Understanding, predicting and optimizing
learning with Learning Analytics
Jingyan Lu, The University of Hong Kong
July 5th...
Assessment in the Education Triangle
Instruction Assessment
Curriculum
7/6/2013Jingyan Lu@hku
2
Assessment triangle
Observation Interpretation
Cognition
Pellegrino, J. W., Chudowsky, N., & Glaser, R. (Eds.). (2002). Kn...
Conceptual Integration of Learning
Analytics and Assessment
Instruction Assessment
Curriculum
Observation Interpretation
C...
Contribution of measurement
and statistical modeling in
Assessment
7/6/2013Jingyan Lu@hku
5
Assessment models
X = T + E
Argumentative
Representation
Structure
Justification
Position
Conceptual Clarification
Conclus...
Conceptual Assessment Framework:
Evidence Center Assessment Design (ECD)
Mislevey, R. J., Steinberg, L. S., Almond, R. G.,...
Assessment in the 21st Century
Classroom
 “This evidence-based approach (Mislevy et al,
2003) is particularly relevant in...
Applications--Where
 Online Learning Systems - online courses or
learning software or interactive environments that
use i...
Application of LA—Predictive
Models in Instructional System
 When are students ready to move onto the next topic?
 When ...
Typical
Adaptive
Learning
System
Predictive
nature of
LA
7/6/2013Jingyan Lu@hku
11
Why are we measuring (1):
Modeling and theory building
User knowledge modeling
User behavior modeling
User experience mode...
Examples of interactive
learning environments
Khan Academy
7/6/2013Jingyan Lu@hku
13
Stakeholders
ADAPTIVE
LEARNING
SYSTEM
7/6/2013Jingyan Lu@hku
14
Some Examples
7/6/2013Jingyan Lu@hku
15
Examples (1): Online
learning behavior
7/6/2013Jingyan Lu@hku
16
What are we measuring on
LMS: Student model
 How peer assessment
affect learning
Lu, J., & Zhang, Z. (2012). Understandin...
Where do we measure it: Task
model
 Peer assessment
 Feedback
 Grading
7/6/2013Jingyan Lu@hku
18
How do we measure: Evidence
model
 Online behavior
 Log data
 Activities
 Content
7/6/2013Jingyan Lu@hku
19
Example 2: Modeling online
critical reading
7/6/2013Jingyan Lu@hku
20
Student Model
 Critical reading behavior
 Critical reading and writing argument
7/6/2013Jingyan Lu@hku
21
Task Model
DiigoOASIS
7/6/2013Jingyan Lu@hku
22
Evidence Model
 Understanding online
reading behavior
 Building up model from
Reading to writing
7/6/2013Jingyan Lu@hku
...
Thank You
jingyan@hku.hk
7/6/2013Jingyan Lu@hku
24
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Understanding, predicting and optimizing learning with Learning Analytics

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Author: Jingyan Lu, The University of Hong Kong
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Understanding, predicting and optimizing learning with Learning Analytics

  1. 1. Understanding, predicting and optimizing learning with Learning Analytics Jingyan Lu, The University of Hong Kong July 5th, LASI-Hong Kong 7/6/2013Jingyan Lu@hku 1
  2. 2. Assessment in the Education Triangle Instruction Assessment Curriculum 7/6/2013Jingyan Lu@hku 2
  3. 3. Assessment triangle Observation Interpretation Cognition Pellegrino, J. W., Chudowsky, N., & Glaser, R. (Eds.). (2002). Knowing what students know: The science and design of educational assessment. Washington, DC: National Academy Press. 7/6/2013Jingyan Lu@hku 3
  4. 4. Conceptual Integration of Learning Analytics and Assessment Instruction Assessment Curriculum Observation Interpretation Cognition 7/6/2013Jingyan Lu@hku 4
  5. 5. Contribution of measurement and statistical modeling in Assessment 7/6/2013Jingyan Lu@hku 5
  6. 6. Assessment models X = T + E Argumentative Representation Structure Justification Position Conceptual Clarification Conclusion Multiple Perspectives Identify Stakeholder Number of Stakeholder Types of Stakeholder Matching Citing Case Information Outside Information Explanation 7/6/2013Jingyan Lu@hku 6
  7. 7. Conceptual Assessment Framework: Evidence Center Assessment Design (ECD) Mislevey, R. J., Steinberg, L. S., Almond, R. G., Haertel, G. D., & Penuel, W. R. (2001). Leverage points for improving education assessment. Princeton: Educational testing Service. 7/6/2013Jingyan Lu@hku 7
  8. 8. Assessment in the 21st Century Classroom  “This evidence-based approach (Mislevy et al, 2003) is particularly relevant in the 21st century technology rich classroom where student’s use of technology tools for learning create a multitude of data (e.g., artefacts, log data) which can be mined, assessed, and presented in ways that students and teachers can interpret it to support learning.”  Hansen & Wasson (forthcoming) Hansen, C. & Wasson, B. (forthcoming). Formaive e-assessment in the 21st century Classroom. NEAR, Iceland, March 7/6/2013Jingyan Lu@hku 8
  9. 9. Applications--Where  Online Learning Systems - online courses or learning software or interactive environments that use intelligent tutoring systems, virtual labs, or simulations, such as Moodle.  Why: Big data 7/6/2013Jingyan Lu@hku 9
  10. 10. Application of LA—Predictive Models in Instructional System  When are students ready to move onto the next topic?  When are students falling behind in a course?  When is a student at risk for not completing a course?  What grade is a student likely to get without intervention?  What is the best next course for a given student?  Should a student be referred to a counselor for help? 7/6/2013Jingyan Lu@hku 10
  11. 11. Typical Adaptive Learning System Predictive nature of LA 7/6/2013Jingyan Lu@hku 11
  12. 12. Why are we measuring (1): Modeling and theory building User knowledge modeling User behavior modeling User experience modeling User Profiling Domain Modeling 7/6/2013Jingyan Lu@hku 12
  13. 13. Examples of interactive learning environments Khan Academy 7/6/2013Jingyan Lu@hku 13
  14. 14. Stakeholders ADAPTIVE LEARNING SYSTEM 7/6/2013Jingyan Lu@hku 14
  15. 15. Some Examples 7/6/2013Jingyan Lu@hku 15
  16. 16. Examples (1): Online learning behavior 7/6/2013Jingyan Lu@hku 16
  17. 17. What are we measuring on LMS: Student model  How peer assessment affect learning Lu, J., & Zhang, Z. (2012). Understanding the effectiveness of online peer assessment: A path model. Journal of Educational Computing Research, 46(3), 313-333. 7/6/2013Jingyan Lu@hku 17
  18. 18. Where do we measure it: Task model  Peer assessment  Feedback  Grading 7/6/2013Jingyan Lu@hku 18
  19. 19. How do we measure: Evidence model  Online behavior  Log data  Activities  Content 7/6/2013Jingyan Lu@hku 19
  20. 20. Example 2: Modeling online critical reading 7/6/2013Jingyan Lu@hku 20
  21. 21. Student Model  Critical reading behavior  Critical reading and writing argument 7/6/2013Jingyan Lu@hku 21
  22. 22. Task Model DiigoOASIS 7/6/2013Jingyan Lu@hku 22
  23. 23. Evidence Model  Understanding online reading behavior  Building up model from Reading to writing 7/6/2013Jingyan Lu@hku 23
  24. 24. Thank You jingyan@hku.hk 7/6/2013Jingyan Lu@hku 24

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