使用Rasch模型分析的大规模开放网络课程(MOOC)简化可靠的在线论文测试阅卷

M. N. Mamat, Zawawi Temyati, Siti Fatahiyah Mahamood, Hanifah Musa
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引用次数: 1

摘要

正式考试中的手工练习并不能准确评估学生的能力,因为它只是计算学生成绩中要考虑的每一道题的分数。有许多教育工作者使用原始分数作为衡量学生能力的一种形式,但它从来没有真正衡量正确的标准。原始的分数应该被转换成正确的线性指标来衡量能力。该程序包括准确测量学生在LOGIT单元中的能力得分,提供学生的成绩概况,以及测量测试集和学生答案的可靠性。该程序是为大规模开放在线学习和无纸化论文测试而设计的,这更难分析。这个程序将学生的答案转换成基于分数比例的量表,以便更准确地测量。这绝对比仅仅分析每道题的原始分数的常见做法要好。它将显示真实学生在代表真实学生能力(LOGIT单位)的认知表现(测试)中的表现,以便准确地衡量正确的结果。这种新的评估模式适用于大量的在线学生。它采用了Raschmodel,为学生提供了准确的能力评分,并为学生的答案提供了科学的可靠性评分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simplified Reliable Online Essay Test Marking for Massive Open Online Course (MOOC) using Rasch Model Analysis
Manual practice in formal examination does not assess accurate measureof a student’s ability, as it merely counts the score of every question to beconsidered for the student’s grade. There are many educators who haveused raw score as a form of measurement for a student’s ability, but it nevertruly measures the right measurement. The raw score should be convertedinto the right linear metrics for ability measurement. This procedurecontains measuring score of accurate student’s ability in LOGIT unit,providing of student’s result profile, and measuring reliability of the testset and the student’s answers. The procedure is designed for massive openonline learning and paperless essay-based test which is more difficult tobe analysed. This procedure converts the student’s answer into rubricalratio-based scale to be more accurately measured. It is definitely better thanthe common practice of merely analysis on raw marks for each question.It would show true student’s performance of cognitive performance (test)which represents the true student’s ability (in LOGIT unit), in order toaccurately measure the right outcome. This new paradigm of assessmentis fit to be applied for massive numbers on online students. It uses Raschmodel which offers reliable solution in producing accurate ability marksfor students, together with scientific reliability score for student’s answer.
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