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Enabling Active Learning Using Prediction Markets
Enabling Active Learning Using Prediction
Markets
Dr. Patrick Buckley
Enabling Active Learning Using Prediction Markets
Introduction
Prediction markets are “designed and run for the primary
purpose of mining and aggregating information scattered
among traders and subsequently using this information in
the form of market values in order to make predictions
about specific future events”
Introduction
Pedagogical Application
Pedagogical Advantages
Enabling Active Learning Using Prediction Markets
Introduction
A Simplified Analogy: Prediction Markets can work like
multiple choice questions. So they are
• Scalable
• Flexible
But
• We can also ask students to calculate values
• They operate in real-time
• They allow students to change their mind
• They are obviously a group activity
Introduction
Pedagogical Application
Pedagogical Advantages
Enabling Active Learning Using Prediction Markets
Pedagogical Application
Our core insight – they can be used to create realistic
decision scenarios that link to learning outcomes and
allow learners to apply knowledge delivered via traditional
educational channels to real-world problems.
Example:
The National Budget Forecasting
Project
Learning Outcomes:
‘Consider and assess the impact of the annual tax budget’
‘Explain the theory underpinning a tax system’
Introduction
Pedagogical Application
Pedagogical Advantages
Enabling Active Learning Using Prediction Markets
Introduction
Pedagogical Application
Pedagogical Advantages
Pedagogical Application
We have pioneered two modes of operations
• Repetitive
• Continuous
We have pioneered across a range of disciplines
• Tax (Continuous)
• Finance (Repetitive)
• Risk Management (Repetitive)
Enabling Active Learning Using Prediction Markets
Pedagogical Advantages
Cognitive Domain of Learning
• Improved Decision Making
• Improved Information
Literacy
Introduction
Pedagogical Application
Pedagogical Advantages
Enabling Active Learning Using Prediction Markets
Pedagogical Advantages
Cognitive Domain of Learning
• Improved Decision Making
• Improved Information
Literacy
Introduction
Pedagogical Application
Pedagogical Advantages
Affective Domain of Learning
• Improved Motivation
Enabling Active Learning Using Prediction Markets
Pedagogical Advantages
Cognitive Domain of Learning
• Improved Decision Making
• Improved Information
Literacy
Introduction
Pedagogical Application
Pedagogical Advantages
Affective Domain of Learning
• Improved MotivationAdvantages for Staff
• Scalable
• Flexible
• Real-world, real-time
examples
Enabling Active Learning Using Prediction Markets
Publications
Cognitive Domain of Learning
• Improved Decision Making
• Improved Information
Literacy
Introduction
Pedagogical Application
Pedagogical Advantages
Affective Domain of Learning
• Improved MotivationAdvantages for Staff
• Scalable
• Flexible
• Real-world, real-time
examples
Buckley, P. and Doyle, E., 2012, Enabling Active Learning Using
Prediction Markets, EDiNEB 2012, Haarlem, Holland, May 2-5.
(Awarded Best Paper)
Buckley, P., Garvey, J. & McGrath, F., 2011, A Case Study on Using
Prediction Markets as a Rich Environment for Active Learning,
Computers and Education, 56(2)
Buckley, P. & Garvey, J. 2011 Using Technology to Encourage
Critical Thinking and Optimal Decision-Making in Risk
Management Education. Risk Management and Insurance
Review, Vol. 14, No. 2, pages 299–309, Fall 2011
Garvey, J. & Buckley, P. 2010. Teaching the Concept of Risk:
Blended Learning Using a Custom-Built Prediction Market. Journal
of Teaching in International Business, 21(4)
Enabling Active Learning Using Prediction Markets
Publications
Cognitive Domain of Learning
• Improved Decision Making
• Improved Information
Literacy
Introduction
Pedagogical Application
Pedagogical Advantages
Affective Domain of Learning
• Improved MotivationAdvantages for Staff
• Scalable
• Flexible
• Real-world, real-time
examples
Buckley, P. and Doyle, E., 2012, Enabling Active Learning Using
Prediction Markets, EDiNEB 2012, Haarlem, Holland, May 2-5.
(Awarded Best Paper)
Buckley, P., Garvey, J. & McGrath, F., 2011, A Case Study on Using
Prediction Markets as a Rich Environment for Active Learning,
Computers and Education, 56(2)
Buckley, P. & Garvey, J. 2011 Using Technology to Encourage
Critical Thinking and Optimal Decision-Making in Risk
Management Education. Risk Management and Insurance
Review, Vol. 14, No. 2, pages 299–309, Fall 2011
Garvey, J. & Buckley, P. 2010. Teaching the Concept of Risk:
Blended Learning Using a Custom-Built Prediction Market. Journal
of Teaching in International Business, 21(4)

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Enabling active learning using prediction markets - Patrick Buckley

  • 1. Enabling Active Learning Using Prediction Markets Enabling Active Learning Using Prediction Markets Dr. Patrick Buckley
  • 2. Enabling Active Learning Using Prediction Markets Introduction Prediction markets are “designed and run for the primary purpose of mining and aggregating information scattered among traders and subsequently using this information in the form of market values in order to make predictions about specific future events” Introduction Pedagogical Application Pedagogical Advantages
  • 3. Enabling Active Learning Using Prediction Markets Introduction A Simplified Analogy: Prediction Markets can work like multiple choice questions. So they are • Scalable • Flexible But • We can also ask students to calculate values • They operate in real-time • They allow students to change their mind • They are obviously a group activity Introduction Pedagogical Application Pedagogical Advantages
  • 4. Enabling Active Learning Using Prediction Markets Pedagogical Application Our core insight – they can be used to create realistic decision scenarios that link to learning outcomes and allow learners to apply knowledge delivered via traditional educational channels to real-world problems. Example: The National Budget Forecasting Project Learning Outcomes: ‘Consider and assess the impact of the annual tax budget’ ‘Explain the theory underpinning a tax system’ Introduction Pedagogical Application Pedagogical Advantages
  • 5. Enabling Active Learning Using Prediction Markets Introduction Pedagogical Application Pedagogical Advantages Pedagogical Application We have pioneered two modes of operations • Repetitive • Continuous We have pioneered across a range of disciplines • Tax (Continuous) • Finance (Repetitive) • Risk Management (Repetitive)
  • 6. Enabling Active Learning Using Prediction Markets Pedagogical Advantages Cognitive Domain of Learning • Improved Decision Making • Improved Information Literacy Introduction Pedagogical Application Pedagogical Advantages
  • 7. Enabling Active Learning Using Prediction Markets Pedagogical Advantages Cognitive Domain of Learning • Improved Decision Making • Improved Information Literacy Introduction Pedagogical Application Pedagogical Advantages Affective Domain of Learning • Improved Motivation
  • 8. Enabling Active Learning Using Prediction Markets Pedagogical Advantages Cognitive Domain of Learning • Improved Decision Making • Improved Information Literacy Introduction Pedagogical Application Pedagogical Advantages Affective Domain of Learning • Improved MotivationAdvantages for Staff • Scalable • Flexible • Real-world, real-time examples
  • 9. Enabling Active Learning Using Prediction Markets Publications Cognitive Domain of Learning • Improved Decision Making • Improved Information Literacy Introduction Pedagogical Application Pedagogical Advantages Affective Domain of Learning • Improved MotivationAdvantages for Staff • Scalable • Flexible • Real-world, real-time examples Buckley, P. and Doyle, E., 2012, Enabling Active Learning Using Prediction Markets, EDiNEB 2012, Haarlem, Holland, May 2-5. (Awarded Best Paper) Buckley, P., Garvey, J. & McGrath, F., 2011, A Case Study on Using Prediction Markets as a Rich Environment for Active Learning, Computers and Education, 56(2) Buckley, P. & Garvey, J. 2011 Using Technology to Encourage Critical Thinking and Optimal Decision-Making in Risk Management Education. Risk Management and Insurance Review, Vol. 14, No. 2, pages 299–309, Fall 2011 Garvey, J. & Buckley, P. 2010. Teaching the Concept of Risk: Blended Learning Using a Custom-Built Prediction Market. Journal of Teaching in International Business, 21(4)
  • 10. Enabling Active Learning Using Prediction Markets Publications Cognitive Domain of Learning • Improved Decision Making • Improved Information Literacy Introduction Pedagogical Application Pedagogical Advantages Affective Domain of Learning • Improved MotivationAdvantages for Staff • Scalable • Flexible • Real-world, real-time examples Buckley, P. and Doyle, E., 2012, Enabling Active Learning Using Prediction Markets, EDiNEB 2012, Haarlem, Holland, May 2-5. (Awarded Best Paper) Buckley, P., Garvey, J. & McGrath, F., 2011, A Case Study on Using Prediction Markets as a Rich Environment for Active Learning, Computers and Education, 56(2) Buckley, P. & Garvey, J. 2011 Using Technology to Encourage Critical Thinking and Optimal Decision-Making in Risk Management Education. Risk Management and Insurance Review, Vol. 14, No. 2, pages 299–309, Fall 2011 Garvey, J. & Buckley, P. 2010. Teaching the Concept of Risk: Blended Learning Using a Custom-Built Prediction Market. Journal of Teaching in International Business, 21(4)