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Park, JinHyeong; Kim, Dong-Won – Educational Studies in Mathematics, 2023
Coordination of theoretical probability and relative frequency estimates is challenging in probability teaching and learning. Modeling is one of the ways of teaching and learning that facilitates inquiry between these two perspectives. Given that, we designed a modeling activity to support fifteen secondary students in investigating theoretical…
Descriptors: Probability, Computation, Mathematics Instruction, Mathematical Models
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Zhipeng Hou; Elizabeth Tipton – Research Synthesis Methods, 2024
Literature screening is the process of identifying all relevant records from a pool of candidate paper records in systematic review, meta-analysis, and other research synthesis tasks. This process is time consuming, expensive, and prone to human error. Screening prioritization methods attempt to help reviewers identify most relevant records while…
Descriptors: Meta Analysis, Research Reports, Identification, Evaluation Methods
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Martha Elena Aguiar Barrera; Humberto Gutierrez Pulido; Veronica Vargas Alejo – Statistics Education Research Journal, 2023
This research presents the results of the implementation of a model-eliciting activity called Brickyards, designed to promote the learning of the binomial distribution. The theoretical framework used was the Models and Modeling Perspective, and the participants were undergraduate students enrolled in a probability and statistics course of the…
Descriptors: Foreign Countries, Undergraduate Students, Civil Engineering, Learning Activities
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Koparan, Timur; Rodríguez-Alveal, Francisco – Journal of Pedagogical Research, 2022
Solving real-life problems through mathematical modeling is one of the aims of modern mathematics curricula. For this reason, prospective mathematics teachers need to acquire modeling skills and use these skills in learning environments in terms of creating rich learning environments. With this study, it is aimed to examine the reflections of…
Descriptors: Probability, Thinking Skills, Preservice Teachers, Graphs
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Hansen, Christian; Hansen, Casper; Alstrup, Stephen; Lioma, Christina – International Educational Data Mining Society, 2019
In this paper we consider the problem of modelling when students end their session in an online mathematics educational system. Being able to model this accurately will help us optimize the way content is presented and consumed. This is done by modelling the probability of an action being the last in a session, which we denote as the…
Descriptors: Integrated Learning Systems, Probability, Foreign Countries, Student Behavior
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Zieffler, Andrew; Justice, Nicola; delMas, Robert; Huberty, Michael D. – Journal of Statistics and Data Science Education, 2021
Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…
Descriptors: Mathematical Models, Thinking Skills, Teaching Methods, Statistics Education
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Hansen, Christian; Hansen, Casper; Hjuler, Niklas; Alstrup, Stephen; Lioma, Christina – International Educational Data Mining Society, 2017
The analysis of log data generated by online educational systems is an important task for improving the systems, and furthering our knowledge of how students learn. This paper uses previously unseen log data from Edulab, the largest provider of digital learning for mathematics in Denmark, to analyse the sessions of its users, where 1.08 million…
Descriptors: Foreign Countries, Markov Processes, Mathematical Models, Student Behavior
Zhang, Zhiyong; Zhang, Danyang – Grantee Submission, 2021
Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These…
Descriptors: Statistics Education, Definitions, Course Descriptions, Computer Science Education
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Dini, Vesal; Hammer, David – Physical Review Physics Education Research, 2017
Research on student epistemologies in introductory courses has highlighted the importance of understanding physics as "a refinement of everyday thinking" [A. Einstein, J. Franklin Inst. 221, 349 (1936)]. That view is difficult to sustain in quantum mechanics, for students as for physicists. How might students manage the transition? In…
Descriptors: Case Studies, Epistemology, Quantum Mechanics, Probability
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Gruver, Nate; Malik, Ali; Capoor, Brahm; Piech, Chris; Stevens, Mitchell L.; Paepcke, Andreas – International Educational Data Mining Society, 2019
Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…
Descriptors: Models, Course Selection (Students), Enrollment, Decision Making
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Wang, Chao; Lu, Hong – Educational Technology & Society, 2018
This study focused on the effect of examinees' ability levels on the relationship between Reflective-Impulsive (RI) cognitive style and item response time in computerized adaptive testing (CAT). The total of 56 students majoring in Educational Technology from Shandong Normal University participated in this study, and their RI cognitive styles were…
Descriptors: Item Response Theory, Computer Assisted Testing, Cognitive Style, Correlation
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Luo, Yong; Jiao, Hong – Educational and Psychological Measurement, 2018
Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software
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Butcher, Greg Q.; Rodriguez, Juan; Chirhart, Scott; Messina, Troy C. – Bioscene: Journal of College Biology Teaching, 2016
In order to increase students' awareness for and comfort with mathematical modeling of biological processes, and increase their understanding of diffusion, the following lab was developed for use in 100-level, majors/non-majors biology and neuroscience courses. The activity begins with generation of a data set that uses coin-flips to replicate…
Descriptors: Biology, Comparative Analysis, Simulation, Questionnaires
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Kazak, Sibel; Pratt, Dave – Statistics Education Research Journal, 2017
This study considers probability models as tools for both making informal statistical inferences and building stronger conceptual connections between data and chance topics in teaching statistics. In this paper, we aim to explore pre-service mathematics teachers' use of probability models for a chance game, where the sum of two dice matters in…
Descriptors: Preservice Teachers, Probability, Mathematical Models, Statistical Inference
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Braham, Hana Manor; Ben-Zvi, Dani – Statistics Education Research Journal, 2017
A fundamental aspect of statistical inference is representation of real-world data using statistical models. This article analyzes students' articulations of statistical models and modeling during their first steps in making informal statistical inferences. An integrated modeling approach (IMA) was designed and implemented to help students…
Descriptors: Foreign Countries, Elementary School Students, Statistical Inference, Mathematical Models
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