使用机构数据预测教师候选人在认证考试中的表现

Q4 Social Sciences

Journal of Assessment and Institutional Effectiveness Pub Date : 2018-12-07 DOI:10.5325/JASSEINSTEFFE.7.1-2.0001

L. Clark, Julia Kara-Soteriou, Michael P. Alfano

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引用次数: 2

摘要

摘要:本研究采用了一个持续质量框架，重点是关闭评估循环并指导干预过程。使用学生的学习成绩数据，应用逻辑回归模型来预测在认证考试，阅读基础测试中的成功。数据分析显示，通过考试的几率受到学生的SAT总分、平均绩点和必修阅读教学课程成绩的影响。该模型的结果使学校能够识别并主动为有风险的学生提供学术干预。关键词:教师资格考试，阅读基础，预测模型，学术干预，机构数据

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Using Institutional Data to Predict Teacher Candidate Performance on a Certification Exam

Abstract:This study employed a continuous quality framework with an emphasis on closing the assessment loop and guiding an intervention process for teacher certification candidates at a master's-level regional institution. Using student academic performance data, a logistic regression model was applied to predict success on a certification exam, the Foundations of Reading Test. Data analysis revealed that the odds of passing this exam were influenced by students' SAT total scores, grade point average, and grade in a required reading instruction course. The results of this model allow the institution to identify and proactively provide academic intervention to at-risk students. Keywords: Teacher certification exam, foundations of reading, predictive model, academic interventions, institutional data

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来源期刊

Journal of Assessment and Institutional Effectiveness Social Sciences-Education

CiteScore

0.30

自引率

0.00%

发文量

期刊介绍： The Journal of Assessment and Institutional Effectiveness publishes scholarly work on the assessment of student learning at the course, program, institutional, and multi-institutional levels as well as more broadly focused scholarship on institutional effectiveness in relation to mission and emerging directions in higher education assessment. JAIE is the official publication of the New England Educational Assessment Network, established in 1995 and recognized as one of the leaders in supporting best practices and resources in educational assessment.