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Jones, Joshua David – Mathematics Teacher: Learning and Teaching PK-12, 2022
To be literate in a society where the information shared online is often exploited, learners should be exposed to multiple aspects of contemporary predictive modeling. This article explores an activity in which grade 10 students learned how a famous AI algorithm (the Apriori algorithm) uses conditional probability to automate the process of…
Descriptors: Mathematics Instruction, Teaching Methods, Grade 10, High School Students
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Stern, David; Stern, Roger; Parsons, Danny; Musyoka, James; Torgbor, Francis; Mbasu, Zach – Statistics Education Research Journal, 2020
The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced -- mathematics…
Descriptors: Foreign Countries, Data Collection, Data Analysis, Higher Education
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Roscoe, Matt B. – Mathematics Teaching in the Middle School, 2016
Instead of reserving the study of probability and statistics for special fourth-year high school courses, the Common Core State Standards for Mathematics (CCSSM) takes a "statistics for all" approach. The standards recommend that students in grades 6-8 learn to summarize and describe data distributions, understand probability, draw…
Descriptors: Data Analysis, Probability, Statistics, Mathematics
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Hidiroglu, Çaglar Naci; Güzel, Esra Bukova – International Journal for Technology in Mathematics Education, 2017
The aim of the study is to conceptualize the technology-aided mathematical modelling process in the frame of cognitive modelling perspective. The grounded theory approach was adopted in the study. The research was conducted with seven groups consisting of nineteen prospective mathematics teachers. The data were collected from the video records of…
Descriptors: Mathematical Concepts, Mathematics Education, Mathematical Models, Mathematics
Akoglu, Leman – ProQuest LLC, 2012
Large real-world graph (a.k.a network, relational) data are omnipresent, in online media, businesses, science, and the government. Analysis of these massive graphs is crucial, in order to extract descriptive and predictive knowledge with many commercial, medical, and environmental applications. In addition to its general structure, knowing what…
Descriptors: Networks, Graphs, Data, Mathematics
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Ellis, Amy B.; Ozgur, Zekiye; Kulow, Torrey; Dogan, Muhammed F.; Amidon, Joel – Mathematical Thinking and Learning: An International Journal, 2016
This article presents an Exponential Growth Learning Trajectory (EGLT), a trajectory identifying and characterizing middle grade students' initial and developing understanding of exponential growth as a result of an instructional emphasis on covariation. The EGLT explicates students' thinking and learning over time in relation to a set of tasks…
Descriptors: Numbers, Mathematics, Mathematics Instruction, Middle School Students
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Darby, Naomi – Australian Primary Mathematics Classroom, 2007
The idea of using mathematical research in the classroom to collect real data has been spoken about within education for many years. The question is, why should teachers bother with real data from their students' worlds and how do they actually put it into practice in the classroom? When using the mathematical research strategy for collecting,…
Descriptors: Mathematical Models, Teaching Methods, Classroom Research, Mathematics
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Leenen, Iwin; Van Mechelen, Iven – Psychometrika, 2004
This paper proposes a multidimensional generalization of Coombs' (1964) parallelogram model for "pick any/'n'" data, which result from each of a number of subjects having selected a number of objects (s)he likes most from a prespecified set of "n" objects. In the model, persons and objects are represented in a low dimensional space defined by a…
Descriptors: Intervals, Simulation, Mathematical Models, Data Analysis
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Jackson, Paul R. – Mathematical Spectrum, 1972
The probabilities of certain English football teams winning different playoffs are determined. In each case, a mathematical model is fitted to the observed data, assumptions are verified, and the calculations performed. (LS)
Descriptors: College Mathematics, Data Analysis, Mathematical Applications, Mathematical Models
McCormick, William T., Jr.; And Others – 1969
Presented are the results of a study conducted to develop algorithms for ordering and organizing data that can be presented in a two-dimensional matrix form. The purpose of the work was to develop methods to extract latent data patterns, grouping, and structural relationships which are not apparent from the raw matrix data. The algorithms…
Descriptors: Algorithms, Data Analysis, Data Processing, Mathematical Applications
Pennell, Roger – 1971
It is argued that many investigators utilize the Tucker and Messick (1963) Model with no intention of looking for individual differences or, after utilizing the model, draw improper inferences. An example is given illustrating the difficulties which result from improper use of the model. Several proper methods are outlined. (Author)
Descriptors: Algorithms, Behavioral Science Research, Computer Oriented Programs, Data Analysis
Burstein, Leigh; Linn, Robert L. – 1982
This discussion of how the multilevel character of data should influence analyses of the determinants of educational achievement is grounded in the context of planning explanatory analyses for the longitudinal Second International Mathematics Study (SIMS). The intention is to describe how a multilevel perspective in the specification of…
Descriptors: Academic Achievement, Data Analysis, Educational Objectives, Educational Practices
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Scheaffer, Richard L. – Mathematics Teacher, 1990
Outlines differences between classical statistics and exploratory data analysis. Provides examples in the use of the exploratory techniques. (YP)
Descriptors: Data Analysis, Evaluation Methods, Graphs, Mathematical Models
Beall, Geoffrey – 1971
This guide presents many new experimental designs for data analysis and reviews certain standard procedures. It is hoped that the treatment of the material will stimulate new applications since the emphasis of the guide is on the problems encountered in running experiments rather than on an elaboration of mathematical models. Discussed are:…
Descriptors: Analysis of Variance, Computer Programs, Data Analysis, Experiments
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers