Learning 2017 McGraw-Hill Education Learning Science Platforms
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Presentation from 10/24/17 @ Learning 2017 session titled "Adaptive Learning: Personalization + Mastery + Engagement"
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Learning 2017 McGraw-Hill Education Learning Science Platforms
- 1. Header is here Adaptive Learning: Mastery, Personalization, Engagement From the learning science company Presented by Zach Posner Christina Yu
- 2. One-size-fits-all, sage-on-the-stage… 2©2016 McGraw-Hill Education. Confidential and proprietary. Not for redistribution. Image source: https://nkilkenny.wordpress.com/category/blogs/ Image source: https://nkilkenny.wordpress.com/category /blogs/
- 3. Principles of conventional learning 3 Conventional model of learning Everyone given the same amount of time to learn same thing Emphasis on final assessment Everyone given same instruction ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 4. Conventional learning standard outcomes #oflearners Mastery level Conventional learning
- 5. But modular content is everywhere
- 6. What does this mean for learning? Break content up Vs. Start Finish Start Finish
- 7. In our consumer lives, modular content is data-driven to maximize entertainment Music Social Media Videos/Movies Books
- 8. How can we use data to drive modular learning content? Entertainment Learning Like Dislike Star Rating Time Tagging Factors Demographic Factors
- 9. What are we optimizing for? Learning is different in that mastery is the goal 9 Learning objectives Assessments (or Probes) Learning resource ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 10. A learning objective: defines the goal 10 Each learning objective is aligned with a resource ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 11. A learning resource: brings the learner to mastery 11©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 12. An assessment: answering correctly reflects mastery 12 Below is a screenshot from SmartBook (the learner tool). It probes the learner’s mastery of the underlying learning objective linked to the learning resource. ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 13. What if we made learning all about mastery? What if you could not progress without demonstrating mastery? 13©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 14. Mastery-based Learning: Progress depends on mastery rather than seat-time 14 Mastery- model Conventional model of learning Everyone given the same amount of time to learn same thing Emphasis on final assessment Each learner progresses at own pace Everyone must achieve mastery before moving on to next objective No one can give up Everyone given same instruction ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 15. Conventional vs. mastery learning outcomes #oflearners Mastery level Conventional learning Mastery learning
- 16. One step further: adaptive learning scales one-to-one learning One-to-one mastery learning Conventional Learning Mastery Learning #oflearners Adaptive learning scales Mastery Level http://web.mit.edu/bosworth/MacData/afs.course/5/5.95/r eadings/bloom-two-sigma.pdf ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 17. 17 Metacognitive Theory The Theory of Deliberate Practice The Theory of Fun for Game Design Ebbinghaus Forgetting Curve Adaptive technology uses AI to personalize learning for each individual
- 18. How personalized mastery is delivered in real-time, at scale 18 Personalized Learning Path Probes Learning resources Data
- 19. Driving mastery: data is used to optimize the learning moment Entertainment Learning Like Dislike Star Rating Time Tagging Factors Demographic Factors Accuracy Confidence Time Cohort Trends
- 20. Mastery meets personalization and scale 20
- 21. Each learner reaches mastery in their own way
- 22. Each learner reaches mastery in their own way
- 23. A personalized path for each learner 23
- 24. What does this mean for content? Learning Goal: Drive a Car Defensive Driving Rules of the Road Operating a vehicle
- 25. Align micro learning objectives with resources and probes Dozens of Question Types Micro Learning Objective Learning Resource Probes Text Video Audio Web Link
- 26. Align micro objectives with resources and probes 26©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution. L R L R L R L R L R L R L R L R P P P P P P Each Learning Objective is aligned with resources and probes •••••• • L R L R L R PP P Micro Learning Objective Micro Learning Objective ? ? ? L R L R L R P P P L R L R L R PP P ? ? ? Text Web Link Audio Video Text Web Link Audio Video
- 27. Unlock performance through a powerful data layer 27©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution. Agile Authoring Tailored Instruction Data Layer L R L R L R L R L R P P ? Micro Learning Objective L R L R L R L R P PP Personalized Learning
- 28. Your turn: break learning goals down into objectives Merchandise Theme parks Movies Micro-objective:________________________ Micro-objective:________________________ Micro-objective:________________________ Micro-objective:________________________ Learning Goal: Understand the magic of Disney
- 29. Use Bloom’s taxonomy to help write objectives Source: https://cft.vanderbilt.edu/guides-sub-pages/blooms-taxonomy/ create evaluate analyze apply understand remember Produce new or original work Design, assemble, construct, conjecture, develop, formulate, author, investigate Justify a stand or decision Appraise, argue, defend, judge, select, support, value, critique, weight Draw connection among ideas Differentiate, organize, relate, compare, contrast, distinguish, examine, experiment, question, test Use Information in a new situation Execute, implement, solve, use, demonstrate, interpret, operate, schedule, sketch Explain ideas or concepts Classify, describe, discuss, explain, identify, locate, recognize, report, select, translate Recall facts and basic concepts Define, duplicate, list, memorize, repeat, state Vanderbilt University Center for Teaching Bloom’s Taxonomy
- 30. Example: break learning goals down into objectives Merchandise Theme parks Movies Micro-objective: Recall that Disneyland was founded in 1955 in Anaheim Micro-objective: Describe the structure of Magic Kingdom Micro-objective: Compare and contrast Epcot Center and Magic Kingdom Learning Goal: Understand the magic of Disney
- 31. Your turn: produce a question that assesses a micro- objective, no more and no less Consider multiple choice, ranking, categorization, matching as potential question types Text Video Audio Web Link Dozens of Question Types Micro Learning Objective Learning Resource Probes
- 32. 32 Tip: What makes a good probe? ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution. Characteristics of good questions: Aligned to objective Can be answered correctly Accuracy yields information about learner’s state of knowledge Realistic distractors Appropriate level of Bloom’s taxonomy
- 33. 33 Tip: Example of a good probe Good: Choose the best answer for when to probe the learner in an adaptive course. A) At the end of the course to test for mastery B) Only when the learner decides they are ready C) Throughout the entire course D) Before the course begins, as a diagnostic test BAD: True or false: Assessment in an adaptive course should only occur after a course is completed by a learner. LO: Understand the purpose of assessment in an adaptive course. ©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution.
- 34. Example: produce a probe that assesses a micro-objective Text Video Audio Web Link Dozens of Question Types Describe the structure of Magic Kingdom Learning Resource Probes Q: Which of the following is NOT a land in Magic Kingdom? A) Adventureland B) Fantasyland C) World Showcase D) Tomorrowland Bloom’s Taxonomy
- 35. Example: produce a probe that assesses a micro-objective Text Video Audio Web Link Dozens of Question Types Compare and contrast Epcot and Magic Kingdom Learning Resource Probes Q: Which of the following is a feature at Epcot and not Magic Kingdom? A) Food and Wine festival B) Dark rides C) Coasters D) Themed dining Draw connection among ideas Bloom’s Taxonomy
- 36. Your turn: think about what resource you would use to teach the micro-objective What content is ideal for teaching the micro-objective? Video, image, article, etc? Text Video Audio Web Link Dozens of Questions Types Micro Learning Objective Learning Resource Probes
- 37. Example: think about what resource you would use to teach the micro-objective Ex: YouTube Videos of rides Ex: Park maps Ex: Park blogs Text Video Audio Web Link Dozens of Questions Types Compare and contrast Epcot Center and Magic Kingdom Learning Resource Probes
- 38. What does this mean at the organizational level?
- 39. Adaptive learning unlocks organizational performance 39 Measurement Mastery Efficiency Engagement Agility
- 40. Learners take ownership of their learning RECHARGE 0% 0% 0% 0%
- 41. Trainers and managers make learning data actionable through reports 41
- 42. Authors and subject matter experts can continually refine content 42©2017 McGraw-Hill Education. Confidential and proprietary. Not for redistribution. Authors see real-time data on the effectiveness of content and questions Learners can offer feedback 70%
- 43. Benefits for every stakeholder • Eliminates course versioning • Real-time feedback for agile authoring LEARNER • Measurable outcomes for reporting • Improved efficiency and retention • Direct savings in cost to train • A personalized experience • Self-paced and easy- to-use • 100% mastery AUTHOR INSTRUCTOR/MANAGER
- 44. Adaptive learning unlocks organizational performance 44 Measurement Mastery Efficiency Engage ment Agility Advanced Analytics Trends Strengths Opportunities Proficiency Organizational Readiness Time to Train Redistributed Investment Direct Opex Savings Productivity Risk Avoidance Retention Personalized Paths Experience Reduced Versioning Real-time Revisions Feedback Measurement Mastery Efficiency Engagement Agility
- 45. Case Study | ROI Each learner can achieve mastery at his or her own pace. Case Study | Tracking Time to Completion Learner 45 All learners must demonstrate mastery to complete the program of study Immediate ROI 32% FTE/hrs recovery
- 46. Case Study | ROI Each learner can achieve mastery at his or her own pace. Case Study | Tracking Time to Completion Learner 46 All learners must demonstrate mastery to complete the program of study Immediate ROI 32% FTE/hrs recovery
- 47. MHE Improvement across all applications Safety Sales TechnicalLeadership Learning Science Platforms
- 48. MHE adaptive leverages investment in science and technology $175M+ per Year in Digital Platforms 2012 DPG Formed 2017 Organic investment 450 Engineers, etc 200 Enginee rs, etc $ 1,600+ Adaptive products 4,000 Authors trained to use MHE Adaptive 5,000,000 Learners using MHE Adaptive 10,000,000,000 Data Layer Interactions MHE Adaptive Acquisition User Knowledge
- 49. We exist to unlock the full potential of every learner 49 Questions? Write to me at zach.posner@mheducation.com