Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

April 28, 2023


Pages


DOI

Article

An analysis of time commitment for college students to online English writing and peer assessment learning

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Authors

Meng Wu Affiliation:
School of Foreign Languages Beijing Technology and Business University, Beijing, 100048, China


Abstract

Online English writing and peer assessment have always occupied an important place in the assessment of composition at the basic education level as an important writing style and assessment tool. Therefore, this paper constructs the IOA-English analysis model based on the intelligent optimization algorithm as the theoretical basis. An in-depth study of online English writing patterns and the time devoted to them, and the intensity and effectiveness of peer assessment among college students. The results of the study are as follows: the computational analysis shows that the time required for the pre-writing preparation stage is 5-10 minutes, with a difficulty factor of 0.3. The final draft submission phase required the least amount of time, 3-7 minutes, with a difficulty factor of only 0.1. The writing revision stage, the most important stage, takes 10-15 minutes and has a difficulty factor of 0.6. The time for the writing revision phase can be divided into two parts: the first part is the time for tasting the model essay, which is about 3-8 minutes. The second part is the writing and revision time, which is about 12-17 minutes. More than 91% of the students were aware of the importance of peer assessment and were brave enough to express their opinions in cooperative learning and to take care of each other’s learning needs in peer assessment.


Keywords

English writing, Peer-to-peer assessment, Pattern analysis, Intelligent optimization algorithm, Online writing, 62P25


Citation

Wu, M. (2023). An analysis of time commitment for college students to online english writing and peer assessment learning. Applied Mathematics and Nonlinear Sciences, 8(1). https://doi.org/10.2478/amns.2023.1.00052

Published by: Engineering Journals

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