Concurrent Session 4
Streamed Session MERLOT

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Brief Abstract

Celebrating 20 years of operation, MERLOT has announced new search services including 1) the traditional MERLOT search, 2) direct access to popular digital libraries, and 3) pre-customized, profile-based WWW searches.  Results are consolidated on redesigned/unified easily filterable hitlist pages.  This presentation demonstrates how these services improve discovery of OERs. 


Barbra has been with MERLOT for over 20 years serving as a consultant, webmaster and for the past 12 years, Manager of Technical Services.
Sorel Reisman, President Emeritus of the IEEE Computer Society, Managing Director of the international, higher education consortium MERLOT.ORG, Professor of Information Systems at California State University Fullerton. Fulbright OER Specialist. Standing Committee Chair of IEEE COMPSAC Conference.

Extended Abstract

This year, MERLOT celebrates 20 years of operation.  During that time, one of MERLOT’s key strategies has been to create a repository of high quality, curated Learning Objects.  Throughout the two decades of MERLOT’s existence, Google has provided increased opportunities for users search for many different kinds of learning materials on the World Wide Web.  However, MERLOT has continued to demonstrate that search results from its exclusive, curated repository are superior to those from any generalized Google search.  Nevertheless, despite the extra work to manually filter the results of a Google search, to identify truly useful learning materials, most users continue to use the generalized Google search,

MERLOT recently announced a set of extended search services that include 1) the traditional MERLOT repository search, 2) direct access to popular Learning Object digital libraries, and 3) pre-customized, profile-based searches for Learning Objects on the World Wide Web.  The results of any or all of these kinds of searches are consolidated on redesigned unified hitlist pages, easily filterable with one click on that page.

While the first service continues to provide users with the MERLOT functionality to which they have become accustomed, the second service, which historically has been available as the so called “Federated Search,” is now more directly available to those who were less likely to see it in the past.  As well, the current implementation of this service is dramatically more efficient in terms of search times and results accuracy than it was with the previous Federated Search.

The third search service is completely new and uses the Google Custom Search Engine; we refer to this service as MERLOT’s Extended Search, and that service is based on the MERLOT team’s development of a multidimensional profile of a typical MERLOT user.  Thus, instead of returning a hit list of hundreds of thousands of hits for any particular search, i.e., the kind of hitlist that anyone would see when doing a regular Google search, the new MERLOT extended search is far more focused, and it returns fewer and more useful and more relevant hits when executed. 

One of the main differences between the traditional MERLOT repository search and the new Extended Search is that the latter does not contain any information about the quality of the hits in the hitlist.  However, any item in that hitlist can be contributed to the MERLOT repository by the searcher for subsequent editorial board review, or crowd sourced review by other MERLOT users.

This presentation will provide detailed comparative descriptions of these features demonstrating how they improve MERLOT users’ discovery of real Learning Objects.