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Autor/inn/enKersting, Nicole B.; Sherin, Bruce L.; Stigler, James W.
TitelAutomated Scoring of Teachers' Open-Ended Responses to Video Prompts: Bringing the Classroom-Video-Analysis Assessment to Scale
QuelleIn: Educational and Psychological Measurement, 74 (2014) 6, S.950-974 (25 Seiten)Infoseite zur Zeitschrift
PDF als Volltext (1); PDF als Volltext kostenfreie Datei (2) Verfügbarkeit 
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0013-1644
DOI10.1177/0013164414521634
SchlagwörterScoring; Automation; Video Technology; Teacher Evaluation; Pedagogical Content Knowledge; Bayesian Statistics; Comparative Analysis; Correlation; Validity; Mathematics Teachers; Classification; Interrater Reliability
AbstractIn this study, we explored the potential for machine scoring of short written responses to the Classroom-Video-Analysis (CVA) assessment, which is designed to measure teachers' usable mathematics teaching knowledge. We created naïve Bayes classifiers for CVA scales assessing three different topic areas and compared computer-generated scores to those assigned by trained raters. Using cross-validation techniques, average correlations between rater- and computer-generated total scores exceeded 0.85 for each assessment, providing some evidence for convergent validity of machine scores. These correlations remained moderate to large when we controlled for length of response. Machine scores exhibited internal consistency, which we view as a measure of reliability. Finally, correlations between machine scores and another measure of teacher knowledge were close in size to those observed for human scores, providing further evidence for the validity of machine scores. Findings from this study suggest that machine learning techniques hold promise for automating scoring of the CVA. (As Provided).
AnmerkungenSAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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