Data logging: Higher-level capturing and multi-level abstracting of user activities

Jim Helms, Dennis C. Neale, Philip L. Isenhour, John M. Carroll

Research output: Contribution to conferencePaper

5 Scopus citations

Abstract

Data logging has been a standard, but under utilized, software evaluation technique for single-user systems. Large volumes of objective data can be collected automatically and unobtrusively. This data, however, is usually in the form of low-level system events, making it difficult to analyze and interpret meaningfully. In this paper we extend traditional logging approaches to collaborative multi-user (groupware) systems. We also show how data captured at a higher level of abstraction can characterize user-system interaction more meaningfully. Lastly, we show how higher-level data abstracted from logging can be more effectively combined with data from other usability methods.

Other

OtherProceedings of the XIVth Triennial Congress of the International Ergonomics Association and 44th Annual Meeting of the Human Factors and Ergonomics Association, 'Ergonomics for the New Millennnium'
CountryUnited States
CitySan Diego, CA
Period7/29/008/4/00

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics

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    Helms, J., Neale, D. C., Isenhour, P. L., & Carroll, J. M. (2000). Data logging: Higher-level capturing and multi-level abstracting of user activities. 303-306. Paper presented at Proceedings of the XIVth Triennial Congress of the International Ergonomics Association and 44th Annual Meeting of the Human Factors and Ergonomics Association, 'Ergonomics for the New Millennnium', San Diego, CA, United States. https://doi.org/10.1177/154193120004400202