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Rachel Clune; Avishek Das; Dipti Jasrasaria; Elliot Rossomme; Orion Cohen; Anne M. Baranger – Journal of Chemical Education, 2023
A student-led mathematics bootcamp has been designed and implemented to help foster community building, improve confidence in mathematical skills, and provide mathematical resources for incoming physical chemistry doctoral students. The bootcamp is held immediately before the start of the first semester of graduate school and uses an active…
Descriptors: Chemistry, Graduate Students, Workshops, Mathematics Skills
Kunene, Niki; Toskin, Katarzyna – Information Systems Education Journal, 2022
Logistic regression (LoR) is a foundational supervised machine learning algorithm and yet, unlike linear regression, appears rarely taught early on, where analogy and proximity to linear regression would be an advantage. A random sample of 50 syllabi from undergraduate business statistics courses shows only two percent of the courses included LoR.…
Descriptors: Introductory Courses, Teaching Methods, Probability, Regression (Statistics)
Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
Pek, Jolynn; Van Zandt, Trisha – Psychology Learning and Teaching, 2020
Statistical thinking is essential to understanding the nature of scientific results as a consumer. Statistical thinking also facilitates thinking like a scientist. Instead of emphasizing a "correct" procedure for data analysis and its outcome, statistical thinking focuses on the process of data analysis. This article reviews frequentist…
Descriptors: Bayesian Statistics, Thinking Skills, Data Analysis, Evaluation Methods
Kirsten Doehler; Laura Taylor – PRIMUS, 2024
A project involving data related to socioeconomic indicators was administered in an introductory statistics course. As part of this project, student groups investigated a data set from the United States Department of Agriculture Food and Nutrition Service website with information on recipients of Supplemental Nutrition Assistance Program (SNAP)…
Descriptors: College Students, Statistics Education, Introductory Courses, Mathematics Education
Majid Ghasemy; James Eric Gaskin; James A. Elwood – Journal of Applied Research in Higher Education, 2024
Purpose: The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job…
Descriptors: Industrial Psychology, Models, Higher Education, Job Satisfaction
Katherine A. Durante; Vanessa Z. Mari; Cristina Caputo – Journal of Latinos and Education, 2024
This research examines the role of Supplemental Instruction in assisting students at a small Hispanic-Serving Institution (HSI) in the Southwest United States to improve their final grades in a required statistics course for criminal justice majors. Data collected over three semesters were analyzed using multivariate regression to test if…
Descriptors: Supplementary Education, Minority Serving Institutions, Hispanic American Students, College Students
Rachel Wiemken; Gabriel Matney; Brandon Floro – Mathematics Teacher: Learning and Teaching PK-12, 2024
Seeking to leverage students' interests into mathematical tasks and noticing how their students excitedly discussed the NCAA's Division 1-A football rankings every year, the authors devised a mathematical modeling task in which students could use mathematics to justify their rankings. The task takes students on a journey to consider the complexity…
Descriptors: Team Sports, Mathematics Instruction, Mathematical Models, Student Interests
Paul Thompson; Kaydee Owen; Richard P. Hastings – International Journal of Research & Method in Education, 2024
Traditionally, cluster randomized controlled trials are analyzed with the average intervention effect of interest. However, in populations that contain higher degrees of heterogeneity or variation may differ across different values of a covariate, which may not be optimal. Within education and social science contexts, exploring the variation in…
Descriptors: Randomized Controlled Trials, Intervention, Mathematics Education, Mathematics Skills
Valerie Nazzaro; Jen Rose; Lisa Dierker; Courtney Merrick; Robin Donatello – Journal of College Science Teaching, 2024
The COVID-19 pandemic altered course delivery in higher education at many universities. This article evaluates the differences between student experiences in the fall 2019 semester (pre-pandemic) and those during the fall 2020 semester (pandemic) within a multidisciplinary, project-based introductory statistics course. Results indicated that there…
Descriptors: Student Projects, Introductory Courses, Statistics, College Mathematics
Anna Fergusson; Maxine Pfannkuch – Journal of Statistics and Data Science Education, 2024
Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics…
Descriptors: High School Students, Statistics Education, Thinking Skills, Computer Science Education
Zachary del Rosario – Journal of Statistics and Data Science Education, 2024
Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…
Descriptors: Foreign Countries, Engineering Education, Engineering, Technical Occupations
Beth Chance; Andrew Kerr; Jett Palmer – Journal of Statistics and Data Science Education, 2024
While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…
Descriptors: Publications, Public Opinion, Surveys, Bias
Laura Vernikoff; Emilie Mitescu Reagan – Review of Research in Education, 2024
Quantitative education research is often perceived to be "objective" or "neutral." However, quantitative research has been and continues to be used to perpetuate inequities; these inequities arise as both intended effects and unintended side effects of traditional quantitative research. In this review of the literature, we…
Descriptors: Educational Research, Educational Researchers, Research Methodology, Research Problems
Ana F. Backes; Valmor Ramos; Ricardo T. Quinaud; Sergio J. Ibáñez; Juliana Pizani; Humberto M. Carvalho; Juarez V. Nascimento – Quest, 2024
This study examined Physical Education Pre-Service Teachers' (PSTs) perceptions of their teaching from constructivist teaching practices and their variation among PSTs' responses when aggregated by sex, teaching practices curriculum, extension project, and university type. The sample consisted of 869 Physical Education PSTs from Brazil (female =…
Descriptors: Physical Education, Physical Education Teachers, Preservice Teachers, Teaching Methods

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