2018
DOI: 10.7575/aiac.alls.v.9n.4p.83
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Revision-mediated and Attention-mediated Feedback: Effects on EFL Learners’ Written Syntactic Accuracy

Abstract: Based on the literature, revision requirement (i.e., when students rewrite their whole text based on the teacher feedback) can perhaps be a necessary intermediate step towards the development of written accuracy because learners have more time to think about and process the corrections; however, some state drawing learner’s attention can be achieved by asking them to take time to look over the received feedback and carefully examine their errors. This quantitative quasi-experimental study, which followed a pre… Show more

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Cited by 3 publications
(4 citation statements)
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References 39 publications
(82 reference statements)
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“…To conduct the study, the following instruments were utilized: Student biodata information questionnaire, Quick Placement Test (QPT), class writing tasks, pretest, posttest, and delayed posttest. Further, in order to assess the syntactic accuracy, and to control for the differences in text length written by the participants, the following formula, which had also been used by Chandler (2003), Truscott and Hsu (2008), as well as Soltanpour and Valizadeh (2018) was used: [total number of syntactic errors/total number of words] × 100 to calculate a measure of errors per 100 words.…”
Section: Instrumentsmentioning
confidence: 99%
“…To conduct the study, the following instruments were utilized: Student biodata information questionnaire, Quick Placement Test (QPT), class writing tasks, pretest, posttest, and delayed posttest. Further, in order to assess the syntactic accuracy, and to control for the differences in text length written by the participants, the following formula, which had also been used by Chandler (2003), Truscott and Hsu (2008), as well as Soltanpour and Valizadeh (2018) was used: [total number of syntactic errors/total number of words] × 100 to calculate a measure of errors per 100 words.…”
Section: Instrumentsmentioning
confidence: 99%
“…Regarding the contribution of feedback to the revision of learners' work in higher education, the vast majority of research is related to academic writing, i.e., the writing of texts, essays, and scientific arguments (Alvarez, Espasa, & Guasch, 2012;Lam, 2013;Wakabayashi, 2013;Ruegg, 2015;Patchan & Schunn, 2016;Grigoryan, 2017;Suzuki, Nassaji, & Sato, 2019;Isnawati, Sulistyo, Widiati, & Suryati, 2019;Cui, Schunn, & Gai, 2021;Suci, Basthomi, Mukminatien, Santihastuti, & Syamdianita 2021;Han & Wang, 2021;Thi & Nikolov, 2021;Mujtaba, Reynolds, Parkash, & Singh, 2021;Huang, 2021;Alharbi, 2022;Van Meenen, Masson, Catrysse, & Coertjens, 2023), as well as eighteen studies on the subject of English as a foreign language (Yang & Meng, 2013;Nakatake, 2013;Wang, 2014;Huang, 2015;Yu & Lee, 2015;Lei, 2017;Tajabadi, Ahmadian, Dowlatabadi, & Yazdani, 2020;Li & Zhang, 2021;Cheng, 2022;Soltanpour & Valizadeh, 2018) and as a second language (Ferris, Liu, Sinha, & Senna, 2013;Razali & Jupri, 2014;Shintani, Ellis, & Suzuki, 2014;Bao, Sato, Leis, & Suzuki, 2016;Conijn, Zaanen, & Waes, 2019;Yamashita, 2021;Endley & Karim, 2022;Koltovskaia, 2020).…”
Section: Discussionmentioning
confidence: 99%
“…A combination of audio-visual and text-based feedback has a significant impact on text revisions (Grigoryan, 2017). Corrective and critical feedback also proves effective in stimulating learners to revise their work (Ferris, Liu, Sinha, & Senna, 2013;Razali & Jupri, 2014: Shintani, Ellis, & Suzuki, 2014Soltanpour & Valizadeh, 2018;Sigott, Fleischhacker, Sihler, & Steiner, 2019;Suzuki, Nassaji, & Sato, 2019;Isnawati, Sulistyo, Widiati, & Suryati, 2019;Yamashita, 2021;Mujtaba, Reynolds, Parkash, & Singh, 2021;Cheng et al, 2021;Endley & Karim, 2022). Thorough feedback is highly appreciated by learners (Wilken, 2018), as well as specific feedback (Yu and Lee, 2015;Lei, 2017;Huang, 2021) and peer feedback confers significant benefits to their revisions (Wakabayashi, 2013;Wang, 2014;Yu & Lee, 2015;Ruegg, 2015;Patchan & Schunn, 2016;Lei, 2017;Tajabadi, Ahmadian, Dowlatabadi, & Yazdani, 2020;Pham, Huyen, & Nguyen, 2020;Abri, 2021;Cui, Schunn, & Gai, 2021;Li & Zhang, 2021;Huang, 2021;Van Meenen, Masson, Catrysse, & Coertjens, 2023).…”
Section: Discussionmentioning
confidence: 99%
“…In addition, to calculate the syntactic complexity, Lu's (2010) web-based L2 Syntactic Complexity Analyzer was employed. Further, in order to assess the syntactic accuracy, and to control for the differences in text length written by the participants, the following formula, which had also been used by Chandler (2003), Truscott and Hsu (2008), as well as Soltanpour and Valizadeh (2018), was used: [total number of syntactic errors/total number of words] × 100 to calculate a measure of errors per 100 words.…”
Section: Instrumentsmentioning
confidence: 99%