APPLICATION OF PRINCIPAL COMPONENT ANALYSIS METHOD ON TUTOR PERFORMANCE ASSESSMENT INSTRUMENTS WITH JEFFREYS'S AMAZING STATISTICS PROGRAM FORMULA

A. Ahmad
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Abstract

Producing tutor performance appraisal instruments is a practical step to improve the quality of human resources and the quality of non-formal education units. This instrument development research aims to produce a standard instrument for assessing tutor performance by involving 250 tutors as respondents when conducting an empirical test by filling in 33 questions representing 11 variables. Data on instrument filling was then analyzed using the formula of Jeffreys's Amazing Statistics Program (JASP) version 16.3. After the instrument met the requirements of factor analysis, an analysis was carried out using the PCA method the results in general the tutor performance assessment instrument had formed eleven main components with various sub-variables of each component such as seven sub-variables, three sub-variables, two sub-variables and one sub variable with matrix values. high correlation, so that the tutor's performance assessment instrument is suitable to be used to assess the tutor's performance.
主成分分析法在导师绩效评估工具上的应用与jeffreys惊人统计程式公式
制作导师绩效评估工具是提高人力资源质量和非正规教育单位质量的一个切实可行的步骤。本工具开发研究以250名教师为调查对象,通过填写33个问题代表11个变量进行实证检验,旨在产生一个标准的教师绩效评估工具。然后使用Jeffreys's Amazing Statistics Program (JASP) 16.3版的公式分析仪器填充数据。在达到因子分析的要求后,采用主成分分析法进行分析,结果总体上辅导员绩效评估工具形成了11个主成分,每个成分有7个子变量、3个子变量、2个子变量和1个子变量,每个子变量有矩阵值。相关性高,因此导师绩效评估工具适合用于评估导师绩效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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