Pea, R. (2012, April 15). The promise of learning about learning with adaptive educational technologies. Invited paper for symposium: "Global Perspectives on New Technologies and Learning" of the World Educational Research Association (Eva Baker, Chair). Annual Meetings of the American Educational Research Association, Vancouver BC, Canada.

1. The Promise of Learning about
Learning with Adaptive
Educational Technologies
Roy Pea
Stanford University
AERA 2012, April 15
Pea, R. (2012, April 15). The promise of learning about learning with adaptive educational technologies. Invited paper for
symposium: "Global Perspectives on New Technologies and Learning" of the World Educational Research Association (Eva
Baker, Chair). Annual Meetings of the American Educational Research Association, Vancouver BC, Canada.

2. http://fednet.net/nae120111/

3. Context
• What research opportunities are possible using these
data?
• What kinds of analyses have researchers conducted
using such data and what has been learned?
• What more is needed to develop research in this
area?
• What are the costs and benefits of using such data
for research?
• What kind of organizational supports would be
needed from developers if data were used for
research and program improvement?
• What other accommodations might be needed for
researchers (e.g., to ensure confidentiality of data,
allow data to be processed statistically, etc.)?

4. Examples

5. How can such
technologies become
trusted metacognitive
resources, providing
valuable feedback and
guidance to learners,
teachers, and other
stakeholders?

6. (1) By expanding
learner profile meta-data

7. (2) By expanding
our data sources for
inferences about
learning and its
conditions

8. • Greater
contextualization of
learning

9. • Capturing learner-
perceptible aspects of
environments

10. • Capturing uses of
written language and
other symbolic systems

11. (3) By expanding
our sense-making
techniques for gauging
learning and its
conditions

12. (4) By expanding access
to our learner data
systems to the learner

13. (5) By expanding learner
access to data about
their own performances
in relation to others

14. (6) By providing large-
scale testbeds to do
experimentation in
comparative pedagogy

15. • To refine theories of
learning progressions

16. • To theorize about more
and less effective forms of
feedback and guidance
during learning activities
for different learner profiles
and contexts

17. • To explore how to exploit
social networks of learners to
build social capital for
learning