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Fávero, Luiz Paulo; Souza, Rafael de Freitas; Belfiore, Patrícia; Corrêa, Hamilton Luiz; Haddad, Michel F. C. – Practical Assessment, Research & Evaluation, 2021
In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…
Descriptors: Regression (Statistics), Selection, Statistical Analysis, Models
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Lozano, José H.; Revuelta, Javier – Applied Measurement in Education, 2021
The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…
Descriptors: Bayesian Statistics, Computation, Learning, Testing
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Shelton, G. Robert; Mamiya, Blain; Weber, Rebecca; Rush Walker, Deborah; Powell, Cynthia B.; Jang, Ben; Dubrovskiy, Anton V.; Villalta-Cerdas, Adrian; Mason, Diana – Journal of Chemical Education, 2021
The Math-Up Skills Tests (MUST) has been used in multiple research projects conducted by the Networking for Science Advancement (NSA) team to determine how automaticity skills (what can be done without a calculator) in arithmetic can be used to predict if students will be successful (course average = 69.5%+) in general chemistry. This study…
Descriptors: Undergraduate Students, College Science, Mathematics Tests, Mathematics Skills
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Miratrix, Luke W.; Weiss, Michael J.; Henderson, Brit – Journal of Research on Educational Effectiveness, 2021
Researchers face many choices when conducting large-scale multisite individually randomized control trials. One of the most common quantities of interest in multisite RCTs is the overall average effect. Even this quantity is non-trivial to define and estimate. The researcher can target the average effect across individuals or sites. Furthermore,…
Descriptors: Computation, Randomized Controlled Trials, Error of Measurement, Regression (Statistics)
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Fanchamps, Nardie L. J. A.; Slangen, Lou; Hennissen, Paul; Specht, Marcus – International Journal of Technology and Design Education, 2021
This study investigates the development of algorithmic thinking as a part of computational thinking skills and self-efficacy of primary school pupils using programmable robots in different instruction variants. Computational thinking is defined in the context of twenty-first century skills and describes processes involved in (re)formulating a…
Descriptors: Computation, Thinking Skills, Self Efficacy, Toys
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Leonard, Alison E.; Daily, Shaundra B.; Jörg, Sophie; Babu, Sabarish V. – Journal of Research on Technology in Education, 2021
Over the past 7 years, we pioneered the development of a program blending dance choreography, computer programming, and a virtual environment to teach computational thinking, broadening pathways for more diverse students. We investigated the ways in which upper elementary and middle school students creating dance performances for virtual…
Descriptors: Dance, Programming, Computation, Computer Simulation
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Mirolo, Claudio; Izu, Cruz; Lonati, Violetta; Scapin, Emanuele – Informatics in Education, 2021
When we "think like a computer scientist," we are able to systematically solve problems in different fields, create software applications that support various needs, and design artefacts that model complex systems. Abstraction is a soft skill embedded in all those endeavours, being a main cornerstone of computational thinking. Our…
Descriptors: Computer Science Education, Soft Skills, Thinking Skills, Abstract Reasoning
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Baris Pekmezci, Fulya; Sengul Avsar, Asiye – International Journal of Assessment Tools in Education, 2021
There is a great deal of research about item response theory (IRT) conducted by simulations. Item and ability parameters are estimated with varying numbers of replications under different test conditions. However, it is not clear what the appropriate number of replications should be. The aim of the current study is to develop guidelines for the…
Descriptors: Item Response Theory, Computation, Accuracy, Monte Carlo Methods
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Diaz, Emily; Brooks, Gordon; Johanson, George – International Journal of Assessment Tools in Education, 2021
This Monte Carlo study assessed Type I error in differential item functioning analyses using Lord's chi-square (LC), Likelihood Ratio Test (LRT), and Mantel-Haenszel (MH) procedure. Two research interests were investigated: item response theory (IRT) model specification in LC and the LRT and continuity correction in the MH procedure. This study…
Descriptors: Test Bias, Item Response Theory, Statistical Analysis, Comparative Analysis
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Polat, Elif; Hopcan, Sinan; Kucuk, Sevda; Sisman, Burak – British Journal of Educational Technology, 2021
Performance in and perceptions of computational thinking (CT) are considered vital dimensions for comprehensively assessing CT skills of students. In this study, secondary school students' CT performance and their perceptions were examined in terms of certain variables including gender, grade level, achievement and self-efficacy.…
Descriptors: Secondary School Students, Computation, Thinking Skills, Gender Differences
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Waterbury, Glenn Thomas; DeMars, Christine E. – Educational Assessment, 2021
Vertical scaling is used to put tests of different difficulty onto a common metric. The Rasch model is often used to perform vertical scaling, despite its strict functional form. Few, if any, studies have examined anchor item choice when using the Rasch model to vertically scale data that do not fit the model. The purpose of this study was to…
Descriptors: Test Items, Equated Scores, Item Response Theory, Scaling
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Lodi, Michael; Martini, Simone – Science & Education, 2021
The pervasiveness of Computer Science (CS) in today's digital society and the extensive use of computational methods in other sciences call for its introduction in the school curriculum. Hence, Computer Science Education is becoming more and more relevant. In CS K-12 education, computational thinking (CT) is one of the abused buzzwords: different…
Descriptors: Computer Science Education, Elementary Secondary Education, Computation, Definitions
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Woodard, Victoria; Lee, Hollylynne – Journal of Statistics and Data Science Education, 2021
As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well…
Descriptors: College Students, Statistics Education, Statistical Analysis, Computation
Karpinski, Zbigniew; Biagi, Federico; Di Pietro, Giorgio – International Association for the Evaluation of Educational Achievement, 2021
Numerous studies have shown that individuals from less advantaged backgrounds face poorer labor market prospects partly because they are characterized by low levels of skills, including digital skills. However, regarding digital skills, most of these studies rely on indicators of general digital competences rather than of specific information and…
Descriptors: Computation, Thinking Skills, Social Differences, Socioeconomic Status
Opfer, John E.; Kim, Dan; Fazio, Lisa K.; Zhou, Xinlin; Siegler, Robert S. – Grantee Submission, 2021
Chinese children routinely outperform American peers in standardized tests of mathematics knowledge. To examine mediators of this effect, 95 Chinese and US 5-year-olds completed a test of overall symbolic arithmetic, an IQ subtest, and three tests each of symbolic and non-symbolic numerical magnitude knowledge (magnitude comparison, approximate…
Descriptors: Foreign Countries, Mathematics Achievement, Cultural Differences, Arithmetic
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