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In higher education levels of resource provision are becoming increasingly important. Within this context academic libraries are required to evaluate their services and ensure that they meet the needs of users. Sensitivity to customer requirements must be extended to include different categories of customer and in light of the changing composition of the student population, serving the needs of part time students should be a priority for academic librarians. The aim of this study was to evaluate the levels of satisfaction with library facilities among part time students in the University of Ulster at Jordanstown (UUJ). A postal questionnaire was administered to two hundred part time students within the Faculty of Business and Management obtaining a response rate of 45%. Factor analysis was used to identify factors underpinning user satisfaction. These reflected two general dimensions of staff and facilities. A clear trend emerged suggesting that part time students rated satisfaction with staff more highly than satisfaction with facilities. Significance testing concluded that there were no differences in levels of satisfaction between regular and irregular users of the library. Clearly further research is needed in the area but this study indicates that efforts at improvement should be directed primarily in the direction of facilities to raise part time students’ satisfaction. 相似文献
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Noreen M. Webb Joan L. Herman Beverly Cabello 《Journal of Educational Measurement》1987,24(2):119-130
This paper describes a four-step approach to constructing diagnostic test profiles that provide precise but practical information on students' instructional needs. The approach is based on the specification and analysis of a domain and uses generalizability theory to determine which skills within the domain need to be assessed to diagnose gaps in students' skills and to estimate score profiles. A 64-item test of pronoun use was constructed to represent 32 categories of usage defined by different combinations of five factors in the domain. Generalizability analyses were conducted to determine the optimal number of categories to be included in students' profiles and the number of items needed for each category, and to produce univariate and multivariate estimates of students' universe scores. Multivariate profiles of universe scores were the most accurate and differed substantially from observed score and univariate universe score profiles. 相似文献
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