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Library assessment on a budget Using effect size meta‐analysis to get the most out of the library‐related survey data available across campus

Library assessment on a budget Using effect size meta‐analysis to get the most out of the... Purpose – Colleges and universities conduct regular surveys that provide space for local questions, including library‐related items. Unfortunately these surveys often use incomparable metrics and scales. This study seeks to examine techniques to take advantage of such surveys to supply practical results. Design/methodology/approach – Effect size meta‐analysis is a statistical method used to combine such disparate results. This method and other statistical tools were used to extract significant findings from the survey results, looking at such library constructs as physical access, analysis (the ability to determine information quality and relevance), collection quality and quantity, retrieval, hours and staff. Findings – The paper describes the meta‐analysis of three separate surveys which contained library‐related data responses, and conclusions subsequently drawn from that analysis. Research limitations/implications – This paper assumes that the reader possesses some understanding of basic statistical concepts, such as means, variance, standardized scores, and null hypothesis significance testing (NHST). It assumes a “good‐enough” approach to library assessment, one that strives for the greatest possible statistical accuracy, reliability, and validity given the time and resource limitations within which most academic libraries operate. Originality/value – The method provides a practical, sustainable, and effective library assessment technique using data from Radford University. The use of freeware to undertake the analysis also makes it financially viable. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Performance Measurement and Metrics Emerald Publishing

Library assessment on a budget Using effect size meta‐analysis to get the most out of the library‐related survey data available across campus

Eric Ackermann
Performance Measurement and Metrics , Volume 9 (3): 10 – Oct 31, 2008
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Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
1467-8047
DOI
10.1108/14678040810928417
Publisher site
See Article on Publisher Site

Abstract

Purpose – Colleges and universities conduct regular surveys that provide space for local questions, including library‐related items. Unfortunately these surveys often use incomparable metrics and scales. This study seeks to examine techniques to take advantage of such surveys to supply practical results. Design/methodology/approach – Effect size meta‐analysis is a statistical method used to combine such disparate results. This method and other statistical tools were used to extract significant findings from the survey results, looking at such library constructs as physical access, analysis (the ability to determine information quality and relevance), collection quality and quantity, retrieval, hours and staff. Findings – The paper describes the meta‐analysis of three separate surveys which contained library‐related data responses, and conclusions subsequently drawn from that analysis. Research limitations/implications – This paper assumes that the reader possesses some understanding of basic statistical concepts, such as means, variance, standardized scores, and null hypothesis significance testing (NHST). It assumes a “good‐enough” approach to library assessment, one that strives for the greatest possible statistical accuracy, reliability, and validity given the time and resource limitations within which most academic libraries operate. Originality/value – The method provides a practical, sustainable, and effective library assessment technique using data from Radford University. The use of freeware to undertake the analysis also makes it financially viable.

Journal

Performance Measurement and Metrics – Emerald Publishing

Published: Oct 31, 2008

Keywords: Academic libraries; User studies; Statistical analysis

References

  • Statistical Power Analysis for the Behavioral Sciences
    Cohen, J.
  • Synthesizing Research: A Guide for Literature Reviews
    Cooper, H.
  • A primer on understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions
    Cumming, G.; Finch, S.
  • Inference by eye: confidence intervals and how to read pictures of data
    Cumming, G.; Finch, S.
  • Replication and researcher's understanding of confidence intervals and standard error bars
    Cumming, G.; Williams, J.; Fidler, F.
  • d to U 3 Statistical Calculator for Windows
    Decoster, J.; Leistico, A.A.
  • ClinTools Software for Windows: Version 3.5
    Devilly, G.J.
  • Effect Sizes for Research, A Broad Practical Approach
    Grissom, R.J.; Kim, J.J.
  • Higher Education Research Institute Faculty Survey
    Higher Education Research Institute (HERI)
  • Methods of Meta‐analysis, Correcting Error and Bias in Research Findings
    Hunter, J.E.; Schmidt, F.L.
  • Beyond Significance Testing, Reforming Data Analysis Methods in Behavioral Research
    Kline, R.
  • The National Survey of Student Engagement: Conceptual Framework and Overview of Psychometric Properties
    Kuh, G.D.
  • Practical Meta‐analysis
    Lipsey, M.W.; Wilson, D.B.
  • Surveys and Experiments in Education Research
    McNamara, J.
  • NSSE 2005 Institutional Report (Sample)
    National Survey of Student Engagement (NSSE)
  • Survey Research
    Office of Academic Assessment
  • Using effect size in NSSE survey reporting
    Springer, R.
  • Questionnaire Survey Research, What Works
    Suskie, L.A.
  • Foundations of Behavioral Statistics: An Insight‐based Approach
    Thompson, B.