an experimental analysis of the behaviour of a personalized case-based recommendation strategy for...
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An experimental analysis of the behaviour of a personalized case-based recommendation strategy for the learning domain
Almudena Ruiz Iniesta, Guillermo Jiménez Díaz and Mercedes Gómez Albarrán [email protected], [email protected], [email protected]
Computer Science School – Complutense University of Madrid
AcknowledgmentsSupported by: Spanish Ministry of Science and Education under grant TIN2009-13692-C03-03;
and Complutense University of Madrid and BSCH under grant 921330-1079 for consolidated Research Groups.
Experiment results: Conclusions
Research problemThe students are overwhelmed due to
the high number of educational resources in repositories.
Experimental analysis of the behaviour
Retrieve LOs that cover same or similar
concepts
Filter LOs not ready to be explored
Rank according to
the LO Quality
Retrieval step
Ranking step
Student queryStudent query
Ranked list of recommended
LOs
Ranked list of recommended
LOs
Study of the ranked list of recommended resources Pedagogical Utility for a LO, a metric that assigns
high utility values to a LO if it covers concepts in which the student has shown a low competence level
and Similarity between the concepts gathered in the
query and the concepts that a LO covers
The analysis of the expected behaviour in two dimensions: the adaptation to the student long-term learning goals
and the satisfaction of her short-term interests
The Normalized Discounted Cumulative Gain (NDCG) measures the usefulness of a result list based on the relevance and the position of the
retrieved documents and it compares the obtained gain with the ideal one
The case-based strategy obtains high values for pedagogical utility, so the
strategy proposes recommendations that satisfy the long-term learning goals.
The recommendation strategy always ensures that the proposed
LOs meet the short-term goals, because a high similarity with the
query is guaranteed.
Which one to choose?
We propose a recommendation approach for repositories of Learning Objects (LOs) that adapts to the student learning profile
Solution
Goals
How to Metrics
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DCG k iNDCG k
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