Towards Automated Analysis of Rhetorical Categories in Students Essay Writings using Bloom’s Taxonomy

Article Status
Published
Authors/contributors
Title
Towards Automated Analysis of Rhetorical Categories in Students Essay Writings using Bloom’s Taxonomy
Date
2023-3-13
Proceedings Title
LAK23: 13th International Learning Analytics and Knowledge Conference
Conference Name
LAK 2023: 13th International Learning Analytics and Knowledge Conference
Place
Arlington TX USA
Publisher
ACM
Pages
418-429
Language
en
ISBN
978-1-4503-9865-7
Accessed
13/12/2023, 19:18
Library Catalogue
DOI.org (Crossref)
Extra
Citation Key: iqbal2023 <标题>: 利用布鲁姆分类法对学生论文写作中的修辞类别进行自动化分析 <AI Smry>: A statistical difference between the associations of rhetorical categories in low-achieving, medium-achiever and high-achievers groups implies that rhetorical categories can be predictive of writing performance. Read_Status: New Read_Status_Date: 2025-11-10T07:26:25.059Z
Citation
Iqbal, S., Rakovic, M., Chen, G., Li, T., Ferreira Mello, R., Fan, Y., Fiorentino, G., Radi Aljohani, N., & Gasevic, D. (2023). Towards Automated Analysis of Rhetorical Categories in Students Essay Writings using Bloom’s Taxonomy. LAK23: 13th International Learning Analytics and Knowledge Conference, 418–429. https://doi.org/10.1145/3576050.3576112
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