Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 4 |
Descriptor
Data Analysis | 4 |
Grade 10 | 4 |
Probability | 4 |
Academic Achievement | 2 |
Grade 8 | 2 |
High School Students | 2 |
Teaching Methods | 2 |
Access to Education | 1 |
Achievement Gains | 1 |
Advertising | 1 |
College Bound Students | 1 |
More ▼ |
Source
ACT, Inc. | 1 |
Australian Mathematics Teacher | 1 |
Journal of Educational and… | 1 |
Mathematics Teacher: Learning… | 1 |
Publication Type
Journal Articles | 3 |
Reports - Descriptive | 2 |
Reports - Evaluative | 1 |
Reports - Research | 1 |
Education Level
Grade 10 | 4 |
High Schools | 3 |
Secondary Education | 3 |
Grade 8 | 2 |
Grade 12 | 1 |
Higher Education | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Audience
Location
Australia | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Jones, Joshua David – Mathematics Teacher: Learning and Teaching PK-12, 2022
To be literate in a society where the information shared online is often exploited, learners should be exposed to multiple aspects of contemporary predictive modeling. This article explores an activity in which grade 10 students learned how a famous AI algorithm (the Apriori algorithm) uses conditional probability to automate the process of…
Descriptors: Mathematics Instruction, Teaching Methods, Grade 10, High School Students
Watson, Jane M. – Australian Mathematics Teacher, 2012
This article compares the definition of "box plot" as used in the "Australian Curriculum: Mathematics" with other definitions used in the education community; describes the difficulties students experience when dealing with box plots; and discusses the elaboration that is necessary to enable teachers to develop the knowledge…
Descriptors: Foreign Countries, Probability, Data Analysis, Mathematics Curriculum
Feldman, Betsy J.; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In longitudinal education studies, assuming that dropout and missing data occur completely at random is often unrealistic. When the probability of dropout depends on covariates and observed responses (called "missing at random" [MAR]), or on values of responses that are missing (called "informative" or "not missing at random" [NMAR]),…
Descriptors: Dropouts, Academic Achievement, Longitudinal Studies, Computation
ACT, Inc., 2007
The Gaining Early Awareness and Readiness for Undergraduate Program (GEAR UP) is designed to provide assistance to low income students. The program provides discretionary grants for the purpose of increasing the readiness of low income students to attend and succeed in postsecondary education. The grants are up to six years in length and provide…
Descriptors: Low Income Groups, Academic Achievement, Data Analysis, Grade 8