概括性理论在2019年贝宁大都市WAEC数学客观考试测量误差中的应用

Kennedy Imasuen, Praise Kehinde Adeosun
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摘要

运用概括性理论对2019年WAEC高中考试的测量误差进行了研究。本研究运用概率论对2019年高中WAEC数学客观考试中的测量误差进行了识别和分析,并确定了学生、项目和教师三个方面对测量误差的最大贡献。提出了四个研究问题来指导研究。本研究采用随机效应双面全交叉s×t×i设计,进行概括性(G)和决策性(D)研究。在2019/2020学年期间,贝宁大都市的七十五所公立中学共有五万六千七百九十七名(5697)高中三年级(SS3)学生。数据收集的工具是一个50(50)的选择题WAEC,数学2019考试。该文书已由西非考试委员会(WAEC)验证。采用库德-理查德森20 (KR - 20)量表来确定项目的信度,以获得内部一致性。它的值为0.92。采用EduG version 6.0-e软件进行方差分析(ANOVA)和概括性分析。研究结果表明:对考试成绩测量误差贡献最大的是学生-教师互动,占68.9%,其次是学生因素(27.5%)和残差,即学生,教师和项目的互动(3.6%)。当教师人数增加到78人时,得到了0.97的归纳系数,足以根据学生的相对考试能力进行排序。因此,根据研究结果,建议研究人员、测试开发人员和检查机构应进行通用性分析,以减少或消除测量误差,从而最大限度地提高可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Generalizability Theory in Measurement Error in 2019 WAEC Mathematics Objective Examination in Benin Metropolis
: This study investigated measurement error in 2019 WAEC senior secondary school examination using generalizability theory. The study was specifically concerned with identifying and analyzing measurement error in the senior secondary school 2019 WAEC mathematics objective examination using generalizability theory, and also to determine the highest contribution of facets: students, items and teachers to measurement error. Four research questions were raised to guide the study. The study was survey which adopted a random effect two-facet fully crossed s×t×i design for a generalizability (G) and decision (D) studies. The population consisted of fifty-six thousand, seven hundred and ninety-seven (5697) senior secondary three (SS3) students in the seventy-five (75) public secondary schools in Benin metropolis for the 2019/2020 academic session. The instrument for data collection was a fifty (50) multiple choice WAEC, mathematics 2019 examination. The instrument has been validated by the West African Examination Council (WAEC). The reliability of the items was ascertained using the Kuder – Richardson 20 (KR 20) to obtain internal consistency. It gave a value of 0.92. Data collected were analyzed using a software EduG version 6.0-e based on analysis of variance (ANOVA) and generalizability. The findings which emerged from the study were: the highest contribution to measurement error in examination scores was the students - teacher interaction which accounted for 68.9%, this was followed by the student factor (27.5%) and the residual, that is, interaction of student, teachers and items (3.6%). A generalizability coefficient of 0.97 high enough to rank order students according to their relative abilities in examinations was obtained when the number of teachers was increased to 78. Based on the findings, it was therefore recommended that generalizability analysis should be carried out by researchers, test developers and examination bodies so as to reduce or eliminate measurement error and hence maximize reliability.
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