INVESTIGATING THE REVISION PROCESS IN A WEB-BASED PEER REVIEW SYSTEM USING MACHINE LEARNING
University of Tartu, Centre for Academic Writing and Communication (ESTONIA)
About this paper:
            
          
           Appears in: 
EDULEARN15 Proceedings
           Publication year: 2015
Pages: 5616-5623
ISBN: 978-84-606-8243-1
ISSN: 2340-1117
Conference name: 7th International Conference on Education and New Learning Technologies
Dates: 6-8 July, 2015
Location: Barcelona, Spain
 
             Abstract:
In the teaching of writing, certain aspects of peer feedback on writing remain controversial; in particular, in the context of second language (L2) writing, there remain questions about how peer feedback supports the L2 writing process. (Liu & Sadler, 2003). 
Peer feedback can have a positive effect on second language writing (Lundstrom & Baker, 2009). Additionally, technology related research fields increasingly testify that learning to write benefits from peers communicating in a web-based environment for language learning (Matsuda et al., 2003; Hyland & Hyland, 2006). These studies report how computer mediated communication itself provides a rich learning experience for second language learners, but also highlight that different web-based platforms provide different results.	
	
This study investigates the effectiveness of one such web-based platform: SWoRD, a web-based peer review system.  The basic principles behind the development of web-based peer review systems are as follows: 
1) writing in higher education plays a significant role to develop content knowledge; 
2) it assists in organising writing assignments and reduces the workload of instructors; 
3) it provides students with an authentic audience to whom they give and from who they receive feedback; and 
4) it enables students to practice writing through constant revision for the purpose of learning how to write (Cho & Schunn, 2004). 
The aim of this study is to better understand how L2 learner-writers conduct peer feedback activities by looking at the types of feedback they provide and the factors that lead to the implementation of this feedback. A machine learning approach was used to predict how eight features, related to the peer feedback comments, performed on an L2 writing task amongst a group of first, second, and third year Bachelor students (N=43) from the department of Chemistry at the University of Tartu, Estonia. The results of this study indicate that peer feedback is effective amongst L2 writers using SWoRD web-based peer review system,  if feedback instances propose specific alterations and if more than one peer makes a reference to a similar aspect in the text that needs changing.
References:
[1] Cho, K., & Schunn, C. D. (2004). The SWoRD is mightier than the pen: Scaffolded writing and rewriting in the discipline. Advanced Learning Technologies, 2004. Proceedings. IEEE International Conference on, 545–549. 
[2] Crossley, S. A. (2013). Advancing research in second language writing through computational tools and machine learning techniques: A research agenda. Language Teaching, 46(02), 256-271.
[3] Hyland, K., & Hyland, F. (2006). Feedback on second language students’ writing. Language Teaching, 39, 83–101. 
[4] Liu, J., & Sadler, R. W. (2003). The effect and affect of peer review in electronic versus traditional modes on L2 writing. Journal of English for Academic Purposes, 2(3), 193–227. 
[5] Matsuda, P. K., Canagarajah, A. S., Harklau, L., Hyland, K., & Warschauer, M. (2003). Changing currents in second language writing research: A colloquium. Journal of Second Language Writing, 12(2), 151–179.Keywords:
 Web-based peer review systems, Machine Learning.