Publication Date
In 2025 | 1 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 15 |
Since 2016 (last 10 years) | 16 |
Since 2006 (last 20 years) | 16 |
Descriptor
Computer Science Education | 16 |
Statistics Education | 16 |
Teaching Methods | 16 |
Data Analysis | 7 |
Computer Software | 6 |
Foreign Countries | 6 |
Programming Languages | 6 |
Undergraduate Students | 6 |
Introductory Courses | 5 |
Student Attitudes | 5 |
College Faculty | 3 |
More ▼ |
Source
Journal of Statistics and… | 7 |
Statistics Education Research… | 4 |
Educational Technology &… | 1 |
International Electronic… | 1 |
Journal of Pedagogical… | 1 |
National Academies Press | 1 |
TechTrends: Linking Research… | 1 |
Author
Publication Type
Journal Articles | 15 |
Reports - Research | 10 |
Reports - Descriptive | 5 |
Tests/Questionnaires | 2 |
Reports - Evaluative | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Hong Kong | 2 |
Australia | 1 |
Germany | 1 |
Israel | 1 |
New Zealand | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Amelia McNamara – Journal of Statistics and Data Science Education, 2024
When incorporating programming into a statistics course, there are many pedagogical considerations. In R, one consideration is the particular R syntax used. This article reports on a head-to-head comparison of a pair of introductory statistics labs, one conducted in the formula syntax, the other in tidyverse. Pre- and post-surveys show minimal…
Descriptors: Teaching Methods, Introductory Courses, Statistics Education, Programming Languages
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
Viet-Ngu Hoang; Will Connell; Radhika Lahiri; H. Nadeeka De Silva; Xuan-Hoan Pham – TechTrends: Linking Research and Practice to Improve Learning, 2025
Dashboards have become a crucial element of contemporary business operation and management; therefore, it is desirable for business students to acquire knowledge of them. This article investigates the effectiveness of designing learning activities around investment dashboards in the context of introductory business analytics (IBA) courses. We…
Descriptors: Introductory Courses, Business Education, Management Systems, Statistics Education
Li, Ken W.; Goos, Merrilyn – International Electronic Journal of Mathematics Education, 2021
This paper addresses the question of whether peer collaboration affects students' performance of regression modelling tasks, an experimental study consisting of a test was conducted in a computing laboratory. Collaborating groups of students were randomly assigned to one of three experimental conditions: pre-task discussion (i.e., group members…
Descriptors: Cooperative Learning, Academic Achievement, Computer Science Education, Regression (Statistics)
Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
Podworny, Susanne; Hüsing, Sven; Schulte, Carsten – Statistics Education Research Journal, 2022
Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…
Descriptors: Statistics Education, Programming, Programming Languages, Data Analysis
Savonen, Candace; Wright, Carrie; Hoffman, Ava M.; Muschelli, John; Cox, Katherine; Tan, Frederick J.; Leek, Jeffrey T. – Journal of Statistics and Data Science Education, 2023
Data science and informatics tools are developing at a blistering rate, but their users often lack the educational background or resources to efficiently apply the methods to their research. Training resources and vignettes that accompany these tools often deprecate because their maintenance is not prioritized by funding, giving teams little time…
Descriptors: Open Source Technology, Multiple Choice Tests, Summative Evaluation, Formative Evaluation
Legacy, Chelsey; Zieffler, Andrew; Fry, Elizabeth Brondos; Le, Laura – Statistics Education Research Journal, 2022
The influx of data and the advances in computing have led to calls to update the introductory statistics curriculum to better meet the needs of the contemporary workforce. To this end, we developed the COMputational Practices in Undergraduate TEaching of Statistics (COMPUTES) instrument, which can be used to measure the extent to which computation…
Descriptors: Statistics Education, Introductory Courses, Undergraduate Students, Teaching Methods
Mike, Koby; Hazzan, Orit – Statistics Education Research Journal, 2022
Data science is a new field of research that has attracted growing interest in recent years as it focuses on turning raw data into understanding, insight, knowledge, and value. New data science education programs, which are being launched at an increasing rate, are designed for multiple education levels and populations. Machine learning (ML) is an…
Descriptors: Teaching Methods, Nonmajors, Statistics Education, Artificial Intelligence
Bhargava, Rahul; Brea, Amanda; Palacin, Victoria; Perovich, Laura; Hinson, Jesse – Educational Technology & Society, 2022
Data literacy is a growing area of focus across multiple disciplines in higher education. The dominant forms of introduction focus on computational toolchains and statistical ways of knowing. As data driven decision-making becomes more central to democratic processes, a larger group of learners must be engaged in order to ensure they have a seat…
Descriptors: Theater Arts, Data Analysis, Social Justice, Statistics Education
Reinhart, Alex; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…
Descriptors: Computer Software, Graduate Students, Computer Science Education, Statistics Education
Liao, Shu-Min – Journal of Statistics and Data Science Education, 2023
SCRATCH, developed by the Media Lab at MIT, is a kid-friendly visual programming language, designed to introduce programming to children and teens in a "more thinkable, more meaningful, and more social" way. Although it was initially intended for K-12 students, educators have used it for higher education as well, and found it…
Descriptors: Teaching Methods, Coding, Programming Languages, Computer Science Education
Burckhardt, Philipp; Nugent, Rebecca; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
Revisiting the seminal 2010 Nolan and Temple Lang article on the role of computing in the statistics curricula, we discuss several trends that have emerged over the last ten years. The rise of data science has coincided with a broadening audience for learning statistics and using computational packages and tools. It has also increased the need for…
Descriptors: Statistics Education, Teaching Methods, Web Based Instruction, Data Analysis
Bilgin, Ayse Aysin Bombaci; Powell, Angela; Richards, Deborah – Statistics Education Research Journal, 2022
Work integrated learning (WIL) has been the norm in disciplines such as medicine, teacher education and engineering; however, it has not been implemented until recently in statistics and not for every student in computer science education. There seems to be no literature on the use of WIL for data science education. With the changed focus of…
Descriptors: Work Experience Programs, Statistics Education, Computer Science Education, Education Work Relationship
Li, Ken W. – Journal of Pedagogical Research, 2022
There has been much attention given to the use of technology in education; mostly concentrating on physical artifacts of technology to facilitate teaching delivery but little mentioning technology as a cultural resource to organize the learning environment promoting social interaction among students and between teacher and students. This paper…
Descriptors: Technology Integration, Statistics Education, Teaching Methods, Technology Uses in Education
Previous Page | Next Page »
Pages: 1 | 2