OWL: A Recommender System for Organization-Wide Learning.
Frank N. Linton, Deborah Joy, Hans-Peter Schaefer, Andrew Charron · 2000
We describe the use of a recommender system to enable continuous knowledge acquisition and individualized tutoring of application software across an organization. Installing such systems will result in the capture of evolving expertise and in organization-wide learning (OWL). We present the results of a year-long naturalistic inquiry into an application's usage patterns, based on logging users' actions. We analyze the data to develop user models, individualized expert models, and instructional indicators. We show how this information is used to recommend learning tips to users. Keywords Recommender system, organization-wide learning, OWL, individualized instruction, agent, instrumentation, logging. Introduction New Workplace Technologies Enable New Learning Methods In the last decade, an enormous change has taken place in the workplace: there is a PC on every desk, and much office work is performed in the medium of software. Mastering one's software - at least the portion of...