Model text as corrective feedback in L2 writing: the role of working memory and vocabulary size
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Syed Muhammad Mujtaba
Syed Muhammad Mujtaba holds a Ph.D. in English Language Studies and has published in reputed international journals, such as
Reading & Writing Quarterly ,Assessing Writing , andForeign Language Annals . Currently, he is working as a Senior Assistant Professor at Bahria University, Karachi Campus. He has taught English to both undergraduate and graduate students. His research and teaching interests include L2 writing, language teaching pedagogies, and written corrective feedback.Tiefu Zhang earned his Ph.D. in Education from The University of Sydney in 2019 and is currently an Associate Professor of Applied Linguistics in the School of Foreign Languages at the University of Electronic Science and Technology of China. His recent publications on second language acquisition, second language writing, and EMI in higher education have appeared in journals such as System,
Journal of Second Language Writing , andAssessing Writing .
,
Shiman Mao
Shiman Mao is a Ph.D. student in the Faculty of Arts and Social Sciences at the University of Sydney. Her research interests include mobile-assisted language learning, second language writing, and second language acquisition. Her research has been published in the Journal of Second Language Writing.
Nisar Ahmed received an M.Phil. in English and has taught English to both undergraduate and graduate students. His research and teaching interests include L2 writing, discourse analysis, and corrective feedback.
Abstract
Recent research highlights model texts as a form of written corrective feedback (WCF) for enhancing L2 writing skills. This study, conducted at a South Asian university, assessed the impact of model texts on the argumentative writing skills of 71 undergraduate ESL students. Divided into treatment and control groups, assessments at various stages employed an analytic rubric and CALF metrics (complexity, accuracy, fluency, lexical richness). Additionally, regression analysis was used to gauge the effect of working memory capacity (WMC) and vocabulary size on the success of the method. The findings revealed that the treatment group exhibited significant improvements, particularly in vocabulary use and structural aspects of their writing. Both WMC and vocabulary size were found to influence the efficacy of model texts. This study underscores the potential of model texts in WCF and highlights the role of individual learner attributes in determining its effectiveness.
Funding source: China Foreign Language Education Fund
Award Identifier / Grant number: ZGWYJYJJ11A174
About the authors
Syed Muhammad Mujtaba holds a Ph.D. in English Language Studies and has published in reputed international journals, such as Reading & Writing Quarterly, Assessing Writing, and Foreign Language Annals. Currently, he is working as a Senior Assistant Professor at Bahria University, Karachi Campus. He has taught English to both undergraduate and graduate students. His research and teaching interests include L2 writing, language teaching pedagogies, and written corrective feedback.
Tiefu Zhang earned his Ph.D. in Education from The University of Sydney in 2019 and is currently an Associate Professor of Applied Linguistics in the School of Foreign Languages at the University of Electronic Science and Technology of China. His recent publications on second language acquisition, second language writing, and EMI in higher education have appeared in journals such as System, Journal of Second Language Writing, and Assessing Writing.
Shiman Mao is a Ph.D. student in the Faculty of Arts and Social Sciences at the University of Sydney. Her research interests include mobile-assisted language learning, second language writing, and second language acquisition. Her research has been published in the Journal of Second Language Writing.
Nisar Ahmed received an M.Phil. in English and has taught English to both undergraduate and graduate students. His research and teaching interests include L2 writing, discourse analysis, and corrective feedback.
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Research funding: This research work was funded by China Foreign Language Education Fund (ZGWYJYJJ11A174).
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/iral-2023-0242).
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