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Title: | Computerized Text Analysis: Assessment and Research Potentials for Promoting Learning |
Authors: | Lee, Hee-Sun McNamara, Danielle Bracey, Zoë Buck Liu, Ou Lydia Gerard, Libby Sherin, Bruce Wilson, Chris Pallant, Amy Linn, Marcia Haudek, Kevin C. Osborne, Jonathan |
Issue Date: | Jun-2019 |
Publisher: | International Society of the Learning Sciences (ISLS) |
Citation: | Lee, H., McNamara, D., Bracey, Z. B., Liu, O. L., Gerard, L., Sherin, B., Wilson, C., Pallant, A., Linn, M., Haudek, K. C., & Osborne, J. (2019). Computerized Text Analysis: Assessment and Research Potentials for Promoting Learning. In Lund, K., Niccolai, G. P., Lavoué, E., Hmelo-Silver, C., Gweon, G., & Baker, M. (Eds.), A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, 13th International Conference on Computer Supported Collaborative Learning (CSCL) 2019, Volume 2 (pp. 743-750). Lyon, France: International Society of the Learning Sciences. |
Abstract: | Rapid advancements in computing have enabled automatic analyses of written texts created in educational settings. The purpose of this symposium is to survey several applications of computerized text analyses used in the research and development of productive learning environments. Four featured research projects have developed or been working on (1) equitable automated scoring models for scientific argumentation for English Language Learners, (2) a real-time, adjustable formative assessment system to promote student revision of uncertainty- infused scientific arguments, (3) a web-based annotation tool to support student revision of scientific essays, and (4) a new research methodology that analyzes teacher-produced text in online professional development courses. These projects will provide unique insights towards assessment and research opportunities associated with a variety of computerized text analysis approaches. |
URI: | https://doi.dx.org/10.22318/cscl2019.743 https://repository.isls.org//handle/1/4500 |
Appears in Collections: | CSCL 2019 |
Files in This Item:
File | Size | Format | |
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743-750.pdf | 732.21 kB | Adobe PDF | View/Open |
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