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Autor/inn/enRoberts , Amy M.; LoCasale-Crouch, Jennifer; Hamre, Bridget K.; Buckrop, Jordan M.
TitelAdapting for Scalability: Automating the Video Assessment of Instructional Learning
QuelleIn: Online Learning, 21 (2017) 1, S.257-272 (16 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationWeitere Informationen
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1939-5256
SchlagwörterVideo Technology; Scoring; Automation; Computer Assisted Testing; Scores; Correlation; Technology Uses in Education; Educational Technology; Online Courses; Observation; Teacher Student Relationship; Randomized Controlled Trials; Preschool Teachers; Faculty Development; Surveys; Pretests Posttests
AbstractAlthough scalable programs, such as online courses, have the potential to reach broad audiences, they may pose challenges to evaluating learners' knowledge and skills. Automated scoring offers a possible solution. In the current paper, we describe the process of creating and testing an automated means of scoring a validated measure of teachers' observational skills, known as the Video Assessment of Instructional Learning (VAIL). Findings show that automated VAIL scores were consistently correlated with scores assigned by the hand scoring system. In addition, the automated VAIL replicated intervention effects found in the hand scoring system. The automated scoring technique appears to offer an efficient and reliable assessment. This study may offer additional insight into how to utilize similar techniques in other large-scale programs and interventions. (As Provided).
AnmerkungenOnline Learning Consortium, Inc. P.O. Box 1238, Newburyport, MA 01950. Tel: 888-898-6209; Fax: 888-898-6209; e-mail: olj@onlinelearning-c.org; Web site: http://onlinelearningconsortium.org/read/online-learning-journal/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2022/4/11
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