Publication Date
In 2025 | 1 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 2 |
Descriptor
Source
Journal of Statistics and… | 2 |
Author
Blake, Adam B. | 1 |
Fries, Laura | 1 |
Jack A. Dieckmann | 1 |
Jesse Ramirez | 1 |
Jo Boaler | 1 |
Ken Cor | 1 |
Kira Conte | 1 |
Megan Selbach-Allen | 1 |
Son, Ji Y. | 1 |
Stigler, James W. | 1 |
Tanya LaMar | 1 |
More ▼ |
Publication Type
Journal Articles | 2 |
Reports - Descriptive | 1 |
Reports - Research | 1 |
Tests/Questionnaires | 1 |
Education Level
High Schools | 1 |
Higher Education | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Location
California | 2 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Jo Boaler; Kira Conte; Ken Cor; Jack A. Dieckmann; Tanya LaMar; Jesse Ramirez; Megan Selbach-Allen – Journal of Statistics and Data Science Education, 2025
This article reports on a multi-method study of a high school course in data science, finding that students who take data science take more mathematics courses than those who do not, there are more under-represented students in data science than is typical for other advanced mathematics courses; that the students who take data science are more…
Descriptors: Mathematics Instruction, Opportunities, High School Students, Data Science
Son, Ji Y.; Blake, Adam B.; Fries, Laura; Stigler, James W. – Journal of Statistics and Data Science Education, 2021
Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help…
Descriptors: Statistics Education, Introductory Courses, Teaching Methods, Data Analysis