Slide 1: 2008
Quantiative Analysis of Learning Object Repositories
Xavier Ochoa, ESPOL, Ecuador Erik Duval, KULeuven, Belgium
Slide 2: Thanks for being here
Slide 3: Slides at...
http://www.slideshare.net/xaoch
Slide 4: Agenda
• What we currently (don’t) know • Quantitative Studies and Implications
– Size – Growth – Contribution – Reuse
• Conclusions
Slide 5: Learning Object Economy
Market Makers
Producers
Market
Consumers
Policy Makers
Slide 6: Learning Object Economy
Market Makers
Producers
LOR (Market)
Consumers
Policy Makers
Slide 7: Learning Object Economy
Market Makers
Producers
LOR (Market)
Consumers
Policy Makers
Slide 8: How many objects are published? How do they grow? Which percentage is reused? How much does a user publish? Does the granularity affect reuse?
Slide 9: Quantitative Analysis
• What we measured (example)
– Repositories (ARIADNE) – Referatories (MERLOT) – OpenCourseWare (MIT OCW) – Learning Management Systems (Moodle) – Institutional Repositories (Georgia Tech)
Slide 10: Repository Size
• Power Law – unequal distribution
Slide 11: Repository Size
Repository
Referatory
OCW
LMS
IR
Slide 12: Repository Size - Implications
• Interoperability is necessary • LMS / OCW are as big as LOR(P/F) • A course uses around 10 to 50 LOs
Slide 13: Growth in Objects
• Growth is Linear (Bi-phase linear)
Slide 14: Growth in Objects - Implications
• Our current strategy is not working! • All repositories go through 2 phases:
– Initial, slow growth (1-3 first years) – Mature, faster growth
• OCW and LMS grow 1 course per day!
Slide 15: Growth in Contributors
• Some are Exponential !
Slide 16: Growth in Contributors – Impl.
• We are not retaining our contributors • LMS and OCW seem to attract more contributors • There is a hope!
Slide 17: Objects per Contributor
• Heavy-tailed distributions (no bell curve)
LORP - LORF Lotka “fat-tail”
Slide 18: Objects per Contributor
• Heavy-tailed distributions (no bell curve)
OCW - LMS Weibull “fat-belly”
Slide 19: Objects per Contributor
• Heavy-tailed distributions (no bell curve)
IR Extreme Lotka “light-head”
Slide 20: Objects per Contributor – Impl.
There is no such thing as an “average user”
Slide 21: Low
Middle
High
Slide 22: Engagement is the key
Slide 23: Enagement is the key
LMSs are the best type of Repository!!!
Slide 24: Percentage of Reuse
• 3 LO collections of different granularity:
– Components in Slides in ARIADNE – Modules in Connexions – Courses at ESPOL
• Compared with:
– Images in Wikipedia articles – Software Libraries in Freshmeat – Web APIs in Mashups
Slide 25: Percentage of Reuse
20% of Learning Objects in a collection are reused at least once
Slide 26: Percentage of Reuse
20% of Learning Objects in a collection are reused at least once NO MATTER THEIR GRANULARITY! We have to re-think the Reuse Paradox
Slide 27: Reuses per Object
• Log-Normal (also heavy-tailed)
Slide 28: Reuses per Object – Impl.
Reuse seems to be the result of a chain of successful events
Slide 29: Reuse vs. Popularity
Slide 30: What’s Next
• Apply to other Learning Object “Markets” • Continue analysis of reuse • Other aspects: creation, updating, use...
Slide 31: Conclusions
• We can gain a lot of knowledge with some simple measurements • This knowledge benefits
– Market Makers – Policy Makers
• We call this “Learnometrics” • Only way to know if we are moving forward
Slide 32: Real, Real Conclusion
MESURE
(and let us help / let us know)
Slide 33: Danke, questions?
Xavier Ochoa – xavier@cti.espol.edu.ec Erik Duval – Erik.Duval@cs.kuleuven.be
