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  • 标题:Adapting for Scalability: Automating the Video Assessment of Instructional Learning
  • 本地全文:下载
  • 作者:Amy M Roberts ; Jennifer LoCasale-Crouch ; Bridget K Hamre
  • 期刊名称:Online Learning
  • 印刷版ISSN:2472-5749
  • 电子版ISSN:2472-5730
  • 出版年度:2017
  • 卷号:21
  • 期号:1
  • 页码:257-272
  • DOI:10.24059/olj.v21i1.961
  • 出版社:Online Learning Consortium
  • 摘要:Although 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.
  • 关键词:automated assessment; scalability; teacher education
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