Development of Questionnaire to Evaluate Students’ Perception about Real and Virtual Refutational Laboratory: A Rasch Measurement Approach

Andi Moh Amin, A. Suhandi, Ridwan Efendi
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Abstract

This study aims to develop the questionnaire of students’ perception about the real and virtual refutational laboratory which is a misconception remediation method adapted from refutation text using a new approach i.e., laboratory. This study was a quantitative description that involved 53 students (12 males and 41 females) chosen using purposive sampling. The students were initially given a trial questionnaire after receiving a misconception remediation treatment using a real and virtual laboratory method in different classes. The validity and reliability of the instrument were analyzed using Rasch Model. The analysis result reveals that the Cronbach's alpha was 0.61 (enough category), the item reliability was 0.82 (good category) and the person reliability was 0.31 (less variance in students' answers). Meanwhile, based on the validity test, the raw variance was obtained from measures of 29.4% reaching the minimum criteria range of 20%. The Differential Item Function (DIF) test based on gender results revealed that an item was biased (p=0.0435), whereas, there is no biased instrument based on the kind of class in the Differential Item Function test study. The analysis demonstrates that after correcting and deleting some items that did not match based on its criteria, this instrument may be used to gather information on students’ perception regarding the implementation of laboratory learning methods or the like in a valid and reliable way by the researchers and teachers.
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学生对真实和虚拟反驳实验室认知的问卷开发:一种Rasch测量方法
本研究旨在开发学生对真实和虚拟反驳实验室的认知问卷,这是一种基于反驳文本的误解纠正方法,采用了一种新的方法,即实验室。本研究采用有目的抽样的方法,选取53名学生(男12名,女41名)进行定量描述。学生们在不同的班级接受了真实和虚拟实验室方法的误解纠正治疗后,首先获得了一份试用问卷。采用Rasch模型对仪器的效度和信度进行了分析。分析结果显示,Cronbach's alpha为0.61(足够类别),项目信度为0.82(良好类别),个人信度为0.31(学生答案方差较小)。同时,根据效度检验,原始方差为29.4%,达到20%的最小标准范围。基于性别的差异项目函数(DIF)检验结果显示一个项目有偏倚(p=0.0435),而在差异项目函数检验研究中,没有基于类别的偏倚工具。分析表明,在根据其标准纠正和删除一些不匹配的项目后,研究人员和教师可以使用该工具有效可靠地收集学生对实施实验室学习方法等的感知信息。
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