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Vehtari, Aki; Gelman, Andrew; Sivula, Tuomas; Jylänki, Pasi; Tran, Dustin; Sahai, Swupnil; Blomstedt, Paul; Cunningham, John P.; Schiminovich, David; Robert, Christian P. – Grantee Submission, 2020
A common divide-and-conquer approach for Bayesian computation with big data is to partition the data, perform local inference for each piece separately, and combine the results to obtain a global posterior approximation. While being conceptually and computationally appealing, this method involves the problematic need to also split the prior for…
Descriptors: Bayesian Statistics, Algorithms, Computation, Generalization
Kiyici, Gülbin; Kahraman, Nurcan – Science Insights Education Frontiers, 2022
This study aims to analyze the reliability generalization of the computational thinking scale. There are five dimensions of computational thinking: creativity, algorithmic thinking, cooperativity, critical thinking, and problem-solving. A Bonett transformation was used to standardize the reliability coefficient of Cronbach's alpha. A…
Descriptors: Meta Analysis, Generalization, Computation, Thinking Skills
Silvia Wen-Yu Lee; Jyh-Chong Liang; Chung-Yuan Hsu; Meng-Jung Tsai – Interactive Learning Environments, 2024
While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs…
Descriptors: Student Attitudes, Beliefs, Computer Science Education, Programming