Systems Design : Information Foraging
Humanizing the process of information foraging in the Knowledge Management Centre having multiple media resources.
project Details
The problem which was considered for the application of the design process was the difficulty in locating the right resources in the KMC. It was understood that the entire search mechanism available as a software package wasn't user centric. Moreover, with the inside-user information that we already possessed, it was easy to see that user search modes differed depending upon the goal and the purpose of searching.
It was decided that there was a need to “humanize” the entire process of seeking resources in the KMC. The design process was evolved and applied, which included the design of a questionnaire for users of the KMC to gauge the principal problem areas in searching for resources. Thereafter, a list of needs and objectives that needed to be satisfied in the search mechanism was tabulated. (The process is illustrated by means of charts in the pages to come) Scenario building was studied and seven preferred scenarios were isolated. It should be noted that the user models created were based on a generic template of an individual with an elementary understanding of design terminology.
The scenarios were divided into two main categories, which included FINDING or the seeking of a resource by a user who is aware of exactly what he/she is looking for; and BROWSING which covered the user seeking a resource within a confined (but not exact) domain, or sometimes seeking an open-ended answer to a query.
The last three scenarios are concerned with creating awareness about new arrivals in the KMC, submitting reviews, and about using the assistance feature that needs to be included to guide users on how to search for whatever they are looking for, since each of the search methods described below can be very effective if used correctly.
It should be added that it would be ideal if the entire search mechanism could adapt to the user's mode of searching, rather than creating two explicit divisions as mentioned. This might be possible using artificial intelligence and predictive techniques.
The search results in all the scenarios presented below would necessarily include the following information about the resources:
- Author, title, accession no., class no., publisher, year of print, edition for BOOKS
- Author, title, year, discipline, guide for DOCUMENTS
- Artist, title, conductor, composer, instrument, genre, and media type for AUDIO
- Title, director, actors/actresses, producer, country of origin, media type, and year for VIDEO
- Genre and year for VISUALS
- Title and genre for CDROMS
- Reviews – both editorial as well as user-submitted, these could be submitted by anyone who has used the resource
- Recommendations – these could also be submitted voluntarily
- Listing of contents for books – this would prevent people from judging a resource by it's cover
- Popularity ratings – would indicate which books are borrowed or referred to the most
- Related resources – would list all associated material related to a given resource
- Relevance to different courses – would help students (and faculty) choose the right books for reference
- Contextual images of the resource – a digitized photograph of the resource (for example, the cover of the book in question), in the relevant context (in the case of books, the rack and shelf where the book is located) would be of immense help to the user in physically locating the resource in the KMC.
