Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Source
International Educational… | 3 |
Author
Gehringer, Edward | 2 |
Jia, Qinjin | 2 |
Xiao, Yunkai | 2 |
Akbar, Shoaib | 1 |
Allen, Laura | 1 |
Balyan, Renu | 1 |
Banawan, Michelle | 1 |
Crossley, Scott | 1 |
Cui, Jialin | 1 |
Dong, Muyao | 1 |
Liu, Chengyuan | 1 |
More ▼ |
Publication Type
Reports - Research | 3 |
Speeches/Meeting Papers | 3 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Wan, Qian; Crossley, Scott; Banawan, Michelle; Balyan, Renu; Tian, Yu; McNamara, Danielle; Allen, Laura – International Educational Data Mining Society, 2021
The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…
Descriptors: Essays, Persuasive Discourse, Automation, Identification
Xiao, Yunkai; Zingle, Gabriel; Jia, Qinjin; Akbar, Shoaib; Song, Yang; Dong, Muyao; Qi, Li; Gehringer, Edward – International Educational Data Mining Society, 2020
Peer assessment adds value when students provide "helpful" feedback to their peers. But, this begs the question of how we determine "helpfulness." One important aspect is whether the review detects problems in the submitted work. To recognize problem detection, researchers have employed NLP and machine-learning text…
Descriptors: Peer Evaluation, Problems, Identification, Natural Language Processing
Liu, 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