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Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2021
This is the fifth in a series of statistical articles for mathematics teachers. In this article the authors discuss graphs for exploring relationships between one categorical variable and one numerical variable using stemplots and boxplots and between two numerical variables, using scatterplots and time series plots. [For "The Data Files 4:…
Descriptors: Mathematics Instruction, Graphs, Mathematical Concepts, Visual Aids
Mohammad, Nagham; McGivern, Lucinda – Online Submission, 2020
In regression analysis courses, there are many settings in which the response variable under study is continuous, strictly positive, and right skew. This type of response variable does not adhere to the normality assumptions underlying the traditional linear regression model, and accordingly may be analyzed using a generalized linear model…
Descriptors: Regression (Statistics), Statistical Distributions, Simulation, Data Analysis
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Tran, Dung; Tarr, James E. – International Journal of Science and Mathematics Education, 2018
Through the lenses of statistical investigations and cognitive demands, we examined bivariate data tasks offered in US high school mathematics textbook series--a popular representative of three curriculum types: traditional, integrated, and hybrid. We developed a framework grounded in literature of association topics for the inclusion and…
Descriptors: High Schools, Secondary School Mathematics, Mathematics Instruction, Textbooks
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Aksoy, Esra; Narli, Serkan; Aksoy, Mehmet Akif – International Journal of Research in Education and Science, 2018
In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…
Descriptors: Academically Gifted, Talent Identification, Data Collection, Mathematics Instruction
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Pfannkuch, Maxine; Wild, Chris; Arnold, Pip; Budgett, Stephanie – set: Research Information for Teachers, 2020
The first two decades of the 21st century has heralded an unprecedented data revolution increasingly impacting our daily lives. Statistics education must continually update itself to prepare students for this new data-driven world. In this reflection on our research during this time, we discuss how fostering learning from data brought many…
Descriptors: Educational Research, Educational History, Statistics, Reflection
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Çelik, H. Coskun – Educational Research and Reviews, 2017
The aim of the present study was to examine the mathematical modelling studies done between 2004 and 2015 in Turkey and to reveal their tendencies. Forty-nine studies were selected using purposeful sampling based on the term, "mathematical modelling" with Higher Education Academic Search Engine. They were analyzed with content analysis.…
Descriptors: Mathematical Models, Foreign Countries, Content Analysis, Qualitative Research
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Lu, Owen H. T.; Huang, Anna Y. Q.; Huang, Jeff C. H.; Lin, Albert J. Q.; Ogata, Hiroaki; Yang, Stephen J. H. – Educational Technology & Society, 2018
Blended learning combines online digital resources with traditional classroom activities and enables students to attain higher learning performance through well-defined interactive strategies involving online and traditional learning activities. Learning analytics is a conceptual framework and is a part of our Precision education used to analyze…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Data Collection
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Liu, Ran; Koedinger, Kenneth R. – Journal of Educational Data Mining, 2017
As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
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Turgut, Sedat – International Journal of Progressive Education, 2019
By using the descriptive content analysis, this research study aimed to evaluate the studies on mathematics education presented within the scope of International Classroom Teaching Education Symposium (USOS) and published in proceeding book between 2014-2018. Findings of the study indicated that the number of studies conducted about mathematics…
Descriptors: Mathematics Education, Mathematics Instruction, Elementary School Mathematics, Content Analysis
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James, Terry – College Quarterly, 2018
The purpose is to improve insights and educational results by applying analytic methods. The focus is on the mathematics applied to learn from the kind of data available to most classes such as final examination marks or homework grades. The sample is 249 students learning introductory college statistics. The result is a predictive model for…
Descriptors: Data Analysis, Mathematics Instruction, Introductory Courses, Statistics
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Konold, Clifford; Higgins, Traci; Russell, Susan Jo; Khalil, Khalimahtul – Educational Studies in Mathematics, 2015
Statistical reasoning focuses on properties that belong not to individual data values but to the entire aggregate. We analyze students' statements from three different sources to explore possible building blocks of the idea of data as aggregate and speculate on how young students go about putting these ideas together. We identify four general…
Descriptors: Statistical Analysis, Mathematical Logic, Data Analysis, Mathematical Concepts
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Blagdanic, Casandra; Chinnappan, Mohan – Australian Mathematics Teacher, 2013
Numeracy in schools is becoming an increasingly important part of mathematics learning and teaching. This is because educators want students to engage with mathematical concepts more deeply, use mathematics to make sense of their environment and make decisions that are based on the analysis of mathematical information. In order to be numerate,…
Descriptors: Statistical Analysis, Statistics, Data Interpretation, Numeracy
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Hassani, Mehdi; Kippen, Rebecca; Mills, Terence – Australian Senior Mathematics Journal, 2016
Life tables are mathematical tables that document probabilities of dying and life expectancies at different ages in a society. Thus, the life table contains some essential features of the health of a population. Probability is often regarded as a difficult branch of mathematics. Life tables provide an interesting approach to introducing concepts…
Descriptors: Probability, Mathematical Concepts, Death, Mortality Rate
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Pierce, Robyn; Chick, Helen – Mathematics Education Research Journal, 2013
As a consequence of the increased use of data in workplace environments, there is a need to understand the demands that are placed on users to make sense of such data. In education, teachers are being increasingly expected to interpret and apply complex data about student and school performance, and, yet it is not clear that they always have the…
Descriptors: Statistical Analysis, Misconceptions, Statistics, Data
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Chen, Xin; Self, Jessica Zeitz; House, Leanna; Wenskovitch, John; Sun, Maoyuan; Wycoff, Nathan; Evia, Jane Robertson; Leman, Scotland; North, Chris – IEEE Transactions on Learning Technologies, 2018
With the rise of big data, it is becoming increasingly important to educate groups of students at many educational levels about data analytics. In particular, students without a strong mathematical background may have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods,…
Descriptors: Data, Visualization, Multidimensional Scaling, Mathematics Instruction
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