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A novel web-based learning platform for accelerated
knowledge retention in higher education
Jeremiah R. Cohen, B.S.
David ...
The Problem
• Increasing volumes of knowledge to retain
• Memorization tools have not fundamentally changed in 10 years
• ...
Jeremiah
George
(formerly “Enki Learning”)
Why not automate Gagne’s 9 Levels of Learning?
• Gain attention (Reception)
• Informing learning of the objective (Expecta...
Strategy
Content
Retrospective Cohort
• Inclusion criteria
• Studying for USMLE Step 1 Board Exam
• 100+ questions answered
• 2+ study sess...
Overview
• 558 students identified
• 552,631 facts studied
0
500
1000
1500
2000
2500
3000
3500
25th 50th 75th
FactsStudied...
Facts Studied per Learning Mode
1. Multiple Choice
2. Flashcards ~ Matching
3. Candy Cannon
79%
10%
10% 1%
Multiple Choice...
Accuracy
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
25th 50th 75th
Accuracy
Percentile
Overall
Multiple Choice
Flashcards...
Weighted Accuracy
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
25th 50th 75th
Accuracy
Percentile
Overall
Multiple Choice
F...
Accuracy per Subject Mastery
R² = 0.9928
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20% 40% 60% 80% 100%
Accuracy
Mastery
Accuracy per Subject Mastery per Mode
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20% 40% 60% 80% 100%
Accuracy
Mastery
Mu...
Case Study: “Cellular Proteins”
• Inclusion criteria
• Set with a large amount of study activity
• Reached exactly 70% mas...
Case Study: Facts Studied per Learning Mode
61%
24%
14%
1%
Multiple Choice Flashcards Matching Candy Cannon
Case Study: Accuracy per Subject Mastery
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20% 40% 60% 70%
Accuracy
Mastery
Case Study: Facts studied to reach 70%
80%
82%
84%
86%
88%
90%
92%
94%
96%
98%
100%
0 50 100 150 200
Accuracy
Number Facts...
Conclusions
• When presented with multiple learning modes, medical
students show an overwhelming preference for multiple c...
Next steps
• Correlate study data with exam scores
• Real-time data tracking for students and educators
• Leverage data to...
Thank you!
We welcome your feedback and questions
yermie@memorang.io
george@memorang.io
Memorang NSF MOOC 2014
Memorang NSF MOOC 2014
Memorang NSF MOOC 2014
Memorang NSF MOOC 2014
Memorang NSF MOOC 2014
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Memorang NSF MOOC 2014

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A novel web-based learning platform for
accelerated knowledge retention in higher
education

Published in: Education, Technology
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Memorang NSF MOOC 2014

  1. 1. A novel web-based learning platform for accelerated knowledge retention in higher education Jeremiah R. Cohen, B.S. David Geffen School of Medicine at UCLA Massachusetts Institute of Technology, 2009 Memorang.io George J. Courtsunis, B.S. Massachusetts Institute of Technology, 2009 Memorang.io June 5, 2014
  2. 2. The Problem • Increasing volumes of knowledge to retain • Memorization tools have not fundamentally changed in 10 years • Most of these tools center around “flashcards” • Flashcards represent knowledge in a one-to-one relation, while integrated knowledge requires many-to-many relations. • Lack of detailed feedback for metacognition • Many students lack structure Create Evaluate Analyze Apply Understand Rote memory
  3. 3. Jeremiah George (formerly “Enki Learning”)
  4. 4. Why not automate Gagne’s 9 Levels of Learning? • Gain attention (Reception) • Informing learning of the objective (Expectancy) • Simulating recall of prior learning (Retrieval) • Presenting the stimulus (Selective perception) • Providing learning guidance (Semantic encoding) • Eliciting Performance (Responding) • Providing Feedback (Reinforcement) • Assessing Performance (Retrieval) • Enhancing Retention and Transfer (Generalization)
  5. 5. Strategy
  6. 6. Content
  7. 7. Retrospective Cohort • Inclusion criteria • Studying for USMLE Step 1 Board Exam • 100+ questions answered • 2+ study sessions • Last 4 weeks • Data items recorded • Answers, mode of study, accuracy, study sessions, mastery score, specific content studied
  8. 8. Overview • 558 students identified • 552,631 facts studied 0 500 1000 1500 2000 2500 3000 3500 25th 50th 75th FactsStudiedPerStudent Percentile
  9. 9. Facts Studied per Learning Mode 1. Multiple Choice 2. Flashcards ~ Matching 3. Candy Cannon 79% 10% 10% 1% Multiple Choice Flashcards Matching Candy Cannon
  10. 10. Accuracy 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 25th 50th 75th Accuracy Percentile Overall Multiple Choice Flashcards Matching Candy Cannon
  11. 11. Weighted Accuracy 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 25th 50th 75th Accuracy Percentile Overall Multiple Choice Flashcards Matching Candy Cannon
  12. 12. Accuracy per Subject Mastery R² = 0.9928 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 20% 40% 60% 80% 100% Accuracy Mastery
  13. 13. Accuracy per Subject Mastery per Mode 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 20% 40% 60% 80% 100% Accuracy Mastery Multiple Choice Flashcards Matching Candy Cannon
  14. 14. Case Study: “Cellular Proteins” • Inclusion criteria • Set with a large amount of study activity • Reached exactly 70% mastery • Data items recorded • Answers, mode of study, accuracy, study sessions, mastery score, specific content studied • Selection: • 17 students • 196 facts per student to reach 70%
  15. 15. Case Study: Facts Studied per Learning Mode 61% 24% 14% 1% Multiple Choice Flashcards Matching Candy Cannon
  16. 16. Case Study: Accuracy per Subject Mastery 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 20% 40% 60% 70% Accuracy Mastery
  17. 17. Case Study: Facts studied to reach 70% 80% 82% 84% 86% 88% 90% 92% 94% 96% 98% 100% 0 50 100 150 200 Accuracy Number Facts Studied to reach 70% Mastery
  18. 18. Conclusions • When presented with multiple learning modes, medical students show an overwhelming preference for multiple choice questions over other modes • Mastery scores can be used to predict accuracy • At lower levels of subject mastery, matching is the easiest • At moderate-to-high levels of mastery, all modes are equal • Flashcards are not more effective than any other learning mode, and students may benefit from having more flexibility.
  19. 19. Next steps • Correlate study data with exam scores • Real-time data tracking for students and educators • Leverage data to offer personalized recommendations • Determine optimum answer events to thoroughly master a concept • Experiment with different strategies and modalities (e.g. spaced repetition vs. original order vs. randomized shuffle). • Compare mobile device vs. desktop/laptop studying
  20. 20. Thank you! We welcome your feedback and questions yermie@memorang.io george@memorang.io

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