Quantiative Analysis of Learning Object Repositories Xavier Ochoa, ESPOL, Ecuador Erik Duval, KULeuven, Belgium 2008

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Slides at... http://www.slideshare.net/xaoch

http://www.slideshare.net/xaoch

Agenda What we currently (don’t) know Quantitative Studies and Implications Size Growth Contribution Reuse Conclusions

What we currently (don’t) know

Quantitative Studies and Implications

Size

Growth

Contribution

Reuse

Conclusions

Learning Object Economy Market Makers Producers Consumers Policy Makers Market

Learning Object Economy Market Makers Producers Consumers Policy Makers LOR (Market)

Learning Object Economy Market Makers Producers Consumers Policy Makers LOR (Market)

How many objects are published? How do they grow? Which percentage is reused? How much does a user publish? Does the granularity affect reuse?

Quantitative Analysis What we measured (example) Repositories (ARIADNE) Referatories (MERLOT) OpenCourseWare (MIT OCW) Learning Management Systems (Moodle) Institutional Repositories (Georgia Tech)

What we measured (example)

Repositories (ARIADNE)

Referatories (MERLOT)

OpenCourseWare (MIT OCW)

Learning Management Systems (Moodle)

Institutional Repositories (Georgia Tech)

Repository Size Power Law – unequal distribution

Power Law – unequal distribution

Repository Size Repository Referatory OCW LMS IR

Repository Size - Implications Interoperability is necessary LMS / OCW are as big as LOR(P/F) A course uses around 10 to 50 LOs

Interoperability is necessary

LMS / OCW are as big as LOR(P/F)

A course uses around 10 to 50 LOs

Growth in Objects Growth is Linear  (Bi-phase linear)

Growth is Linear  (Bi-phase linear)

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!

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!

Growth in Contributors Some are Exponential  !

Some are Exponential  !

Growth in Contributors – Impl. We are not retaining our contributors LMS and OCW seem to attract more contributors There is a hope!

We are not retaining our contributors

LMS and OCW seem to attract more contributors

There is a hope!

Objects per Contributor Heavy-tailed distributions (no bell curve) LORP - LORF Lotka “ fat-tail”

Heavy-tailed distributions (no bell curve)

Objects per Contributor Heavy-tailed distributions (no bell curve) OCW - LMS Weibull “ fat-belly”

Heavy-tailed distributions (no bell curve)

Objects per Contributor Heavy-tailed distributions (no bell curve) IR Extreme Lotka “ light-head”

Heavy-tailed distributions (no bell curve)

Objects per Contributor – Impl. There is no such thing as an “average user ”

Low Middle High

Engagement is the key

Enagement is the key LMSs are the best type of Repository!!!

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

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

Percentage of Reuse 20% of Learning Objects in a collection are reused at least once

20% of Learning Objects in a collection

are reused at least once

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

20% of Learning Objects in a collection

are reused at least once

NO MATTER THEIR GRANULARITY!

We have to re-think the Reuse Paradox

Reuses per Object Log-Normal (also heavy-tailed)

Log-Normal (also heavy-tailed)

Reuses per Object – Impl. Reuse seems to be the result of a chain of successful events

Reuse seems to be the result of a chain of successful events

Reuse vs. Popularity

What’s Next Apply to other Learning Object “Markets” Continue analysis of reuse Other aspects: creation, updating, use...

Apply to other Learning Object “Markets”

Continue analysis of reuse

Other aspects: creation, updating, use...

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

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

MESURE (and let us help / let us know) Real, Real Conclusion

Danke, questions? Xavier Ochoa – [email_address] Erik Duval – [email_address]