Modelling the Synergy of Automated Writing Evaluation (AWE) and Peer Feedback: Indonesian L2 Learners’ Perspectives on Writing Quality

Abstract

AbstractThis study addresses the critical pedagogical challenge of integrating technological tools and human interaction within second language (L2) writing instruction. Grounded in socio-constructivist and self-regulated learning theories, this research aims to model the synergy between Automated Writing Evaluation (AWE) and peer feedback by examining how they influence perceived L2 writing quality through the psychological and behavioral mediators of writing self-efficacy and revision engagement. Employing a quantitative cross-sectional design, data were gathered from 65 undergraduate L2 learners using a validated survey instrument and analyzed via Partial Least Squares Structural Equation Modeling (PLS-SEM). The structural model evaluations reveal a pattern of full mediation, wherein the direct paths from both feedback inputs to writing quality are non significant. Crucially, AWE acts as an affective driver directly boosting writing self-efficacy, while peer feedback strongly drives revision engagement, which subsequently operates as the dominant predictor of perceived text quality. This study offers empirical novelty by establishing a balanced socio-cognitive feedback framework, suggesting that curriculum designers should adopt a blended feedback system where automated systems cultivate psychological readiness and human feedback drives deep behavioral execution.Keywords: Automated Writing Evaluation (AWE); L2 Writing Quality; Peer Feedback; Revision Engagement; Writing Self-Efficacy.