Publication Date
| In 2025 | 0 |
| Since 2024 | 1 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Evaluation Methods | 2 |
| Guidelines | 2 |
| Models | 2 |
| Accuracy | 1 |
| Achievement Gains | 1 |
| Achievement Rating | 1 |
| Algorithms | 1 |
| Artificial Intelligence | 1 |
| Bayesian Statistics | 1 |
| Concept Mapping | 1 |
| Curriculum Development | 1 |
| More ▼ | |
Source
| Measurement:… | 2 |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
| Elementary Secondary Education | 1 |
| Grade 8 | 1 |
Audience
Location
| California | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkA. M. Sadek; Fahad Al-Muhlaki – Measurement: Interdisciplinary Research and Perspectives, 2024
In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…
Descriptors: Monte Carlo Methods, Accuracy, Artificial Intelligence, Guidelines
Black, Paul; Wilson, Mark; Yao, Shih-Ying – Measurement: Interdisciplinary Research and Perspectives, 2011
The overall aim of this article is to analyze the relationships between the roles of assessment in pedagogy, the interactions between curriculum assessment and pedagogy, and the study of pupils' progression in learning. It is argued that well-grounded evidence of pupils' progressions in learning is crucial to the work of teachers, so that a method…
Descriptors: Evidence, Learning Strategies, Program Effectiveness, Grade 8
