1. 1 Pearson Research John T. Behrens,Ph.D. Pearson Center for Digital Data, Analytics, & Adaptive Learning 12 September, 2012

2. Agenda Me The centers My Center Two things we think about Copyright © 2010 Pearson Education, Inc. or its affiliates. All rights reserved.2

3. Pearson Research & Innovation Network 3

4. Foci of the Center 4 Digital Data Games & New Genre Big Data and Data Policy Analytics Communication Visualization Data Mining & Statistics Adaptive Learning Modeling Recommendation Adaptation Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

5. Three Epistemic Frames of the Center 5 Not just re-doing, but re- thinking Digitally Motivated Statistics, Psychology, Computing, Policy, HCI, etc Multi- disciplinary Comprehensive framework and language Extensible ECD centric Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

6. Four goals Research Communication Product Vision Capacity Building in Company and Field 6 Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

7. 7 How does a small center have big impact? Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

8. Idea 1

9. Consider the data presented by Anscombe (1973): Y-mean = 7.5, sd=2.03 X-mean = 9, sd = 3.3 Slope =.5 with intercept of 3 Correlation of r =.83 Picture the data in your mind (or otherwise if you philosophically object to “ mind ” )

10. If you think the data look like this, then you are right

11. or, if you think the data look like this, then you are right

14. All of these patterns have the same algebraic summaries, but dramatically different data patterns!

15. Conclusion 1 Algebraic summaries lie, so we need to use graphics!

16. Now, consider this small set of numbers which we may see in quiz scores. 1,1,2,2,3,3,4,4,5,5,5,5,6,6,6,6,6,6,7,7,7,7, 8,8,9,9,10,10,11,11 Lets see how graphics can help.

17. Here is a histogram of the data: Notice the structure of slight skew that we could not see in the listing of data.

18. Bin width = 1 Bin width = 2 Some more histograms of the same data

19. Bin width = 1.5, intervals start at 1. Bin width = 2, intervals start at 1. Even more histograms of the same data

20. Which is the real picture of the data?

21. Evolving Communication Framework 21 Communication Perception Language of graphics Background of audience Intended Message or range Cultural / Background variation Measurement Argument Nature of Scaling Measurement Error Sampling Error Data Sampling Scheme CAT Method Test Blue Print Amount of data Grainsize of data Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

22. Idea 2

23. A general adaptivity loop Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved. 23 Combine observations & Update Profile If A and B then activity = Z Give Activity& Collect WP Look at Profile and choose Activity Identify features & make observations X1 X2 X3 X4 Xn If A and B then X1 = 1 If C then X2 = “P”

24. CAT (in item paradigm) Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved. 24 Combine scores & Update Profile Give Item & Collect Answer Look at Profile and choose Activity Identify correctness & make score X1 X2 X3 X4 Xn If A and B then X1 = 1 If C then X2 = “P”

25. The Practice Tutor Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved. 25 Combine observations & Update Profile (To move in ZPD) Give Activity & Collect Work Look at Profile and choose Activity Identify features & make observation X1 X2 X3 X4 Xn If A and B then X1 = 1 If C then X2 = “P”

26. The Game Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved. 26 Combine observations & Update Profile (To Maximize Motivation) Give Activity & Collect Work Look at Profile and choose Activity Identify features & make observation X1 X2 X3 X4 Xn If A and B then X1 = 1 If C then X2 = “P”

27. Wouldn’t it be interesting To work at a company that did all these things?

28. Your Life in the Digital Ocean Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved. 28 Combine observations & Update Profile (To Maximize Whatever is needed) Give Activity & Collect Work Look at Profile and choose Activity Identify features & make observation X1 X2 X3 X4 Xn If A and B then X1 = 1 If C then X2 = “P”

29. Digital DesertDigital Ocean Disconnected intrusionsOngoing ubiquitous data Small samples of dataDramatically large and ubiquitous Special intrusive systems to get data Data built into daily activity Lack of data requires special focused inputs “Items” no longer exist Absence of data requires inferential stretch Availability of data lessons need for inference Data scarcity leads to small sample science (e.g models of expertise) Data ocean leads to improved understanding of detailed mechanisms & rules (automated automated scoring) “Exam” ignorant of your state Activity starts with access to previous history Data outside classroom not even considered Data is data no matter where it is Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

30. And what will this do for current concepts and boundaries? Curriculum and Assessment? Games and instruction? Games and assessment? Formal and informal? Formative and Summative? Schooling and Education In school / out of school Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

31. And perhaps more important… SummativeAutopsy FormativeCheck up Embedded Ubiquitous Unobtrusive Stealth Invisible Heart Monitor Copyright © 2012 Pearson Education, Inc. or its affiliates. Al rights reserved.

32. Say the summary here 32

33. Thanks! 33