DATA CENTRIC EDUCATION & LEARNING
Seung Won Yoon, Ph.D. firstname.lastname@example.org
Instructional Design & Technology, Western Illinois University
Project & Case Examples
Technology in Education: Past
Now and Future
Strategies first, then technologies.
If great people/tool vs. bad culture/system, latter wins.
Most technology integration has failed. Innovation adoption
has been tough. Workshop or training to (big) data/analytics
will always have minimal impacts.
Learning and performance must be integrated.
Technologies in the Past
Technologies in education
Process: Instructional design, learning strategy, 4C/ID (for complex
contents), learning environments, design based research, etc.
Media: radio, TV, CBT, video, PC, multimedia, Web, virtual worlds, …
now, analytics & network analysis (paradigm change? Anything new?)
Education: Industry lowest in adopting technologies
People will always focus more on new media
Media vs. methods debate
New technology has never replaced ‘old’
Present & Future
NMC Horizon report
Near: MOOC and Tablet computing
Middle: Learning analytics & gaming
Far: 3D printing & wearable technology
A day made of glass
by Amber Case, from Flick’r
What’s New about Data-centric Learning?
Tablet, phone, devices connected to the cloud
Real-time feedback (pacing)
Adaptive contents (individualization)
Instructional precision/effectiveness (previous knowledge)
Analyzed and used to augment teacher/student capabilities
Watters. A. (2011, July). How data and analytics will change education.
Data-centric Education & Learning
LMS: grade, log, forum postings
Web 2.0/3.0 – digital trails
Top 100 learning tools – more data
Data sources (in addition to social media):
PSLC’s learning datasets
Carnegie Melon University
Stanford’s multimodal learning analytics
Stanford’s large network data collection
Society for Learning Analytics Research datasets
Nodes, edges, density, centrality, community, motif
Data: Affiliation matrix, edge list
Project & Case Examples
Use of SNAPP (Moodle, BlackBoard, D2L, Angel)
At risk students/non-participants
Before and after new strategy (e.g., each post vs. responding to
LATF at U of Michigan: Cross-course analysis - Time on tasks,
frequency of contacts, network position, resource use, instructor
reuse of contents, learning-reflecting assessments, contextual
resources (privacy, security, governance)
Bakharia, A., & Dawson, S. (2011). SNAPP: A bird’s eye view of temporal participant interaction
Predictive analytics at American Public Universities
1 mil students, 5 mil courses, 16 schools
Cho, Y. J. and colleagues. (2012). Landscape of educational technology. BJET.
Leadership and programs
Co-authorship & collaboration
In the Workplace
IBM’s Knowledge creation & sharing
Encouraging strategic collaboration, before & after
Learning must take place in the context of work or performing
Learning & Performance Architecture
Rosenberg, M. (2006). Beyond E-Learning: Approaches and technologies to enhance
organizational knowledge, learning, and performance. New York: Pfeiffer.
Yoon, S. W., & Lim, D. H. (2007). Strategic blending: A conceptual framework to improve learning and performance. International Journal on E-Le
Yoon, S. W., & Lim, D. H. (2007). Strategic blending: A conceptual framework to improve learning and
performance. International Journal on E-Learning, 6(3), 475-489.
Yoon, S. W., & Lim, D. H. (2010). Virtual learning and technologies for managing organizational
competency and talents. Advances in Developing Human Resources, 12(6), 715-728.
Van Tiem, D. M., Moseley, J. L. & Dessinger, J. C. (2012). Fundamentals of Performance Improvement: A
guide to optimizing results through people, process, and organizations
Learning & Knowledge at Macro Level
Figure 1. Esterby-Smith’s (2003) Key Topics of Learning in Organizations
Song J.H., Uhm, D., Yoon, S. W. (2011). Organizational knowledge creation practice., LODJ.
Interactions & Others
PBL, PJL, AL – Activity Theory
4C/ID, Learning environment
Figure. Activity Theory (Engeström, 2000)
Figure. Online interactions (Hirumi, 2002)
It’s not about if (big) data/analytics is different;
it’s about doing the right thing & doing things right
Must be treated as the same as business intelligence
Tools & frameworks are here, are you ready?