Predicting the Culturally Responsive Teacher Roles With Cultural Intelligence and Self-Efficacy Using Machine Learning Classification Algorithms

IF 0.8 4区教育学 Q3 EDUCATION & EDUCATIONAL RESEARCH

Education and Urban Society Pub Date : 2022-04-13 DOI:10.1177/00131245221087999

Kasım Karataş, Ibrahim Arpaci, Yusuf Yildirim

{"title":"Predicting the Culturally Responsive Teacher Roles With Cultural Intelligence and Self-Efficacy Using Machine Learning Classification Algorithms","authors":"Kasım Karataş, Ibrahim Arpaci, Yusuf Yildirim","doi":"10.1177/00131245221087999","DOIUrl":null,"url":null,"abstract":"This study aimed to predict the culturally responsive teacher roles based on cultural intelligence and self-efficacy using machine learning classification algorithms. The research group consists of 415 teachers from different branches. The Bayes classifier (NaiveBayes), logistic-regression (SMO), lazy-classifier (KStar), meta-classifier (LogitBoost), rule-learner (JRip), and decision-tree (J48) were employed in the assessment of the predictive model. The results indicated that JRip rule-learner had a better performance than other classifiers in predicting the culturally responsive teachers based on six attributes used in the study. The JRip rule-learner classified the culturally responsive teachers as low, medium, or high with an accuracy of 99.76% (CCI: 414/415) [Kappa statistic: 0.996, Mean Absolute Error (MAE): 0.003, Root Mean Square Error (RMSE): 0.043, Relative Absolute Error (RAE): 0.663, Relative Squared Error (RRSE): 9.244]. The results indicated that all classifiers had an acceptable performance but JRip rule-learner had a better performance than the other classifiers in predicting the culturally responsive teachers.","PeriodicalId":47248,"journal":{"name":"Education and Urban Society","volume":"55 1","pages":"674 - 697"},"PeriodicalIF":0.8000,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Education and Urban Society","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1177/00131245221087999","RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}

引用次数: 3

Abstract

This study aimed to predict the culturally responsive teacher roles based on cultural intelligence and self-efficacy using machine learning classification algorithms. The research group consists of 415 teachers from different branches. The Bayes classifier (NaiveBayes), logistic-regression (SMO), lazy-classifier (KStar), meta-classifier (LogitBoost), rule-learner (JRip), and decision-tree (J48) were employed in the assessment of the predictive model. The results indicated that JRip rule-learner had a better performance than other classifiers in predicting the culturally responsive teachers based on six attributes used in the study. The JRip rule-learner classified the culturally responsive teachers as low, medium, or high with an accuracy of 99.76% (CCI: 414/415) [Kappa statistic: 0.996, Mean Absolute Error (MAE): 0.003, Root Mean Square Error (RMSE): 0.043, Relative Absolute Error (RAE): 0.663, Relative Squared Error (RRSE): 9.244]. The results indicated that all classifiers had an acceptable performance but JRip rule-learner had a better performance than the other classifiers in predicting the culturally responsive teachers.

查看原文本刊更多论文

利用机器学习分类算法预测具有文化智能和自我效能感的文化反应型教师角色

本研究旨在使用机器学习分类算法，基于文化智力和自我效能预测文化反应型教师角色。该研究小组由来自不同分支机构的415名教师组成。贝叶斯分类器（NaiveBayes）、逻辑回归（SMO）、懒惰分类器（KStar）、元分类器（LogitBoost）、规则学习器（JRip）和决策树（J48）用于预测模型的评估。结果表明，基于研究中使用的六个属性，JRip规则学习者在预测文化反应教师方面比其他分类器有更好的表现。JRip规则学习者将文化反应型教师分为低、中、低三类，或高，准确率为99.76%（CCI:414/415）[CKappa统计量：0.996，平均绝对误差（MAE）：0.003，均方根误差（RMSE）：0.043，相对绝对误差（RAE）：0.663，相对平方误差（RRSE）：9.244]具有文化敏感性的教师。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Education and Urban Society Multiple-

CiteScore

3.00

自引率

8.30%

发文量

期刊介绍： Education and Urban Society (EUS) is a multidisciplinary journal that examines the role of education as a social institution in an increasingly urban and multicultural society. To this end, EUS publishes articles exploring the functions of educational institutions, policies, and processes in light of national concerns for improving the environment of urban schools that seek to provide equal educational opportunities for all students. EUS welcomes articles based on practice and research with an explicit urban context or component that examine the role of education from a variety of perspectives including, but not limited to, those based on empirical analyses, action research, and ethnographic perspectives as well as those that view education from philosophical, historical, policy, and/or legal points of view.lyses.