Abstract
Effective revision necessitates substantial self-regulation in managing the underlying sub-processes and in drawing on relevant knowledge and strategies. Unskilled writers, especially when they have to write in a second/foreign language (L2/FL), might find revision difficult to execute. This study leveraged on the Self-Regulated Strategy Development (SRSD) revision instruction that targeted the knowledge about evaluation criteria for writing to help students to learn effective revision. It employed a quasi-experimental design, involving three intact classes of undergraduate students as participants (N = 102). They were assigned into three instructional conditions: SRSD revision instruction using genre-specific criteria, SRSD revision instruction using generic criteria, and regular instruction without SRSD. The instructional effects on students’ text revisions and written text quality were examined. Analyses of the revisions identified in participants’ pre- and posttest written texts suggested that both SRSD groups made more text-improving, meaning-changing re-visions and more revisions involving larger segments of texts compared to the comparison group. The analyses of writing test scores indicated that, in general, both SRSD conditions were more effective in helping participants to improve text quality than the comparison condition. The treatment groups produced more reader-oriented writing and made greater gains in the scores for content than the comparison group. Overall, this research provides initial evidence for the effectiveness of SRSD in facilitating the development of students’ abilities to revise and in improving their writing quality in an English-as-a-foreign-language (EFL) context.
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The research is funded by a joint doctoral scholarship awarded to Jing Chen by The University of Auckland and the China Scholarship Council, Ministry of Education of China (UoA2016/CSC21).
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Chen, J., Zhang, L.J. & Parr, J.M. Improving EFL students’ text revision with the Self-Regulated Strategy Development (SRSD) model. Metacognition Learning 17, 191–211 (2022). https://doi.org/10.1007/s11409-021-09280-w
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DOI: https://doi.org/10.1007/s11409-021-09280-w