Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Accuracy | 2 |
| Form Classes (Languages) | 2 |
| Natural Language Processing | 2 |
| Teaching Methods | 2 |
| Artificial Intelligence | 1 |
| Classification | 1 |
| College Freshmen | 1 |
| Computational Linguistics | 1 |
| Computer Mediated… | 1 |
| Computer Software | 1 |
| Data Analysis | 1 |
| More ▼ | |
Author
| Allen, Laura K. | 1 |
| Cui, Jialin | 1 |
| Gehringer, Edward | 1 |
| Jia, Qinjin | 1 |
| Liu, Chengyuan | 1 |
| McNamara, Danielle S. | 1 |
| Mills, Caitlin | 1 |
| Perret, Cecile | 1 |
| Shang, Ruixuan | 1 |
| Xiao, Yunkai | 1 |
Publication Type
| Reports - Research | 2 |
| Speeches/Meeting Papers | 2 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 2 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textLiu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
Direct linkAllen, Laura K.; Mills, Caitlin; Perret, Cecile; McNamara, Danielle S. – Grantee Submission, 2019
This study examines the extent to which instructions to self-explain vs. "other"-explain a text lead readers to produce different forms of explanations. Natural language processing was used to examine the content and characteristics of the explanations produced as a function of instruction condition. Undergraduate students (n = 146)…
Descriptors: Language Processing, Science Instruction, Computational Linguistics, Teaching Methods
