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Journals / Eurasian Journal of Educational Research / 2018 / Cilt: 76 - Sayı: 76

Analytical Weighting Scoring for Physics Multiple Correct Items to Improve the Accuracy of Students’ Ability Assessment

Wasis -
Bastari -
Mundilarto -
Atik Wintarti
Pages
187–202
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Implications for Research and Practice: It is recommended that the assessment of physics ability using multiple-correct items on a large scale can apply the analytical weighting scoring based on the complexity of the content and a penalty system.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Purpose: This is a developmental research study that aims to develop a model of polytomous scoring based-on weighting for multiple correct items in the subject of physics.
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Key Findings & Data:The multiple correct items used have 3–4 options.
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Conclusion & Impact:Implications for Research and Practice: It is recommended that the assessment of physics ability using multiple-correct items on a large scale can apply the analytical weighting scoring based on the complexity of the content and a penalty system.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Purpose: This is a developmental research study that aims to develop a model of polytomous scoring based-on weighting for multiple correct items in the subject of physics. Weighting was analytically applied based on question complexity and imposed penalties on wrong answers. Research Methods: Within the development model, Fenrich's development cycle, consisting of analysis, planning, design, development, implementation, evaluation, and revision, was selected throughout the cycle. The multiple correct items used have 3–4 options. The items were implemented to 140 upper secondary school students and 410 first-year undergraduate students. The students’ physics ability was analyzed using the Quest program, and the results of dichotomous and polytomous scoring were compared. Findings: The results of this study showed that the analytical weighting scoring based on a complexity and penalty system on the developed assessment items generated a higher number of scoring level categories (three to seven categories) than that of dichotomous scoring (only two categories), estimated students’ physics abilities more accurately and in greater detail, had an approximate distribution closer to the normal distribution, and produced a standard deviation smaller than that of dichotomous scoring. Thus, the analytical weighting scoring for multiple correct items in this study was able to produce a more accurate estimation of physics ability than those using dichotomous scoring. Implications for Research and Practice: It is recommended that the assessment of physics ability using multiple-correct items on a large scale can apply the analytical weighting scoring based on the complexity of the content and a penalty system.

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Cite This Article

-, W., -, B., -, M., Wintarti, A. (2022). Analytical Weighting Scoring for Physics Multiple Correct Items to Improve the Accuracy of Students’ Ability Assessment. Eurasian Journal of Educational Research, Cilt: 76 - Sayı: 76, 187–202. https://ajindex.com/articles/507173

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References (12)

  1. Adams, R.J., & Khoo, S.T. (1996). Quest (Computer software). The interactive test analysis system. Victoria: Acer. Adeyemo, S. A. (2010). Students’ ability level and their competence in problem-solving task in physics. International Journal of Educational Research and Technology, 1(2), 35 – 47. Ali, S. H., Carr, P. A., & Ruit, K. G. (2016). Validity and reliability of scores obtained on multiple-choice questions: Why functioning distractors matter. Journal of the Scholarship of Teaching and Learning, 16 (1), 1-14.
  2. Baghaei, P., & Dourakhshan, A. (2016). Properties of single-response and double-response multiple-choice grammar items. International Journal of Language Testing, 6 (1), 33-49.
  3. Baker, J.G., Rounds, J.B., & Zeron, M.A. (2000). A comparison of graded response and rasch partial credit models with subjective well-being. Journal of Educational and Behavioral Statistic, 25(3), 253-270.
  4. Bishara, A. J., & Lanzo, L. A. (2015). All of the above: When multiple correct response options enhance the testing effect. Journal Memory, 23(7), 1013-1028.
  5. Bush, M. (2015). Reducing the need for guesswork in multiple-choice tests. Assessment & Evaluation in Higher Education, 40(2), 218-231.
  6. Bond, T. G., & Fox, C. M. (2007). Applying the rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah: Lawrence Erlbaum Associates, Publishers.
  7. Donoghue, J. R. (2005). An empirical examination of the IRT information of polythomously scored reading items under the generalized PCM. Journal of Educational Measurement, 31(4), 295-311.
  8. Emaikwu, S. O. (2015). Recent issues in the construction and scoring of multiple-choice items in examinations. The International Journal of Humanities & Social Studies. 3(6), 201-207.
  9. Fenrich, P. (2004). Instructional design tips for virtually teaching practical skills. In Proceedings of the 2004 Informing Science and IT Education Joint Conference. Rockhampton, Australia June 25–28, 2004.
  10. Frisbie, D.A. (1992). The multiple true-false format: A status review. Educational Measurement: Issues and Practice, 11(4), 21-26
  11. Grunert, M. L., Raker, J. R., Murphy, K. L., & Holme, T. A. (2013). Polytomous versus dichotomous scoring on multiple-choice examinations: development of a rubric for rating partial credit. Journal of Chemical Education, 90(10), 1310-1315.
  12. Haladyna, T.M., Downing, S.M., & Rodriguez, M.C. (2002). A review of multiple choice item-writing guidelines for classroom assessment. Applied Measurement in Education, 15 (3), 309-334.