Number of found records: 19
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COOK, Coleen; HEATH, Fred; THOMPSON, Bruce |
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A New Culture of Assessment: Preliminary Report on the ARL SERVQUAL Survey |
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IFLA Council and General Conference, No. 66, 2000. |
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On line ( 15/06/2004) |
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Texas A&M University and the Association of Research Libraries (ARL) under the New Measures initiative is engaged in a project to evaluate service quality in research libraries using an augmented SERVQUAL instrument. In spring 2000, 13 ARL libraries in North America invited a random sample of students and faculty to take the survey through the web. The pilot project evaluates the efficacy of web-based survey instruments, and the augmented SERVQUAL protocol will be tested for its usefulness in measuring service quality from the user perspective in research libraries. The project plan will be discussed, and preliminary results reported from the administration of the survey to selected ARL libraries in spring 2000 (AU) |
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Servqual; total quality; services assessment; LibQual+ |
Assessment |
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MARGARET, A.; WINKER, M.D. |
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The Need for Concrete Improvement in Abstract Quality |
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JAMA, 1999. |
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On line ( 15/06/2004) |
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Presentation of the concept abstract, its structure, its criteria for quality and elements of improvement |
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Abstract; criteria; quality; evaluation
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Assessment |
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MORSE, Emile L. |
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Evaluation Methodologies for Information Management Systems |
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On line ( 15/06/2004) |
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The projects developed under the auspices of the Defense Advanced Research Projects Agency (DARPA) Information Management (IM) program are innovative approaches to tackle the hard problems associated with delivering critical information in a timely fashion to decision makers. To the extent that each of the information management systems interfaces with users, these systems must undergo testing with actual humans. The DARPA IM Evaluation project has developed an evaluation methodology that can assist system developers in assessing the usability and utility of their systems. The key components of an evaluation plan are data, users, tasks and metrics. The DARPA IM Evaluation project involved six IM project Principal Investigators (PI's) who devoted a year's effort toward developing a method for getting beyond exploring and implementing systems to actually planning and performing structured, hypothesis-based evaluations of those systems. Five IM projects participated in this effort while a sixth IM project was integrated into and evaluated within a larger effort. This article describes component systems, evaluation (AU) |
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DARPA; evaluation; information management system |
Assessment |
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PINTO, María |
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Data representation factors and dimension from the quality function deployment (QFD) perspective. |
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Journal of information Science, 2006, vol.32, n.2, pp.116-130 |
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In order to optimize access to the increasing amount of information, a classic solution has been data representation. The aim of this research is to uncover and systematize the factors and dimensions involved in the data representation issue and more exactly in the planning and design of the information products (IP) and their previous representation processes (RP). QFD (quality function deployment) is a planning tool based on user needs and expectations - quality functions - allowing the planning and design of IPs and RPs. A series of linked deployments provides the implied factors and dimensions: IP planning factors-representing, relating, filtering and seeking relevant information; IP design_dimensions-relevance, format, comprehensiveness, consistency, accuracy and currentness; RP planning factors-comprehension, synthesizing, structuring and selecting; and RP design dimensions - human resources, computers and tangibles. By means of these deployments, the analysis of the factors and dimensions and their corresponding relationships provides an excellent picture for the quality planning and design of information products and representation processes. (AU) |
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abstracting quality; data quality; data representation; information quality; quality function deployment; representation processes; total data quality management |
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