Literaturnachweis - Detailanzeige
| Autor/inn/en | An, Lily Shiao; Ho, Andrew Dean; Davis, Laurie Laughlin |
|---|---|
| Titel | Disrupted Data: Using Longitudinal Assessment Systems to Monitor Test Score Quality |
| Quelle | In: Educational Measurement: Issues and Practice, 41 (2022) 1, S.28-32 (5 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0731-1745 |
| DOI | 10.1111/emip.12491 |
| Schlagwörter | Documentation; Scores; Evaluation Methods; Longitudinal Studies; Tests; Test Items; Test Validity; Test Interpretation; Data Collection; COVID-19; Pandemics; Inferences; Correlation |
| Abstract | Technical documentation for educational tests focuses primarily on properties of individual scores at single points in time. Reliability, standard errors of measurement, item parameter estimates, fit statistics, and linking constants are standard technical features that external stakeholders use to evaluate items and individual scale scores. However, these cross-sectional, "point-in-time" features can mask threats to the validity of score interpretations, including those for aggregate scores and trends over time. We use test score data collected before and during the COVID-19 pandemic to show that longitudinal analyses, not just point-in-time analyses, are necessary to detect threats to desired inferences. We propose that educational agencies require and vendors include longitudinal data features, including "match rates" and correlations, as standard exhibits in technical documentation. (As Provided). |
| Anmerkungen | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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