Assessing the Psychometric Qualities of the Data-Informed School Leadership Survey

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  • Author(s): Jingping Sun (ORCID Jingping Sun (ORCID 0000-0002-7671-0792); Jiangang Xia (ORCID Jiangang Xia (ORCID 0000-0002-6486-8613); Cheng Hua; Kaiwen Man; Bob L. Johnson
  • Language:
    English
  • Source:
    Educational Administration Quarterly. 2024 60(4):531-580.
  • Publication Date:
    2024
  • Document Type:
    Journal Articles
    Reports - Research
    Tests/Questionnaires
  • Additional Information
    • Availability:
      SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: [email protected]; Web site: https://sagepub.com
    • Peer Reviewed:
      Y
    • Source:
      50
    • Education Level:
      Junior High Schools
      Middle Schools
      Secondary Education
    • Subject Terms:
      Psychometrics; Data Use; Leadership; Surveys; School Administration; Measurement; Reliability; Validity; Teacher Collaboration; Teaching Methods; Measures (Individuals); Public Schools; Evaluation; Middle Schools; Teacher Attitudes
    • Subject Terms:
      Alabama
    • Accession Number:
      10.1177/0013161X241271250
    • ISSN:
      0013-161X
      1552-3519
    • Abstract:
      Purpose: There is little consensus in the literature regarding a) what it means for a school leader to lead with data, and b) how to measure data-informed leadership in a reliable and valid way. This study examines the psychometric properties of an operational measure intended to assess the extent to which a school leader is a data-informed school leader. The measurement invariance, reliabilities and construct and predictive validities of the "Data-Informed School Leadership Survey" (DISL Survey) are assessed using various psychometric statistical techniques. Methods: Using data collected from 155 teachers from 7 public schools in a southern state, the following psychometric statistics used to address our purpose: the Many-Facet Rasch (MFR) Model, Bayesian second-order Confirmatory Factor Analysis (CFA), Bayesian Structural Equation Modeling--Multiple Indicators, Multiple Causes analysis (Bayesian SEM-MIMIC), and reliability analysis. Findings: Results show an adequate fit from all MFR, Bayesian CFA, and MIMIC models and a high reliability (Cronbach [alpha] = 0.98). The DISL Survey instrument exhibits sound psychometric properties. Results likewise confirm the value of using MFR modeling and Bayesian methods to examine the psychometric properties of DISL Survey as a means of improving educational leadership measures. Implications for Research and Practice: Data from this study confirm the validity and reliability of the "Data-Informed School Leadership Survey" (DISL Survey) as an instrument to assess the strengths and weaknesses of Data-Informed School Leadership (DISL) and as a means for providing feedback for improving such leadership. Heretofore a measure for assessing this leadership was non-existent.
    • Abstract:
      As Provided
    • Publication Date:
      2024
    • Accession Number:
      EJ1440162