relevance ranking of learning objects

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Relevance Ranking Metrics for Learning Objects Xavier Ochoa, ESPOL, Ecuador Erik Duval, KULeuven, Belgium

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Presentation at EC-TEL 2007 (Crete). The need for relevance rank is presented and basic metrics are presented and evaluated.

TRANSCRIPT

Page 1: Relevance Ranking of Learning Objects

Relevance Ranking Metrics for Learning Objects

Xavier Ochoa, ESPOL, Ecuador

Erik Duval, KULeuven, Belgium

Page 2: Relevance Ranking of Learning Objects

Agenda

• Why Relevance Ranking?

• What is Relevance?

• Relevance Ranking Metrics

• Do they work?

• What is next?

Page 3: Relevance Ranking of Learning Objects

Economy of Abundance

Page 4: Relevance Ranking of Learning Objects

Economy of Abundance

Put your LMS here!

Page 5: Relevance Ranking of Learning Objects

Why Relevance Ranking?

Abundance

=

Difficult to find most relevant

Page 6: Relevance Ranking of Learning Objects

Why Relevance Ranking?

Abundance

=

Difficult to find most relevant

Solution:Do it the Google way

Page 7: Relevance Ranking of Learning Objects

Why Relevance Ranking?

Abundance

=

Difficult to find most relevant

Relevance RankingMEANINGFUL & SCALABLE

Page 8: Relevance Ranking of Learning Objects

How we do it now?

• Manual rating:–Meaningful but not Scalable

• Text based Ranking Algorithms:–Scalable but not Meaningful

Page 9: Relevance Ranking of Learning Objects

What is Relevance?

Page 10: Relevance Ranking of Learning Objects

Relevance Ranking Metrics

Relevance Ranking

Relevance Ranking

MetricB

MetricA

MetricC

Context

Page 11: Relevance Ranking of Learning Objects

Relevance Ranking Metrics

Relevance Ranking

Relevance Ranking

MetricB

MetricA

MetricC

Context

Meaningful

Page 12: Relevance Ranking of Learning Objects

Relevance Ranking Metrics

Relevance Ranking

Relevance Ranking

MetricB

MetricA

MetricC

Context

Scalable

Page 13: Relevance Ranking of Learning Objects

Topi

cal R

elev

ance

Page 14: Relevance Ranking of Learning Objects

Personal Relevance

Page 15: Relevance Ranking of Learning Objects

Situational Relevance

Page 16: Relevance Ranking of Learning Objects

Do they work?

• Exploratory Study– 10 users (8 Prof. and 2 R.A.)– MIT OCW learning objects (34,640 LO)– Search and Select Objects to create 10

lessons (10 different topics on CS)– Web application was used

Page 17: Relevance Ranking of Learning Objects
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Ranking the Rankings

• Baseline Rank: TF-IDF similarity algorithm

• Re-rank according to Basic Metrics

• All rankings compared with manual relevance ranking

• Kendall Tau was used to measure similaritiy between lists

Page 21: Relevance Ranking of Learning Objects

Results

Page 22: Relevance Ranking of Learning Objects

Basic Topical Relevance MetricTrees

Page 23: Relevance Ranking of Learning Objects

Basic Personal Relevance Metric

Net.

Page 24: Relevance Ranking of Learning Objects

Basic Situational Relevance Metric

XML

Page 25: Relevance Ranking of Learning Objects

Linear Combination

Page 26: Relevance Ranking of Learning Objects

Linear Combination

Page 27: Relevance Ranking of Learning Objects

Results

• Even basic metrics improve the ranking

• Linear Combination should be learnt

• Limited (and Synthetic) Study!

Page 28: Relevance Ranking of Learning Objects

What is next?

• Implementation in ARIADNE NEXT

• Capture user behavior and learn from it for 3 months

• Natural (Real) evaluation of the metrics

• Develop BETTER metrics

Page 29: Relevance Ranking of Learning Objects

Conclusions

• Meaningful and Scalable metrics are possible

• Cheap to implement • Provide significant improvement• While not optimal, they could be

use as a base-line for further research

Page 30: Relevance Ranking of Learning Objects

Thank You! Dank U! Gracias!• Questions, Comments, Critics…

are all welcome!!

Xavier [email protected]

http://www.cti.espol.edu.ec/xavier

Erik [email protected] http://www.cs.kuleuven.ac.be/~erikd