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Travis Weiland; Immanuel Williams – Journal of Statistics and Data Science Education, 2024
In this article, we consider how to make data more meaningful to students through the choice of data and the activities we use them in drawing upon students lived experiences more in the teaching of statistics and data science courses. In translating scholarship around culturally relevant pedagogy from the fields of education and mathematics…
Descriptors: Undergraduate Students, Predominantly White Institutions, Statistics Education, Culturally Relevant Education
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Barb Bennie; Richard A. Erickson – Journal of Statistics and Data Science Education, 2024
Effective undergraduate statistical education requires training using real-world data. Textbook datasets seldom match the complexities and messiness of real-world data and finding these datasets can be challenging for educators. Consulting and industrial datasets often have nondisclosure agreements. Academic datasets often require subject area…
Descriptors: Undergraduate Students, Statistics Education, Data Science, Earth Science
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Gabriella Roby Dodd; Cedric Gondro; Tasia M.Taxis; Margaret Young; Breno Fragomeni – NACTA Journal, 2024
The objectives of this study were to identify gaps in educational training for undergraduate and graduate students in agricultural data science, propose paths for filling these gaps, and provide an annotated list of resources currently available to different training levels. Data in this study was collected through three voluntary surveys catered…
Descriptors: Data Science, Statistics Education, Agriculture, Genetics
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Noll, Jennifer; Tackett, Maria – Teaching Statistics: An International Journal for Teachers, 2023
As the field of data science evolves with advancing technology and methods for working with data, so do the opportunities for re-conceptualizing how we teach undergraduate statistics and data science courses for majors and non-majors alike. In this paper, we focus on three crucial components for this re-conceptualization: Developing research…
Descriptors: Undergraduate Students, Statistics Education, Data Science, Teaching Methods
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Qing Wang; Xizhen Cai – Journal of Statistics and Data Science Education, 2024
Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…
Descriptors: Active Learning, Class Activities, Classification, Artificial Intelligence
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Vilhuber, Lars; Son, Hyuk Harry; Welch, Meredith; Wasser, David N.; Darisse, Michael – Journal of Statistics and Data Science Education, 2022
We describe a unique environment in which undergraduate students from various STEM and social science disciplines are trained in data provenance and reproducible methods, and then apply that knowledge to real, conditionally accepted manuscripts and associated replication packages. We describe in detail the recruitment, training, and regular…
Descriptors: Statistics Education, Data Science, STEM Education, Social Sciences
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Jose L. Salas; Xinran Wang; Mary C. Tucker; Ji Y. Son – Online Learning, 2024
Students believe mathematics is best learned by memorization; however, endorsing memorization as a study strategy is associated with a decrease in learning (Schoenfeld, 1989). When the world changed with the onset of the COVID-19 global pandemic, instruction transitioned to fully remote instruction where many assignments and examinations became…
Descriptors: Distance Education, Memorization, Pandemics, COVID-19
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Anna Khalemsky; Yelena Stukalin – Statistics Education Research Journal, 2024
The article describes the inclusive perspective of instruction of multi-stage practical projects in undergraduate non-STEM statistics and data mining courses at an academic college in Israel. The student population is highly diverse, comprising individuals from various cultural and ethnic groups. The study examines the impact of diversity on…
Descriptors: Foreign Countries, Undergraduate Students, Statistics Education, Data Science