Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Collaborative Writing | 1 |
| Electronic Publishing | 1 |
| Grades (Scholastic) | 1 |
| Grading | 1 |
| Natural Language Processing | 1 |
| Peer Acceptance | 1 |
| Readability | 1 |
| Reading Comprehension | 1 |
| Reading Instruction | 1 |
| Scores | 1 |
| Scoring | 1 |
| More ▼ | |
Source
| International Educational… | 1 |
Author
| Cai, Zhiqiang | 1 |
| Graesser, Arthur | 1 |
| Li, Haiying | 1 |
Publication Type
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textLi, Haiying; Cai, Zhiqiang; Graesser, Arthur – International Educational Data Mining Society, 2016
In this paper, we applied the crowdsourcing approach to develop an automated popularity summary scoring, called wild summaries. In contrast, the golden standard summaries generated by one or more experts are called expert summaries. The innovation of our study is to compute LSA (Latent Semantic Analysis) similarities between target summary and…
Descriptors: Peer Acceptance, Electronic Publishing, Collaborative Writing, Grading
