • Histology : 366/532 = 0.69 pg/hr
    • Embryology : 313/532 = 0.59 pg/hr
    • Med Term : 830/532 = 1.56 pg/hr
    • TOTAL ~ 5 pages / hour
  • Information load
    • Physiology : 1.37 pages/hour
    • Biochemistry : 1.35 pages/hour
    • Neurosciences : 0.87 page/hour
    • TOTAL ~ 4 pages / hour
  • 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
    • Architect
    • Anatomist
    • Sculptor
    • Engineer
    • Inventor
    • Geometer
    • Scientist
    • Mathematician
    • Musician
    • Painter
    Leonardo da Vinci
  • 200 years ago
    • Anatomist
    • Physician
    • Surgeon
    • Gynecologist
    • Obstetrician
    • Pediatrician
    • Orthopedician
    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
    • Brachiocephalic
    • Phrenicopleural
    • Vasa brevia
    • Musculophrenic
    • Internal jugular
    • Lateral funiculus
    • Spinothalamic
    • Cuneocerebellar
    • Tractus solitarius
    • Funiculus gracilis
  • Cognitive load
    • Gostak distims doshes
    • Boetimperoferous
    • Isenorinopiclles
    • Halptemiloginous
    • Czashmigedonix
    • Etrigenxous
    • Acondolytic effect
    • Fekritionoxes
    • Donglistonix
    • Grodoscinamity
  • 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
    • “ Practice makes perfect "
    • a.k.a. Progress Functions
    • Applied to all types of work
      • Effort decreases by constant % each time output quantity is doubled
      • More times a task is performed, less time is required on each subsequent iteration
    • Steep learning curve = something gets easier quickly
  • 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
    • Everybody has a Learning Style (Preference)
    • No single type is wrong/right; good/bad
    • Related to cognitive and mental abilities
    • 71 models of learning styles
  • Learning styles and cognition Adapted from JISC, UK Adapted from Bendigo Senior Secondary College, Aus
  • Learning style models
    • Felder-Soloman : AR-SI-VV-SG
    • Honey-Mumford : ARTP
    • Kolb : ADAC / DW-TF /CE-RO-AC-AE
  • Learning style models
    • Fleming : VARK-Multi
    • Bandler, Grinder (NLP): VAK(Ad)
    • Martinez (LO): TPCR
    • Memletics : VAK-VLSS
    Adapted from Memletics
  • Brain paradigms
    • Each style uses different parts of brain
    • Paul MacLean : Triune brain model
  • Brain paradigms
    • Roger Sperry / Rose & Nicholl : Right-left brain model
  • Brain paradigms Ned Herrmann: 4 (whole)-brain model
  • Personality Types
    • Isabel Briggs Meyers : MBTI
    • 4 scales: EI-SN -TF-JP
    • 2 4 = 16 types
    Guardian Artisan Rationalist Idealist
  • Personality Types
    • David Keirsey : GARI Temperament sorter
  • Multiple Intelligence
    • Howard Gardner / Gary Harms Multiple (7 + 1) intelligence – related to Memletics learning styles (VAK-VLSS + Naturalistic)
  • Cognitive Psychology
    • Guilbert domains :
    • Bloom’s taxonomy :
      • Knowledge
      • Comprehension
      • Application
      • Analysis
      • Synthesis
      • Evaluation
    Framework for determining learning outcomes Attitude Skills Knowledge Affective Psychomotor Cognitive
  • Tentative Solution
    • Conduct survey
    • Identify:
      • Intelligence preference-based LS
      • Personality-based LS
      • Dominant t hinking pattern
      • Stress level
  • Tentative Solution
    • Once students know what learning type they are, they can capitalize on their strengths and strengthen their weaknesses
    • Once we know what type they are, we can plan the foundation for appropriately-oriented course delivery
  • Conclusion Adapted from Bendigo SS College, Australia 'Whole brain learning'
  • References
    • Hanka R. Information overload and 'just-in-time' knowledge. University of Cambridge, 1997. http://www.medinfo.cam.ac.uk/miu/papers/hanka/mic97/just_in_time.html
    • Odell E. Assessment by e-Learning http://www.kcl.ac.uk/content/1/c4/49/01/assessment%20e-learning%20Odell.ppt
  • References
    • Dix A, Finlay J, Abowd GD, Beale R. Human-Computer Interaction (3rd edition, 2003) http://www.hcibook.com/e3/
    • Learning Curve Calculator. http://www1.jsc.nasa.gov/bu2/learn.html
    • Experience curve effects http:// en.wikipedia.org/wiki/Learning_curve
  • References
    • Exponential decay http://en.wikipedia.org/wiki/Exponential_decay
    • Joint Information Systems Committee. http://www.jisc.ac.uk/uploaded_documents/Stage%202%20Learning%20Styles%20(Version%201).pdf
    • Bendigo Senior Secondary College. http://www.bssc.edu.au/public/learning_teaching/pd/toc/files/hbdt.ppt
  • References
    • Learning Disabilities Resource Community: http:// www.ldrc.ca/projects/miinventory/mitest.html
    • O'Connor T. Indiana State University. 1997 February 21. Using Learning Styles to Adapt Technology for Higher Education http:// web.indstate.edu/ctl/styles/learning.html