Person fit statistics to identify irrational response patterns for multiple-choice tests in learning evaluation

doi:10.47750/pegegog.12.04.05

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…This is an important note considering that the abilities of students in all schools are not at the same level. Therefore, test questions prepared by teachers must be able to facilitate various levels of student ability [46], [47].…”

Section: Figure 1 Kmo and Bartlett's Testmentioning

confidence: 99%

Item Analysis of High School Specialization Mathematics Exam Questions With Item Response Theory Approach

Arriza,

Retnawati,

Ayuni

2024

BAREKENG: J. Math. & App.

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Analysis of item characteristics on test instruments is carried out to determine high-quality items. This study aims to describe the parameters of specialized high school mathematics test items using the IRT approach. It is an exploratory descriptive study employing a quantitative approach. The research subjects were 36 students of grade XI high school who took the specialization mathematics subject. Response data with dichotomous scoring were analyzed using the IRT approach with the R program to obtain information about item parameters and student ability. The results of the model fit test showed that most of the specialization mathematics exam items fit the Rasch model. The results showed that all items met the criteria of good quality because they had good difficulty parameters. Relatively, the test items were suitable for students with abilities between -2.6 and 2.8 logits. This estimation is also supported by the TIF with a maximum value of 3.049 at 0.08 logit ability and SEM of 0.541. Test items that have been proven to be of high quality can be used as examples in both teaching and diagnostic assessments. Further research could consider the discrimination parameter when analyzing the characteristics of the questions.

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Section: Figure 1 Kmo and Bartlett's Testmentioning

confidence: 99%

Item Analysis of High School Specialization Mathematics Exam Questions With Item Response Theory Approach

Arriza,

Retnawati,

Ayuni

2024

BAREKENG: J. Math. & App.

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The Effect of Learning Method and Self-Confidence on Student Learning Outcomes

Awaludin,

Ruhiat,

Anriani

et al. 2024

IJORER Int. J. Recent Educ. Res.

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Objective: This study examines the disparities in enhancing student learning outcomes based on learning methods and varying levels of student self-confidence, categorized as high, medium, and low. Method: This study employs quantitative methodologies utilizing quasi-experimental methods. The study uses a non-equivalent control group technique and follows a 2 x 3 two-way ANOVA factorial design. The study sample comprised 1000 students enrolled at the health Polytechnic Banten, an educational institution in Indonesia. The enormity of this scale requires the study to be divided into many portions due to the significant temporal and financial resources needed. Therefore, a sample size of 10.00% of the population was chosen. In addition, the researchers utilized a systematic random sampling method to determine the number of students involved in the study. Results: The research findings can be classified into three main areas. Firstly, there were significant differences in student learning outcomes between those taught using STEM learning methods and those who received bedside teaching. Secondly, variations in student self-confidence levels (high, medium, and low) also resulted in differences in learning outcomes. Lastly, an interaction was observed between the learning methods and the levels of student self-confidence, which influenced the overall learning outcomes as measured by the average pre-test and post-test scores and questionnaires. Novelty: The novelty of this research was variations from previous research in terms of emphasis, subject, results, and combination of research variables. Previous research only concentrated on STEM methods and self-confidence to improve student learning outcomes. Previous research only examined one research variable: STEM, bedside teaching method, and self-confidence.

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Person fit statistics to identify irrational response patterns for multiple-choice tests in learning evaluation

Cited by 2 publications

References 30 publications

Item Analysis of High School Specialization Mathematics Exam Questions With Item Response Theory Approach

Item Analysis of High School Specialization Mathematics Exam Questions With Item Response Theory Approach

The Effect of Learning Method and Self-Confidence on Student Learning Outcomes

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