Predicting teachers’ research reading: A machine learning approach

IF 2.3 Q1 EDUCATION & EDUCATIONAL RESEARCH
Mehrdad Yousefpoori-Naeim, Surina He, Ying Cui, Maria Cutumisu
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引用次数: 0

Abstract

In addition to pre- and in-service teacher education programmes, teachers’ autonomous reading of content related to their work contributes significantly to their professional development. This study investigated the factors that influenced the professional reading of 10,469 language teachers in the 2018 dataset of the Programme for International Student Assessment (PISA). Two machine learning models – logistic regression and Support Vector Machines (SVM) – were used to classify light and heavy readers. Nineteen variables related to teachers, including various aspects of their life, education and instructional practices, were used as predictors for classification. The results indicate that the two models had very similar accuracy scores around 65%. Moreover, the length of the reading texts that teachers assign to their students, instruction of reading comprehension strategies, and teachers’ own general reading habits were found to be the most important predictors of professional reading time.

Abstract Image

预测教师的研究性阅读:机器学习方法
除了职前和在职教师教育课程外,教师自主阅读与其工作相关的内容对其专业发展也大有裨益。本研究调查了 2018 年国际学生评估项目(PISA)数据集中 10,469 名语文教师专业阅读的影响因素。研究采用了两种机器学习模型--逻辑回归和支持向量机(SVM)--对轻阅读者和重阅读者进行分类。与教师相关的 19 个变量(包括教师生活、教育和教学实践的各个方面)被用作分类的预测因子。结果表明,两个模型的准确率非常接近,都在 65% 左右。此外,教师分配给学生的阅读文本的长度、阅读理解策略的指导以及教师自身的一般阅读习惯被认为是专业阅读时间的最重要预测因素。
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来源期刊
INTERNATIONAL REVIEW OF EDUCATION
INTERNATIONAL REVIEW OF EDUCATION EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
5.60
自引率
6.20%
发文量
45
期刊介绍: The International Review of Education – Journal of Lifelong Learning (IRE) is edited by the UNESCO Institute for Lifelong Learning, a global centre of excellence for lifelong learning and learning societies. Founded in 1955, IRE is the world’s longest-running peer-reviewed journal of comparative education, serving not only academic and research communities but, equally, high-level policy and practice readerships throughout the world. Today, IRE provides a forum for theoretically-informed and policy-relevant applied research in lifelong and life-wide learning in international and comparative contexts. Preferred topic areas include adult education, non-formal education, adult literacy, open and distance learning, vocational education and workplace learning, new access routes to formal education, lifelong learning policies, and various applications of the lifelong learning paradigm.Consistent with the mandate of UNESCO, the IRE fosters scholarly exchange on lifelong learning from all regions of the world, particularly developing and transition countries. In addition to inviting submissions from authors for its general issues, the IRE also publishes regular guest-edited special issues on key and emerging topics in lifelong learning.
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