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Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
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Yigiter, Mahmut Sami; Dogan, Nuri – Measurement: Interdisciplinary Research and Perspectives, 2023
In recent years, Computerized Multistage Testing (MST), with their versatile benefits, have found themselves a wide application in large scale assessments and have increased their popularity. The fact that forms can be made ready before the exam application, such as a linear test, and that they can be adapted according to the test taker's ability…
Descriptors: Programming Languages, Monte Carlo Methods, Computer Assisted Testing, Test Format
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Kilic, Abdullah Faruk; Uysal, Ibrahim – International Journal of Assessment Tools in Education, 2022
Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the…
Descriptors: Item Analysis, Correlation, Item Response Theory, Test Items
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Melissa G. Wolf; Daniel McNeish – Grantee Submission, 2023
To evaluate the fit of a confirmatory factor analysis model, researchers often rely on fit indices such as SRMR, RMSEA, and CFI. These indices are frequently compared to benchmark values of 0.08, 0.06, and 0.96, respectively, established by Hu and Bentler (1999). However, these indices are affected by model characteristics and their sensitivity to…
Descriptors: Programming Languages, Cutting Scores, Benchmarking, Factor Analysis
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Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
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Seebut, Supot; Wongsason, Patcharee; Kim, Dojin; Putjuso, Thanin; Boonpok, Chawalit – EURASIA Journal of Mathematics, Science and Technology Education, 2022
Simulation modeling is an effective tool for solving problems that cannot be explained analytically or when data cannot be collected. This is done by simulating the observed behavior of a problem under study using a computer program. In math education, this can develop knowledge and fundamental competencies of simulation modeling at a higher level…
Descriptors: Programming Languages, Mathematics Instruction, Grade 12, Secondary School Students
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Lockwood, J. R.; Castellano, Katherine E.; McCaffrey, Daniel F. – Journal of Educational and Behavioral Statistics, 2022
Many states and school districts in the United States use standardized test scores to compute annual measures of student achievement progress and then use school-level averages of these growth measures for various reporting and diagnostic purposes. These aggregate growth measures can vary consequentially from year to year for the same school,…
Descriptors: Accuracy, Prediction, Programming Languages, Standardized Tests