Publication Date
| In 2025 | 0 |
| Since 2024 | 1 |
| Since 2021 (last 5 years) | 2 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Algorithms | 2 |
| Artificial Intelligence | 2 |
| Comparative Analysis | 2 |
| Hierarchical Linear Modeling | 2 |
| Identification | 2 |
| Accuracy | 1 |
| At Risk Students | 1 |
| Attendance | 1 |
| Classification | 1 |
| Computer Software | 1 |
| Early Childhood Education | 1 |
| More ▼ | |
Source
| Society for Research on… | 2 |
Publication Type
| Reports - Research | 2 |
Education Level
| Early Childhood Education | 1 |
| Elementary Education | 1 |
| Grade 3 | 1 |
| Primary Education | 1 |
Audience
Location
| Massachusetts (Boston) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkWei Li; Walter Leite; Jia Quan – Society for Research on Educational Effectiveness, 2023
Background: Multilevel randomized controlled trials (MRCTs) have been widely used to evaluate the causal effects of educational interventions. Traditionally, educational researchers and policymakers focused on the average treatment effects (ATE) of the intervention. Recently there has been an increasing interest in evaluating the heterogeneity of…
Descriptors: Artificial Intelligence, Identification, Hierarchical Linear Modeling, Randomized Controlled Trials
Tiffany Wu; Christina Weiland – Society for Research on Educational Effectiveness, 2024
Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…
Descriptors: Attendance, Early Childhood Education, Intervention, Artificial Intelligence
