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10 pseudo-scientific myths about learning 1. Behaviourism 2. Learning styles 3. L/R brain theories 4. Mozart effect 5. Most of Piaget 6. Vygotsky.

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Presentation on theme: "10 pseudo-scientific myths about learning 1. Behaviourism 2. Learning styles 3. L/R brain theories 4. Mozart effect 5. Most of Piaget 6. Vygotsky."— Presentation transcript:

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4 10 pseudo-scientific myths about learning 1. Behaviourism 2. Learning styles 3. L/R brain theories 4. Mozart effect 5. Most of Piaget 6. Vygotsky 7. Maslow 8. NLP 9. Kirkpatrick 10. Get a life not a coach

5 10 ignored scientific facts about learning 1. Spaced practice 2. Cognitive overload 3. Chunking 4. Order 5. Episodic & semantic memory 6. Psychological attention 7. Context 8. Media mix 9. Learn by doing 10. Peer groups

6 10 ways to keep courses short 1. Learning objectives 2. ‘Introduction’ 3. Pretty but useless graphics 4. Text 5. Audio 6. Annoying animation 7. Video 8. Glossary 9. Abandon fixed times 10. Happy sheets

7 10 ways to massively increase retention 1. Self- rehearsal 2. Take notes 3. Blogging 4. Repetition 5. Delayed assessment 6. Record 7. Spaced e-learning 8. Mobile technology 9. Games 10. Simulations

8 Email donald.clark@hotmail.co.uk Blog http://donaldclarkplanb.blogspot.com/ Twitter @donaldclark Facebook DonaldClark

9 Kirkpatrick STOPS innovative learning

10 Recommendations Kill Kirkpatrick Customise to decision makers Customise to decisions Don’t harvest - sample Keep it simple

11 Binkerhoff’s Success Case Method -Qualitative analysis -Find out quickly what's working and what's not -Mining for best and worst cases -All about IMPACT on organisation

12 Robert Stake's Responsive Evaluation -Quantitative & qualitative analysis -Observe and respond -Customise to situation

13 Daniel Stufflebeam's CIPP Model: Context ( needs, assets, and problems within a defined environment) Input (competing strategies & work plans & budgets of selected approach) Process (monitor, document, and assess program activities) Product (impact, effectiveness, sustainability, and scalability) Decision/Accountability-Oriented Evaluation (Stufflebeam, 2001, in Evaluation Models)


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