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Roberto Silva de Souza Jr.; Endler Marcel Borges – Journal of Chemical Education, 2023
This laboratory experiment was divided into four parts. In the first part, students evaluate previously published data and check their normality using histograms, Q-Q plots, the Shapiro-Wilk test, and boxplots. In the second part, two different groups were compared. First, data normality and homoskedasticity were checked by using the Shapiro-Wilk…
Descriptors: Statistics Education, Hypothesis Testing, Chemistry, Comparative Analysis
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Wanxue Zhang; Lingling Meng; Bilan Liang – Interactive Learning Environments, 2023
With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…
Descriptors: Information Technology, Computer Science Education, High School Students, Scoring
Doroudi, Shayan; Kamar, Ece; Brunskill, Emma; Horvitz, Eric – Online Submission, 2016
We explore how crowdworkers can be trained to tackle complex crowdsourcing tasks. We are particularly interested in training novice workers to perform well on solving tasks in situations where the space of strategies is large and workers need to discover and try different strategies to be successful. In a first experiment, we perform a comparison…
Descriptors: Training Methods, Novices, Outsourcing, Comparative Analysis
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Alverson, Charlotte Y.; Yamamoto, Scott H. – SAGE Open, 2016
In this study, we used a paper-pencil questionnaire to investigate whether teachers, administrators, and parents differed in their preferences and accuracy when interpreting visual data displays for decision making. For the data analysis, we used nonparametric tests due to violations of distributional assumptions for using parametric tests. We…
Descriptors: Visual Aids, Data, Decision Making, Data Analysis
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Koon, Sharon; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2015
The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…
Descriptors: Classification, Regression (Statistics), Models, At Risk Students
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Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…
Descriptors: At Risk Students, Reading Difficulties, Identification, Reading Comprehension
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Kos, Marjanca; Jerman, Janez; Anžlovar, Urška; Torkar, Gregor – International Journal of Environmental and Science Education, 2016
Early childhood is a period of life in which lifelong attitudes, values and patterns of behaviour regarding nature are shaped. Environmental education is becoming a growing area of interest in early childhood education. The aim of the research study was to identify children's understanding of why and how their pro-environmental behaviours…
Descriptors: Foreign Countries, Preschool Children, Childhood Attitudes, Knowledge Level
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Stull, Andrew T.; Hegarty, Mary – Journal of Educational Psychology, 2016
This study investigated the development of representational competence among organic chemistry students by using 3D (concrete and virtual) models as aids for teaching students to translate between multiple 2D diagrams. In 2 experiments, students translated between different diagrams of molecules and received verbal feedback in 1 of the following 3…
Descriptors: Models, Organic Chemistry, Science Instruction, Skill Development
Karabatsos, George; Walker, Stephen G. – Society for Research on Educational Effectiveness, 2011
Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…
Descriptors: Bayesian Statistics, Regression (Statistics), Nonparametric Statistics, Statistical Inference