Student perspectives on personalized account-based recommender systems in libraries

Hahn, James F.

Permalink

https://hdl.handle.net/2142/103995 Copy

Description

Title

Student perspectives on personalized account-based recommender systems in libraries

Author(s)

Hahn, James F.

Issue Date

2019-06-12

Keyword(s)

• personalization
• recommender systems
• academic libraries
• research libraries
• student interviews
• interdisciplinary research
• discovery

Abstract

A personalized account-based recommender was developed in the University of Illinois Library's mobile app interface. The recommender system (RS) was derived from data mining topic clusters of items that are checked out together. Using the library mobile RS as a prompt to understand student preferences for personalized account-based RS, structured interviews were undertaken and analyzed thematically to determine RS features and functionality desired. In the interviews, students described their perceptions of RS, together with features and functionality desired. Students indicated that they desired data stewardship and sharing levels, which provided valuable input into matters of system transparency pertaining to recommendations derived algorithmically. An unexpected finding from students was growing unease with aspects of surveillance capitalism. Academic library recommenders can distinguish themselves from commercial recommenders in several ways, including increased transparency beyond what is available in commercial systems, and by attending to student privacy and data retention as a system design issue.

Publisher

NISO

Type of Resource

• text
• image

Language

en

Permalink

• https://www.niso.org/events/2019/06/discovery-and-online-search-part-one-drivers-change-online-search
• http://hdl.handle.net/2142/103995

Copyright and License Information

© Jim Hahn 2019

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