Approaches to Teaching and Learning Information Retrieval



TITLE: Approaches to Teaching and Learning Information Retrieval




Efthimis N. Efthimiadis

The Information School, University of Washington, Seattle, WA, USA


Juan Manuel Fernandez Luna, Departamento de Ciencias de la Computacn

Inteligencia Artificial, Universidad de Granada, Spain


Juan Huete

Departamento de Ciencias de la Computaci?n e Inteligencia Artificial,

Universidad de Granada, Spain


Andrew MacFarlane

Dept. Of Information Science,  City University, London, UK


Proposal Submission Deadline:             September 15, 2009

Author Notification:                      October 15, 2009

Full Chapters Due:                        March 1, 2010



Web search is part of our daily lives, and this has made understanding of the Information Retrieval (IR) principles paramount to many professions that were not previously concerned with search and its associated activities.  System builders, information scientists, human computer interactions specialists, librarians, educators in K-12, scientists, information architecture designers, IP lawyers, advertisers and retailers in e-Commerce, to name a few professions are involved in building and running search systems.


Consequently, the Teaching and Learning of IR is changing in nature. It is being practiced in many different forms, so that it satisfies the separate needs in those fields that makeup the field search as we know it today.



This book will aim to coordinate and integrate the current thinking of teaching and learning IR.  It will focus on both educational and domain-specific research and practice and how that reaches the learners.



Planned book sections include, but are not limited to, the following:

A.  Technical Levels (non-technical to highly technical)

B.  Educational Goals:

         discipline specific (CS, LIS, CL, MIS)

         by domain or search task

         search (Web, DL, .)


C.  Teaching and Learning Methods:


         e-learning (distance/online learning)

         use of IR systems for teaching

D.  Assessment and Feedback

E.  Curricula


The above levels are to be examined in the broadly defined IR areas that include and are not limited to:

         Advertising and IR

         Data Mining and IR

         e-Commerce and IR

         Evaluation (user-centered or system focused)

         Log analysis / web analytics

         Natural Language Processing and IR

         Personalization / Recommendation

         Search Engine Optimization

         Structured data (XML) and IR



The target audience of this book will be composed of educators, professionals, and researchers working in the fields of information retrieval, information studies, information science, information management, knowledge management, computer-supported cooperative work and human-computer interaction.



Potential contributors are invited to submit a 2-5 page chapter proposal to the Editors by September 15, 2009. Authors will be notified by October 15, 2009 about the status of their proposals and sent chapter guidelines. Full chapters should be at least 8,000-9,000 words in length and are due by March 1, 2010.



Inquiries and submissions can be forwarded electronically to the editors listed above.


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