Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 2 |
Descriptor
| Coding | 2 |
| Regression (Statistics) | 2 |
| Alphabets | 1 |
| Artificial Intelligence | 1 |
| Bayesian Statistics | 1 |
| Business Education | 1 |
| Computer Software | 1 |
| Data Analysis | 1 |
| Early Intervention | 1 |
| Higher Education | 1 |
| Learning Strategies | 1 |
| More ▼ | |
Author
| Chen Zhong | 1 |
| J. B. Kim | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
| Reports - Research | 1 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkChen Zhong; J. B. Kim – Journal of Information Systems Education, 2024
Data Analytics has emerged as an essential skill for business students, and several tools are available to support their learning in this area. Due to the students' lack of programming skills and the perceived complexity of R, many business analytics courses employ no-code analytical software like IBM SPSS Modeler. Nonetheless, generative…
Descriptors: Business Education, Regression (Statistics), Programming, Artificial Intelligence
Download full textWhat Works Clearinghouse, 2023
The appendices accompany the full report "Using Bayesian Meta-Analysis to Explore the Components of Early Literacy Interventions. WWC 2023-008," (ED630495), which pilots a new taxonomy developed by early literacy experts and intervention developers as part of a larger effort to develop standard nomenclature for the components of literacy…
Descriptors: Bayesian Statistics, Meta Analysis, Early Intervention, Literacy
