Use of contextualized attention metadata for ranking and recommending learning objects

Xavier Ochoa, Erik Duval

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The tools used to search and find Learning Objects in different systems do not provide a meaningful and scalable way to rank or recommend learning material. This work propose and detail the use of Contextual Attention Metadata, gathered from the different tools used in the lifecycle of the Learning Object, to create ranking and recommending metrics to improve the user experience. Four types of metrics are detailed: Link Analysis Ranking, Similarity Recommendation, Personalized Ranking and Contextual Recommendation. While designed for Learning Objects, it is shown that these metrics could also be applied to rank and recommend other types of reusable components like software libraries.

Original languageEnglish (US)
Title of host publicationCIKM 2006 Workshop - Proceedings of CAMA 2006
Subtitle of host publication1st International ACM Workshop on Contextualized Attention Metadata: Collecting, Managing and Exploiting of Rich Usage Information
Pages9-15
Number of pages7
DOIs
StatePublished - 2006
EventCAMA 2006: International Workshop on Contextualized Attention Metadata: Collection, Management and Analysis of Rich Usage Information Conference on Information and Knowledge Management, held in conjunction with the ACM 15th Conference on Information - Arlington, VA, United States
Duration: Nov 10 2006Nov 11 2006

Publication series

NameProceedings of CAMA 2006: 1st International ACM Workshop on Contextualized Attention Metadata: Collecting, Managing and Exploiting of Rich Usage Information

Other

OtherCAMA 2006: International Workshop on Contextualized Attention Metadata: Collection, Management and Analysis of Rich Usage Information Conference on Information and Knowledge Management, held in conjunction with the ACM 15th Conference on Information
CountryUnited States
CityArlington, VA
Period11/10/0611/11/06

Keywords

  • Attention metadata
  • Learning objects
  • Ranking
  • Recommending

ASJC Scopus subject areas

  • Information Systems
  • Software

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  • Cite this

    Ochoa, X., & Duval, E. (2006). Use of contextualized attention metadata for ranking and recommending learning objects. In CIKM 2006 Workshop - Proceedings of CAMA 2006: 1st International ACM Workshop on Contextualized Attention Metadata: Collecting, Managing and Exploiting of Rich Usage Information (pp. 9-15). (Proceedings of CAMA 2006: 1st International ACM Workshop on Contextualized Attention Metadata: Collecting, Managing and Exploiting of Rich Usage Information). https://doi.org/10.1145/1183604.1183608