Poster presented at RecSys2010

1. Personalized and diversity-aware recommendation strategies for
educational resources
Almudena Ruiz Iniesta, Mercedes Gómez Albarrán and Guillermo Jiménez Díaz
Department of Software Engineering and Artificial Intelligence – Computer Science School – Complutense University of Madrid
Motivation
The development of electronic repositories with high number of educational
resources has been intensified
Cascade Hybrid Recommender
Reactive strategy Proactive strategy
Personalization
Recommender systems support users in pre-selecting information they may be
&
interested in Case-based strategy Diversity
We propose a recommendation approach for repositories of LOs that
adapts to the student learning profile
Learning community
Collaborative strategy
opinion
Collaborative strategy
Required knowledge
Domain ontology Student profile Preference repository
 Domain concepts  The goals achieved in the learning process  Rating scores explicitly assigned by the students to each LO
 Precedence property among the concepts  Mastery level achieved in each concept  The profile that the student had when she rated the LO
Learning Objects
Cascade Hybrid Recommender
The reactive strategy: A proactive strategy that fosters diversity
combining long-term and short-term learning goals
 Diversity  Select LOs from different partitions in the
space of LOs
Student query
Retrieve LOs that
cover same or  First stage  Second stage
{if, for,…} similar concepts  Repeat until leaves are reached
Reinforce Discover
Retrieval step Filter LOs not ready
to be explored
Ranked list of
Ranking step Rank according to
recommended
the LO Quality
LOs
Collaborative strategy
 User-based nearest neighbour
 Neighbourhood formation
 candidates: students who rated the LOs proposed by the case-based recommender
 similarity between the target student profile and the profile that the neighbour had
when she rated the LO
 Rating prediction and top-k selection
Open Issues
 Recommender systems in the learning domain impose new challenges in the  Repository of LOs for Computer Programming
evaluation process
 More important to measure the impact of the recommender in the final user
 Goal-Questions Metrics method 
 Analyzing the usability of the repository
 Analyzing students’ grades
 Analyzing the impact of different recommendation strategies
 Basili VR, Rombach HD. The TAME project: towards improvement-oriented software environments. Software Engineering, IEEE
Transactions on. 1988;14(6):758-773
Acknowledgments
Supported 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.