Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 3 |
| Since 2016 (last 10 years) | 3 |
Descriptor
Author
| Bailey, Jessica | 1 |
| Cheng Liu | 1 |
| Hanita, Makoto | 1 |
| Hwang, Gwo-Jen | 1 |
| Khanani, Noman | 1 |
| Tang, Kai-Yu | 1 |
| Teresa M. Ober | 1 |
| Tu, Yun-Fang | 1 |
| Yikai Lu | 1 |
| Ying Cheng | 1 |
| Zhang, Xinxin | 1 |
| More ▼ | |
Publication Type
| Guides - General | 1 |
| Information Analyses | 1 |
| Journal Articles | 1 |
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Elementary Secondary Education | 1 |
| High Schools | 1 |
| Secondary Education | 1 |
Audience
| Policymakers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textHwang, Gwo-Jen; Tu, Yun-Fang; Tang, Kai-Yu – International Review of Research in Open and Distributed Learning, 2022
This study reviews the journal publications of artificial intelligence-supported online learning (AIoL) in the Web of Science (WOS) database from 1997 to 2019 taking into account the contributing countries/areas, leading journals, highly cited papers, authors, research areas, research topics, roles of AIoL, and adopted artificial intelligence (AI)…
Descriptors: Artificial Intelligence, Electronic Learning, Educational Research, Data Analysis
Direct linkYikai Lu; Teresa M. Ober; Cheng Liu; Ying Cheng – Grantee Submission, 2022
Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…
Descriptors: Prediction, Statistics Education, Data Analysis, Learning Analytics
Hanita, Makoto; Bailey, Jessica; Khanani, Noman; Zhang, Xinxin – Regional Educational Laboratory Northeast & Islands, 2021
This applied research methods report is a guide for state and local education agency policymakers and their analysts who are interested in studying teacher mobility and retention. This report is the second in a two-part set and builds on the foundational information in report 1. This report presents guidance on how to interpret differences in…
Descriptors: Faculty Mobility, Teacher Persistence, Educational Research, Research Methodology
