Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 3 |
| Since 2006 (last 20 years) | 3 |
Descriptor
| Bayesian Statistics | 4 |
| Classification | 2 |
| College Students | 2 |
| Higher Education | 2 |
| Models | 2 |
| Academic Achievement | 1 |
| Academic Failure | 1 |
| Academic Persistence | 1 |
| Accuracy | 1 |
| Artificial Intelligence | 1 |
| Career Choice | 1 |
| More ▼ | |
Source
| Measurement and Evaluation in… | 4 |
Author
Publication Type
| Journal Articles | 4 |
| Reports - Research | 4 |
| Reports - General | 1 |
Education Level
| High Schools | 1 |
| Higher Education | 1 |
| Postsecondary Education | 1 |
| Secondary Education | 1 |
| Two Year Colleges | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Myers Briggs Type Indicator | 1 |
| Youth Risk Behavior Survey | 1 |
What Works Clearinghouse Rating
Direct linkBaghestani, Ahmad Reza; Ahmadi, Farzane; Tanha, Azadeh; Meshkat, Mojtaba – Measurement and Evaluation in Counseling and Development, 2019
The content validity ratio (CVR), which is suggested by Lawshe (1975), is a widely used index to quantify content validity. In this study, the Bayesian approach is used to determine the minimum number of experts required to agree an item is essential, and then the CVR is calculated.
Descriptors: Content Validity, Bayesian Statistics, Specialists, Measurement Techniques
Mangino, Anthony A.; Smith, Kendall A.; Finch, W. Holmes; Hernández-Finch, Maria E. – Measurement and Evaluation in Counseling and Development, 2022
A number of machine learning methods can be employed in the prediction of suicide attempts. However, many models do not predict new cases well in cases with unbalanced data. The present study improved prediction of suicide attempts via the use of a generative adversarial network.
Descriptors: Prediction, Suicide, Artificial Intelligence, Networks
Kooken, Janice; Welsh, Megan E.; McCoach, D. Betsy; Johnston-Wilder, Sue; Lee, Clare – Measurement and Evaluation in Counseling and Development, 2016
The Mathematical Resilience Scale measures students' attitudes toward studying mathematics, using three correlated factors: Value, Struggle, and Growth. The Mathematical Resilience Scale was developed and validated using exploratory and confirmatory factor analyses across three samples. Results provide a new approach to gauge the likelihood of…
Descriptors: Mathematics, Mathematics Instruction, Student Attitudes, Thinking Skills
Peer reviewedJones, W. Paul – Measurement and Evaluation in Counseling and Development, 1993
Investigated model for reducing time for administration of Myers-Briggs Type Indicator (MBTI) using real-data simulation of Bayesian scaling in computerized adaptive administration. Findings from simulation study using data from 127 undergraduates are strongly supportive of use of Bayesian scaled computerized adaptive administration of MBTI.…
Descriptors: Bayesian Statistics, Classification, College Students, Computer Assisted Testing
