Abstract
Skillful essay writers successfully transform knowledge from multiple sources. However, when post-secondary writers draft essays after researching the articles, they often face challenges to engage in knowledge transforming, a complex process simultaneously involving reading comprehension, writing production and metacognitive monitoring (Bereiter & Scardamalia, 1987). We describe a two-facet methodological approach to model linguistic properties that distinguish knowledge-telling evidential sentences from knowledge- transforming ones in disciplinary argumentative writing. We collected and coded 40 post- secondary disciplinary argumentative essays based on an assigned argumentation framework and Bloom’s taxonomy (Sadker & Sadker, 2006). We use these coded argumentation schemes to develop a computational tool to generate writing analytics to scaffold writers towards more knowledge transforming processes.
| Original language | English |
|---|---|
| Title of host publication | Companion Proceeding of the 9th International Conference on Learning Analytics & Knowledge (LAK’19) |
| Editors | Christopher Brooks, Rebecca Ferguson, Ulrich Hoppe |
| Place of Publication | New York NY USA |
| Publisher | Society for Learning Analytics Research |
| Pages | 267-272 |
| Number of pages | 6 |
| Publication status | Published - 2019 |
| Externally published | Yes |
| Event | International Learning Analytics & Knowledge Conference 2019 - Arizona State University, Tempe, United States of America Duration: 4 Mar 2019 → 8 Mar 2019 Conference number: 9th https://lak19.solaresearch.org/ |
Conference
| Conference | International Learning Analytics & Knowledge Conference 2019 |
|---|---|
| Abbreviated title | LAK 2019 |
| Country/Territory | United States of America |
| City | Tempe |
| Period | 4/03/19 → 8/03/19 |
| Internet address |
Keywords
- Argumentation
- writing
- text analysis
- knowledge telling
- Knowledge transfer
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