Appropriating and Assessing Heuristics for Mobile Computing

@inproceedings{citeulike:882544, abstract = {Mobile computing presents formidable challenges not only to the design of applications but also to each and every phase of the systems lifecycle. In particular, the HCI community is still struggling with the challenges that mobile computing poses to evaluation. Expert-based evaluation techniques are well known and they do enable a relatively quick and easy evaluation. Heuristic evaluation, in particular, has been widely applied and investigated, most likely due to its efficiency in detecting most of usability flaws at front of a rather limited investment of time and human resources in the evaluation. However, the capacity of expert-based techniques to capture contextual factors in mobile computing is a major concern. In this paper, we report an effort for realizing usability heuristics appropriate for mobile computing. The effort intends to capture contextual requirements while still drawing from the inexpensive and flexible nature of heuristic-based techniques. This work has been carried out in the context of a research project task geared toward developing a heuristic-based evaluation methodology for mobile computing. This paper describes the methodology that we adopted toward realizing mobile heuristics. It also reports a study that we carried out in order to assess the relevance of the realized mobile heuristics by comparing their performance with that of the standard/traditional usability heuristics. The study yielded positive results in terms of the number of usability flaws identified and the severity ranking assigned.}, address = {New York, NY, USA}, author = {Bertini, Enrico and Gabrielli, Silvia and Kimani, Stephen }, booktitle = {AVI '06: Proceedings of the Working Conference on Advanced Visual Interfaces}, citeulike-article-id = {882544}, doi = {10.1145/1133265.1133291}, isbn = {1595933530}, keywords = {heuristics, mobile}, pages = {119--126}, posted-at = {2006-10-12 10:43:11}, priority = {3}, publisher = {ACM Press}, title = {Appropriating and Assessing Heuristics for Mobile Computing}, url = {http://portal.acm.org/citation.cfm?id=1133265.1133291}, year = {2006} }

TY - CONF ID - citeulike:882544 L3 - citeulike-article-id:882544 TI - Appropriating and Assessing Heuristics for Mobile Computing T2 - AVI '06: Proceedings of the Working Conference on Advanced Visual Interfaces SP - 119 EP - 126 AD - New York, NY, USA PB - ACM Press SN - 1595933530 N2 - Mobile computing presents formidable challenges not only to the design of applications but also to each and every phase of the systems lifecycle. In particular, the HCI community is still struggling with the challenges that mobile computing poses to evaluation. Expert-based evaluation techniques are well known and they do enable a relatively quick and easy evaluation. Heuristic evaluation, in particular, has been widely applied and investigated, most likely due to its efficiency in detecting most of usability flaws at front of a rather limited investment of time and human resources in the evaluation. However, the capacity of expert-based techniques to capture contextual factors in mobile computing is a major concern. In this paper, we report an effort for realizing usability heuristics appropriate for mobile computing. The effort intends to capture contextual requirements while still drawing from the inexpensive and flexible nature of heuristic-based techniques. This work has been carried out in the context of a research project task geared toward developing a heuristic-based evaluation methodology for mobile computing. This paper describes the methodology that we adopted toward realizing mobile heuristics. It also reports a study that we carried out in order to assess the relevance of the realized mobile heuristics by comparing their performance with that of the standard/traditional usability heuristics. The study yielded positive results in terms of the number of usability flaws identified and the severity ranking assigned. KW - heuristics KW - mobile AU - Bertini, Enrico AU - Gabrielli, Silvia AU - Kimani, Stephen PY - 2006/// UR - http://portal.acm.org/citation.cfm?id=1133265.1133291 ER -