Content area
The present study employs a cross-lagged panel design to investigate the intricate interplay between peer feedback and self-regulation and their influences on writing performance. Data were collected through surveys and writing tests conducted twice, involving a total of 249 students studying English as a foreign language (EFL) at a university in China. The results illuminate positive correlations among self-regulation, peer feedback, and writing performance, extending across a longitudinal perspective. These findings underscore the pivotal role of self-regulation in shaping the dynamics of peer feedback, subsequently influencing writing outcomes over time. Notably, peer feedback emerges as a critical longitudinal mediator in the relationship between self-regulation and writing performance. This study distinguishes itself through its innovative approach, which integrates peer feedback and self-regulation in the realm of writing over an extended period. The encouraging outcomes underscore the potential of this pioneering methodology in enriching the landscape of peer feedback through self-regulation, and, ultimately, writing development. The innovative, pragmatic, and scalable nature of this approach further enhances its promise for both research and practical application.
Introduction
While peer feedback and self-regulation are widely studied in foreign language (FL) writing, their bidirectional relationship remains underexplored. According to sociocognitive theory (Bandura, 1986), peer feedback fosters observational learning, while self-regulation reflects proactive agency. Control-value theory (Pekrun, 2006) further links them: Feedback quality affects learners’ perceived control (self-efficacy), which drives self-regulation. Peer feedback offers external input, yet its impact depends on learners’ self-regulatory capacity to process and apply it. Conversely, self-regulated learners may actively seek higher-quality feedback. A cross-lagged analysis bridges this gap by examining how these constructs mutually influence each other over time, offering insights into the mechanisms behind effective FL writing development.
Peer feedback is a crucial element in self-regulated online learning (Clayton Bernard & Kermarrec, 2025), while learners’ self-regulatory practices are integral to fostering effective foreign language writing skills during synchronous online English learning (Molnar, 2025; Teng & Pan, 2024). Self-regulated learning involves learners actively constructing knowledge by setting writing goals, managing their learning process, and evaluating their performance in relation to those goals (Wilson et al., 2023). By setting goals, monitoring progress, applying feedback, managing emotions, and engaging in metacognitive reflection, learners maximize the benefits of peer feedback, leading to significant improvements in their writing skills (Nicol & Macfarlane-Dick, 2006). This argument recognizes the significance of self-regulation in enabling learners to process feedback for their own foreign language writing processes, ultimately enhancing their writing proficiency (Fan & Xu, 2020; Zhao, 2010). However, as Hyland and Hyland (2019) noted, the mechanisms driving peer feedback’s effectiveness remain partially unexplained. A critical gap lies in understanding how learners’ self-regulatory behaviors, such as initiating, directing, and persisting in the writing process, mediate feedback utilization (Xiao & Yang, 2019). Investigating this interplay between self-regulation and peer feedback could thus unravel the dynamics that shape successful FL writing development.
Self-regulation holds a crucial role in the realm of FL writing (Teng et al., 2022). It is also evident that peer feedback can influence self-regulatory practices (Xiao & Yang, 2019), and, conversely, self-regulation can also exert an impact on the peer feedback process (Yang & Zhang, 2023). Examining the interplay between peer feedback and learners’ self-regulatory practices, and their resulting writing outcomes, is imperative for optimizing instructional strategies and gaining a deeper understanding of the dynamics within FL writing classrooms. The current study endeavors to bridge this gap by focusing on exploring the reciprocal relationship between peer feedback and self-regulation through a cross-lagged panel design. At the same time, their impacts on writing performance are also investigated. By delving into self-regulation at various stages of giving and receiving feedback and throughout the writing process from a longitudinal perspective, this study not only contributes to the theoretical foundations of feedback but also provides an in-depth understanding of the intricate relationship between peer feedback, self-regulation, and the writing performance of EFL students. This research augments the existing body of knowledge on peer feedback and enhances our comprehension of the complex interplay between self-regulation, peer feedback, and writing outcomes in the FL writing classroom.
Literature review
Theoretical frameworks
The theoretical foundation is rooted in Vygotsky’s sociocultural theory (SCT) (1978), particularly the concept of the zone of proximal development (ZPD). The ZPD represents a dynamic, individualized space where learners can develop their skills through scaffolded collaboration, emphasizing open-ended problem-solving over rote procedures to maximize learning potential (Mcleod, 2023). SCT highlights the intricate interplay between social and cognitive dimensions in language learning, asserting that interactive activities shape language processing through a combination of individual behavior, personal factors, and environmental characteristics (Van Meter & Stevens, 2000). This reciprocal process suggests that individual cognition can be influenced by the environment, while the environment, in turn, can be shaped by individual behavior. Within the ZPD, learners can effectively develop their skills with the support of their peers, making it a critical framework for understanding peer feedback dynamics.
A central focus of this study is the nexus between peer feedback and self-regulation. Peer feedback, as a socially mediated process, serves as a catalyst for self-regulatory behaviors by externalizing internal thought processes and enabling learners to compare, evaluate, and adjust their writing strategies. Collaborative writing tasks within the ZPD scaffold learners’ transition from other regulation (relying on peers) to self-regulation (independently applying feedback principles). This process fosters essential self-regulatory capacities, such as goal setting, monitoring, and emotional control, which are core tenets of Zimmerman’s (2002) self-regulation model.
The study also highlights the bidirectional nature of the peer feedback and self-regulation relationship. As learners internalize feedback norms, they enhance the quality of their future social exchanges, creating a positive feedback loop that sustains self-regulatory growth. Environmental structures, such as training protocols and iterative feedback cycles, play a crucial role in modulating this reciprocity. By positioning peer feedback as a transformative practice that coevolves with learners’ self-regulatory capacities, the study advances a dialectical model of L2 writing development. This model not only enriches the learning experience but also empowers students to actively shape their learning process, ultimately fostering sustainable writing proficiency.
Self-regulation and writing
According to Zimmerman and Risemberg (1997), the concept of self-regulation (SR) in writing necessitates a comprehensive consideration that extends beyond cognitive aspects to encompass social, motivational, and behavioral processes. Writing is not merely an exhibition of cognitive ability; it is a social cognitive activity where authors must be attuned to their readers’ expectations and remain prepared to revise their drafts to achieve effective communication. According to the writer(s)-within-community model (WWC), student writers draw on oral language knowledge stored in long-term memory to carry out the processes involved in writing (Graham et al., 2021). Within the SR framework, this notion encompasses cognitive, emotional, motivational, and behavioral dimensions that enable learners to adapt their actions and goals in response to evolving circumstances (Dörnyei, 2005). In essence, SR represents a multifaceted construct that encompasses cognition, metacognition, social behavior, and motivational control (Zimmerman, 2011). Pintrich (2004) proposed four key aspects essential to SR: learner agency, learner control, goal orientation, and strategy mediation. Consequently, the self-regulation process can be perceived as an array of actions, such as monitoring, directing, and regulating, all aimed at achieving effective writing (Ziegler et al., 2011; Zimmerman, 2002). To gain a deeper insight into self-regulated learning, it is imperative to focus on fostering learner autonomy, cultivating metacognitive awareness, promoting a growth mindset, and establishing efficient feedback mechanisms. The purpose is to create a supportive atmosphere for learning to write, empowering students to take on responsibilities for their writing and navigate the ever-evolving demands within the writing landscape. Thus, SR in writing encompasses not only cognitive but also social, motivational, and behavioral elements, offering a comprehensive understanding of self-regulated learning in the context of writing.
Numerous empirical studies have underscored the significance of SR in foreign language writing, with some key investigations shedding light on the predictive effects of SR in EFL writing (Bai & Wang, 2023; Negretti, 2012; Teng & Huang, 2019; Teng et al., 2022). Particularly, the research by Teng et al. (2022) revealed substantial predictive effects of various strategies, including writing planning, goal-oriented monitoring, goal-oriented evaluation, emotional control, memorization, and metacognitive judgment, on EFL writing outcomes. They also emphasized the importance of considering gender and grade differences in the utilization of self-regulated strategies in writing. Negretti (2012) is a qualitative study that adopted a constructivist grounded theory approach, examining a semester’s worth of student journals. The findings highlighted how students with conditional metacognitive awareness were able to adapt their writing strategies uniquely and personally, underscoring the intricate relationship between metacognition and self-regulation in writing. Bai and Wang (2023) introduced the concept of self-regulated reading to write (R2W), which involves learners proactively acquiring content, rhetorical features, and conventions from reading through the use of various strategies. This approach serves as an effective bridge between reading and writing, ultimately enhancing writing competence. The self-regulated R2W strategies, including mining reading, writerly reading, cognitive strategies, purposive reading, recalling while writing, and peer revision reading, had a substantial impact on the writing competence of primary school students. These studies collectively contribute to a deeper understanding of the role of self-regulation in foreign language writing and offer valuable insights into enhancing writing skills among learners in a foreign language context.
Recent research in the field of self-regulation in writing has yielded insightful findings. Zhang and Zhang (2024) explored how different self-regulated learning (SRL) writing strategy profiles relate to individual differences such as language aptitude, working memory, writing achievement goals, L2 grit, and writing self-efficacy. Their findings highlighted significant differences across the SRL profiles, particularly concerning writing achievement goals, L2 grit, and writing self-efficacy, while language aptitude, working memory, and performance-avoidance goals showed less variation. Teng, F. (2024) explored the mediating roles of self-efficacy belief and emotional adjustment on the relationship between social support and anxiety related to online English learning. A total of 585 university students in mainland China participated in this study. Structural Equation Modelling (SEM) was adopted to explore the relationships among the four variables. Results lent support to the mediating role of self-efficacy belief on the effects of social support on foreign language learning anxiety. Teng, L. (2024) investigated the role of motivational beliefs and self-efficacy in self-regulation strategies among 389 undergraduate students from four universities in Mainland China. Participants completed questionnaires measuring motivational beliefs (including extrinsic and intrinsic goal orientation, task value, and control of learning belief), self-efficacy (linguistic, performance, and self-regulatory efficacy), and self-regulation strategies (cognition, metacognition, social behavior, and motivational regulation). The study’s multiple regression analyses revealed that motivational beliefs significantly predicted self-regulation strategies, with task value and intrinsic goal orientation being key predictors of nine sub-factors of self-regulation strategies. Additionally, self-efficacy emerged as a strong predictor of metacognitive, cognitive, and motivational regulation strategies. Shen and Tao (2025) examine the impact of metacognitive strategies (planning, monitoring, and evaluating) and AI-based writing self-efficacy on reducing writing anxiety among a total of 193 EFL learners in Chinese AI-assisted writing contexts. Using structural equation modeling, the findings reveal that both metacognitive strategies and AI-based writing self-efficacy negatively predict writing anxiety. Additionally, AI-based writing self-efficacy fully mediates the relationship between planning strategies and writing anxiety and partially mediates the relationships with monitoring and evaluating strategies.
Armed with the knowledge outlined above, learners are equipped to engage in the crucial processes of planning, monitoring, and regulating external distractions while developing their writing skills. SRL is a comprehensive and multifaceted concept that encompasses various dimensions, including metacognition, emotions, social factors, and specific learning contexts. One plausible explanation for why SRL predicts improvements in writing is that self-regulated learners possess not only the “will” in terms of academic motivation but also the “skill” represented by learning strategies. They efficiently employ a wide array of self-regulated learning (SRL) strategies to effectively manage their thoughts, behaviors, emotions, and environments, all in pursuit of predetermined writing goals (Zimmerman, 1989). Moreover, self-regulation operates within a continuous cycle of self-initiations, self-observations, self-judgments, and self-reactions (Bandura, 1986). In the quest to become self-regulated, learners establish personal goals, actively engage in academic behaviors, invest efforts, and manage their learning environment (Graham et al., 2021). During the writing process, the learners could conduct ongoing monitoring of their learning progress, evaluation of their performance, and making necessary adaptations to ensure they reach their objectives.
Peer feedback and writing
In recent years, there has been a growing focus among writing researchers on the pivotal role of peer feedback, which goes by various names such as “peer response,” “peer review,” “peer assessment,” or “peer editing.” Peer feedback is a widely used approach in academic writing that offers several benefits. One of its primary merits is that it fosters collaborative learning (Zhang, 2025) and critical thinking (Chen et al., 2024). According to Finkenstaedt-Quinn et al. (2024), engaging in peer review helps students improve not only their ability to critique others’ work but also their own writing skills, as they develop a better understanding of writing conventions and audience expectations. The peer feedback practice involves the exchange of feedback, which can be conveyed either in written or oral form, through pair or group work (Liu & Hansen, 2002). In this collaborative approach, learners not only act as sources of information but also actively participate in providing commentary and critique on one another’s work. This unique dynamic allows students to assume roles akin to teachers, tutors, or editors within the learning-to-write process (Nicol & Macfarlane-Dick, 2006). The process of peer feedback encompasses not only the sharing of observations and recommendations but also the interactive and collaborative aspects of peer interaction. The product of peer feedback, on the other hand, comprises the tangible feedback or comments provided by peers. Peer feedback serves as a valuable tool for promoting learning and enhancing writing skills. It plays a multifaceted role in helping learners better understand effective writing strategies, recognize their strengths and weaknesses in writing (Tsui & Ng, 2000), and subsequently improve their writing skills based on the scaffolded peer comments (Hyland & Hyland, 2006). Additionally, peer feedback has the potential to raise awareness of the intended audience and genre, stimulate revisions, and enhance the overall quality of the writing (Berggren, 2015).
Further benefits of peer feedback were also noted in other studies. For example, peer feedback represents a shift from a product-oriented emphasis to a more process-oriented approach in writing classrooms. The active exchange of ideas among students within this framework motivates meaningful opportunities for discussion and collaboration (Lee, 2020) and encourages critical thinking by entrusting students with responsibility for their own learning (Zhan, 2021). This change in focus from the final written product to the broader writing process characterizes the essence of process-oriented writing classrooms. Peer feedback thus plays a pivotal role in facilitating this approach, promoting a holistic view of writing education that encourages students to actively engage in their own learning and development.
Recent research has shed light on the role of peer feedback in writing. Huisman et al. (2019) synthesized the findings of 24 quantitative studies concerning higher education students’ academic writing performance following peer feedback. The results underscored the significant impact of peer feedback, as it led to substantial improvements in writing compared to control groups without such feedback. One of the most profound benefits of peer feedback lies in its formative nature, providing learners with opportunities for collaboration with more proficient peers. Wu and Schunn (2023) investigated peer feedback in a sample of 367 advanced placement students, who participated in assignments involving peer assessment rubrics. Results indicated that constructive activities, such as providing explanations and revising work after receiving feedback, were consistently linked to learning improvements. In contrast, simply receiving feedback without making changes, or only implementing specific suggestions, did not show the same benefits. Noroozi et al. (2023) explored the effectiveness of an online-supported peer feedback module with 330 students from various bachelor and master courses. In this module, students wrote argumentative essays on controversial topics, provided feedback to peers, and revised their essays based on the feedback received. Data collected included initial essays, peer feedback, and revised essays, along with a learning satisfaction questionnaire. The findings demonstrated that the online-supported peer feedback module effectively enhanced the quality of students’ argumentative essays. Li (2025) emphasized the value of incorporating peer support into self-regulated strategy development (SRSD) instruction, demonstrating its effectiveness with a study involving 136 11th-grade students in China. The students who received SRSD instruction with a peer-support component produced a higher frequency of high-quality texts compared to those who participated in SRSD instruction without peer support. Peer collaboration during the self-regulated strategy development process enhanced students’ understanding of planning, strengthened their perseverance in composing informational texts, and led to better writing outcomes. Zhan and Teng (2025) demonstrated the superior benefits of asynchronous digital feedback in a sample of 268 university students in China. Compared to traditional face-to-face peer review, Chinese EFL students who received feedback through computer-mediated channels showed significantly greater improvement not only in their writing performance but also in their self-efficacy and ability to self-regulate their learning.
However, peer feedback also has weaknesses. The quality of feedback can vary significantly depending on the skill level and motivation of the peers involved. Hyland and Hyland (2006) argue that students may lack the expertise to provide constructive or accurate feedback, which can lead to misunderstandings or unhelpful suggestions. Although teachers can offer detailed, targeted, and accurate feedback that addresses specific weaknesses in a student’s writing, ensuring alignment with academic standards (Ferris, 2003), teacher feedback can be perceived as overly authoritative, which may discourage students from engaging critically with the feedback or developing their own voice in writing (Zhang & Hyland, 2023). Peer feedback, which promotes active engagement and collaboration, shall be used for allowing students to learn by evaluating others’ work and reflecting on their own (Zhang & Hyland, 2023).
In summary, the above studies collectively highlight the multifaceted nature of peer feedback and its potential to significantly enhance writing skills when properly implemented. They point to the need for educational strategies that foster not only the technical aspects of feedback but also the emotional and cognitive engagement of students, including self-regulation.
Peer feedback and self-regulation
Peer feedback is related to self-regulation. Nicol and Macfarlane-Dick (2006) emphasized the connection between peer feedback and self-regulation. Self-regulation involves the act of actively managing one’s own learning to achieve growth, particularly within the context of peer feedback activities. This self-regulation process encompasses setting learning goals, managing resources, and investing efforts for feedback. It is worth noting that more self-regulated learners tend to possess a heightened sense of self-efficacy, enabling them to recognize their strengths and weaknesses. This, in turn, motivates them to actively seek feedback as a means of improving their writing skills (Ma, 2023). This underscores the interconnectedness of self-regulation and peer feedback in the learning process. Professional writers may employ unique strategies to create conducive social and physical environments for writing. Additionally, they utilize various behavioral and cognitive techniques to generate and sustain positive emotions and motivation, effectively leveraging feedback in the process.
Empirical findings also supported the role of self-regulation in peer feedback. Ma (2023) explored how self-regulation in writing interacts with peer feedback. Self-regulation in writing involves the self-initiated management of thoughts, emotions, and behaviors aimed at enhancing one’s writing skills (Zimmerman & Risemberg, 1997). This process includes three key sub-processes that enable student writers to generate, seek, process, and utilize feedback effectively. As they monitor their writing progress, students often provide themselves with feedback to identify and address potential issues in their work. Importantly, they may also seek external feedback on areas they find challenging or unsatisfactory, using this feedback to inform their self-assessment (Truscott, 2023). Based on this self-evaluation, students can make necessary adjustments to align their writing with desired standards. Leow (2023) provides a cognitive perspective on the impact of corrective feedback—whether oral or written—on second language (L2) development. His Feedback Processing Framework suggests that feedback serves as essential input that L2 learners must process. The extent to which this feedback is processed depends on the learners’ prior knowledge. Cognitive processes such as metacognition, activation of prior knowledge, hypothesis testing, and rule formulation play a crucial role in determining how feedback is processed by L2 learners, highlighting the role of self-regulation in the feedback processing process.
Researchers also explored the role of peer feedback in self-regulation. Hawe and Dixon (2017) identified the elements of peer feedback that promote self-regulation among students. These elements include setting clear learning goals, providing examples, implementing activities that elicit evidence of learning, engaging in dialogical interactions, conducting peer reviews, and offering feedback on both current understanding and task-related processes. Lam (2015) highlighted the role of student-generated feedback in supporting self-regulation. This form of feedback enhances students’ understanding of assessment criteria and motivates them to delve into subject-matter knowledge. It reinforces the idea that feedback and self-regulation are intricately intertwined aspects of a more comprehensive learning process. Self-regulated learners not only receive and interpret external feedback but also can produce their own feedback, applying it effectively to achieve their learning objectives (Boekaerts & Corno, 2005). Xiao and Yang (2019) presented findings derived from classroom observations and interviews with teachers and students in a foreign language secondary school. The results indicated that under the guidance of their teachers, students actively engaged in peer assessment and appeared to be evolving into self-regulated learners. It was observed that both skilled and less-skilled self-regulators exhibited varying levels of engagement with teacher-written feedback. Importantly, the engagement of students in the feedback process significantly influenced their writing self-regulation and outcomes.
Armed with the above findings, it is not surprising that skilled and less-skilled self-regulators displayed differing degrees of involvement across cognitive, behavioral, and affective dimensions, underscoring the importance of peer feedback activities in deepening their understanding and honing self-regulation skills. In a recent study from the self-regulation perspective (Teng & Ma, 2024), a total of 708 students from a Chinese university were involved. They aimed to address a gap in understanding by focusing on two main objectives: first, to develop a scale for assessing metacognition-based student feedback literacy, and, second, to explore how different components of this scale predict academic writing performance. The findings underscored the importance of metacognitive awareness and skills in student feedback literacy. It demonstrated that elements such as feedback-related strategies in participation, motivation, feedback-related monitoring strategies, and strategy knowledge have significant predictive effects on the academic writing performance of EFL learners. Hence, peer feedback activities play a pivotal role in nurturing writing self-regulation, and writing self-regulation enables students to foster their growth as writers by actively engaging in the processes of giving and receiving feedback.
Rationale and research questions
Although existing research has established a link between learners’ engagement in peer feedback and their writing performance (Fan & Xu, 2020), and self-regulation and writing (Bai & Wang, 2023), the interplay between peer feedback, self-regulation capacity, and writing over time remains an area of limited exploration. In particular, it is essential to explore the mediating role of peer feedback on self-regulation and writing performance. Exploring the mediating role of peer feedback addresses a gap in the existing literature regarding the temporal dynamics of the learning-to-write processes. Previous studies have often focused on the immediate effects of peer feedback on writing performance (Fan & Xu, 2020), but few have considered how this interaction evolves over time and influences self-regulation (van den Boom et al., 2007; Yang & Zhang, 2023). By employing a cross-lagged panel design, the present study aims to provide a more comprehensive picture of the developmental trajectory of learners’ writing proficiency and self-regulatory capacities while considering the role of peer feedback, offering valuable insights into how educators can better support students in becoming autonomous, reflective, and effective writers.
The first purpose relates to a need to explore how peer feedback, self-regulation, and writing performance are interrelated at two different assessment time points. This inquiry provides a foundational understanding of how these elements interact at specific moments in time, capturing changes and developments in learners’ abilities and strategies. The second purpose focuses on the potential longitudinal mediation role of peer feedback in the relationship between self-regulation and writing performance. Investigating this mediation role can reveal the mechanisms through which peer feedback impacts writing outcomes. This is a necessary step in facilitating further thinking on whether feedback not only influences directly writing skills but also enhances learners’ ability to regulate their learning processes over time (Hattie & Timperley, 2007).
To address these purposes, the present study employs a cross-lagged panel design to delve into this intricate relationship and shed light on the dynamics that influence learners’ development in writing (see the hypothesized model in Fig. 1). The study aims to answer the following research questions:
How are peer feedback, self-regulation, and writing performance related at the two assessment time points?
What is the possible longitudinal mediation role of peer feedback on the relationship between self-regulation and writing performance?
[See PDF for image]
Fig. 1
Hypothesized cross-lagged panel regression model
Method
Participants
The study involved 268 first-year students at a Chinese university. After excluding cases with missing data, the final dataset comprised 249 students, consisting of 138 Males and 131 females. English was considered a foreign language for these participants, who pursued various Majors in fields Like business, marketing, and other disciplines. They had a minimum of 6 years of English language learning experience. The students voluntarily participated in the study and provided informed consent by signing a form that clearly explained the research’s purpose. In addition to gathering demographic information such as age, gender, and years of learning experience, the participants were also queried about their previous exposure to peer feedback in the context of English writing. The responses indicated that they had not previously engaged in peer feedback during their English writing classes. It is worth noting that these students were primarily accustomed to teacher-led explanations for their writing, and writing constituted only a portion of their English language learning, which was primarily delivered through top-down teacher instruction. A noteworthy feature of their EFL learning was the emphasis on test-oriented assessment.
Instruments
The data collection process included the completion of two questionnaires related to writing self-regulation and feedback handling. Additionally, the students took a writing test to assess their writing performance. The reliability of these instruments, detailed in the results section, indicated acceptable reliability.
Writing self-regulation
The survey assessing writing self-regulation was adapted from existing tools commonly used for measuring self-regulated capacity or metacognitive writing strategies, as previously established in research (e.g., Schraw & Dennison, 1994; Teng, 2020; Teng, L & Zhang, 2016). These writing strategies were designed to capture three key dimensions of self-regulated capacity: Planning (P), Monitoring (M), and Evaluating (E). The Planning dimension, comprising items 1–7, was intended to assess how well students could efficiently plan and organize their writing efforts. These items focused on promoting effective planning and organization skills in writing. The Monitoring dimension, encompassing items 8–12, aimed to gauge students’ ability to Maintain focus during the writing process. It assessed their use of effective writing strategies, the ability to track progress, and the adherence to their initial plan while writing. The Evaluating dimension, made up of items 13–18, was designed to explore students’ practices in engaging with self-assessment, reflection, and revision after completing a writing task. Collectively, the 18 items in this survey were intended to capture the techniques employed by students to plan, monitor, manage, and regulate their cognitive resources in addressing the challenges of the writing process.
Feedback handling
The feedback handling scale used in the present study was adapted from previous research (Lee & Evans, 2019; McConlogue, 2015; Zhan, 2022). It encompasses two distinct dimensions: giving and receiving feedback. The dimension of receiving feedback (items 1–6) aimed to assess learners’ practices and perceptions concerning the processing of feedback they receive, with the ultimate goal of improving their writing skills. This part of the scale delved into how students handle and make use of feedback they receive from peers to enhance their writing abilities. On the other hand, the dimension of giving feedback (items 7–14) sought to explore learners’ practices and perceptions in the context of providing feedback to their peers during the writing process. It examined their approaches and attitudes toward offering constructive feedback to their fellow students. In essence, by examining both the receiving and giving of peer feedback, the study aimed to gain insights into learners’ perceptions, competencies, and practices related to the process of giving and receiving feedback in the context of writing.
Writing test
The writing assessment used in the present study was based on the academic writing component of the IELTS (International English Language Testing System) exam. The task involved crafting an argumentative essay, with the requirement to write a minimum of 250 words on the topic “Does boredom lead to trouble?” This assessment aimed to evaluate learners’ proficiency in several critical areas, including gathering and presenting essential information, formulating and justifying a coherent opinion, identifying and addressing key issues, and defending their stance with well-supported arguments and evidence. Argumentative essays are a valuable exercise for assessing language proficiency and critical thinking skills. The chosen topic, based on five teachers’ comments, is particularly intriguing, as it prompts students to explore the relationship between idleness and potential negative outcomes. By assessing learners’ performance in this academic writing task, the study could gain valuable insights into their ability to express complex ideas, build logical arguments, and use language effectively to communicate their thoughts. Overall, the assessment serves as a tool to measure their skill in constructing and defending an argument in a formal academic context, a crucial skill for academic success and beyond.
Scoring system
In the surveys, a 7-point Likert scale was employed, with responses ranging from 1 (indicating “not at all true of me”) to 7 (representing “very true of me”). The mean scores obtained from these survey items served as indicators of the participants’ degree of agreement with the statements, reflecting their perceptions, beliefs, or attitudes pertaining to the topic under investigation. The scoring system utilized for the writing test was aligned with both the university’s writing rubric requirements and the criteria set by the IELTS examination. It covered various evaluation criteria for each section of the test, including task achievement, coherence and cohesion, lexical resource, organization, punctuation, and grammatical range and accuracy. This scoring system was designed to offer a comprehensive assessment of the students’ writing abilities. Each of these components was graded on a scale of up to 4 points, allowing for a detailed and nuanced evaluation of their performance. Consequently, the total possible score for the writing test was 24 points. The adoption of this particular scoring system, which adhered to the university’s writing rubric standards and was consistent with the established IELTS writing criteria, aimed to provide a reliable and consistent measure of their writing proficiency, aligning with recognized standards and expectations.
The evaluation of the writing tests involved the voluntary participation of three doctoral students. In order to maintain the anonymity of the participants, their identities were kept confidential. To ensure a uniform and consistent understanding of the evaluation criteria and the application of the university’s writing rubrics, these raters engaged in a dedicated training session. This training involved the review and scoring of sample tests, facilitating the development of a shared understanding of the evaluation process. The initial assessment was carried out independently by the first two raters. Remarkably, their evaluations demonstrated a high level of agreement, with an inter-rater reliability rate of 93.5% for the pretest and 91.6% for the posttest. In cases where discrepancies emerged in their assessments, the third rater was consulted to provide their perspective. Through discussions regarding the contested items and subsequent agreement on the majority consensus, the raters ensured that the final scores accurately reflected a balanced and well-informed judgment. This rigorous and collaborative process significantly contributed to the overall fairness, reliability, and validity of the rating system for the writing test.
Procedures
All the students who participated in the study filled out the questionnaires online at the commencement of the writing course in which they were enrolled. It took approximately 15 min for the participants to complete these questionnaires and around 40 min to complete the essay-writing task. After a full semester of learning, the learners were once again requested to complete the questionnaires and the writing test. Peer feedback activities were incorporated in each lesson. Students were given clear guidelines for both giving and receiving feedback. Students participated in role-playing exercises to practice giving and receiving feedback, building their confidence and familiarity with the process. After each session, the instructor reviewed a sample of student feedback and offered additional comments to enhance its quality.
The questionnaires were thoughtfully presented in a bilingual format, offering both Chinese and English versions to cater to the varying language comprehension levels of the participants. The instructions for the writing test were provided in Chinese, and the participants composed their essays using traditional paper and pencil methods. This approach aimed to create an environment that was comfortable and familiar to the students.
Data analysis
In this research, we applied a cross-lagged analysis technique to construct a structural equation model (SEM) to explore the relationships among the examined variables. The cross-lagged model is a commonly used tool in longitudinal studies that lack experimental conditions. It helps uncover and analyze the reciprocal influences between multiple variables over time (Selig & Little, 2012). This approach allows us to estimate the strength of the effects each variable has on the others and examine how these relationships evolve. To perform the analysis, we utilized Mplus 8.0 (Muthén & Muthén, 2012) and employed the maximum likelihood (ML) estimation method to calculate model parameters.
Results
How are peer feedback, self-regulation, and writing performance related at the two assessment time points?
Descriptive statistics
Table 1 Coefficient effects of the examined modelEstimateSECRPStandardized coefficientMain paths in the model WPt1 → WPt20.697.05014.053***0.667 SRt1 → SRt20.512.0756.860***0.431 SRt1 → WPt20.7600.2642.874.0040.142 PFt1 → PFt20.531.0638.462***0.495 PFt1 → SRt20.192.0692.792.0050.175 SRt1 → PFt20.235.0683.442***0.201 PFt1 → WPt20.4530.2222.043.041.092Correlation coefficients in the model WPt1 <--> SRt11.3460.1678.057***0.595 SRt1<--> PFt10.254.0347.379***0.530 WPt1<--> PFt11.1630.1736.740***0.474 e1<--> e2.089.0263.410***0.2221 presents the average values, standard deviations, and Cronbach’s alpha reliability coefficients for each assessed variable at two different time points. In terms of self-regulation (SR), specifically planning (P), monitoring (M), and evaluating (E), all of them scored higher than the midpoint on the 7-point Likert scale for both time points. Similarly, the evaluated aspects of feedback handling (PF), including giving feedback (GF) and receiving feedback (RF), also surpassed the midpoint of the 7-point Likert scale for both time points. Participants’ writing performance (WP) also reached the midpoint, showing slight improvement during the second test. The distribution of these variables exhibited normality, as indicated by skewness values within the range of −1 and 1, following Bulmer’s (1979) criteria. The reliability of all assessed variables, measured by Cronbach’s alpha values, ranged between 0.880 and 0.962 for both time points, indicating satisfactory reliability.
Table 1. Means, standard deviations, and internal reliability for the observed variables at two times
Variables | Time 1 | Time 2 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
M | SD | Min | Max | Cronbach α | M | SD | Min | Max | Cronbach α | |
SR | 4.12 | 0.67 | 1.39 | 6.06 | 0.911 | 4.20 | 0.79 | 1.00 | 7.00 | 0.925 |
Planning | 3.70 | 0.91 | 1.00 | 6.00 | 0.935 | 3.76 | 1.04 | 1.00 | 7.00 | 0.952 |
Monitoring | 4.12 | 0.89 | 1.60 | 6.00 | 0.894 | 4.03 | 1.03 | 1.00 | 7.00 | 0.932 |
Evaluating | 4.54 | 0.91 | 1.00 | 7.00 | 0.936 | 4.82 | 0.99 | 1.00 | 7.00 | 0.888 |
PF | 4.37 | 0.72 | 1.75 | 6.65 | 0.928 | 4.43 | 0.78 | 1.00 | 7.00 | 0.902 |
GF | 4.33 | 0.92 | 1.50 | 6.63 | 0.962 | 4.43 | 0.96 | 1.00 | 7.00 | 0.880 |
RF | 4.41 | 0.83 | 2.00 | 6.67 | 0.910 | 4.43 | 0.92 | 1.00 | 7.00 | 0.924 |
Writing performance | 12.51 | 3.41 | 7.00 | 21.00 | 15.22 | 3.56 | 6.00 | 24.00 | ||
Correlation results
The correlation analysis presented in Table 2 reveals a noteworthy and statistically significant positive relationship among the variables for the two test points. The correlation coefficients ranged from 0.326 to 0.795, indicating the strength and direction of the associations. These findings establish a solid foundation for future investigation using structural equation modeling (SEM) to delve deeper into the relationships between these variables.
Table 2. Correlation between the factors for the two test points
Variables | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
1. SR1 | 1 | ||||
2. SR2 | 0.524** | 1 | |||
3. PF1 | 0.530** | 0.404** | 1 | ||
4. PF2 | 0.464** | 0.450** | 0.601** | 1 | |
5. Writing performance pre | 0.595** | 0.339** | 0.474** | 0.326** | 1 |
6. Writing performance post | 0.588** | 0.395** | 0.483** | 0.396** | 0.795** |
Note: *p<.05, **p<.01, ***p<.001
What is the possible longitudinal mediation role of peer feedback on the relationship between self-regulation and writing performance?
Cross-lagged analysis through SEM
The first-order cross-lagged panel regression model (CLPM) was used to examine the longitudinal mediating role of PF on SR and WP (Wang & Zhang, 2020). The first-order CLPM is suitable for analyzing data with repeated measures taken at two time points. In this study, SRT1→PFT2 represents the first path of mediation, with a coefficient of “a,” and PFT1→WPT2 represents the second path of mediation, with a coefficient of “b.” The direct effect path of SR T1→WPT2 in the mediation model is represented by coefficient “c.” The product of “a” and “b” represents the mediation effect. Since the model is a saturated model, meaning that all the parameters to be estimated exactly Match the elements in the covariance matrix, the degrees of freedom are 0. Therefore, the model fit indices are not estimated, and only the focus is on the path coefficients (Steeger & Gondoli, 2013). The main path coefficients of the cross-lagged panel regression full model are shown in Fig. 2, and the detailed results of the analysis can be found in Table 3.
[See PDF for image]
Fig. 2
Results on the cross-lagged panel regression model
Table 3. Coefficient effects of the examined model
Estimate | SE | CR | P | Standardized coefficient | |||
|---|---|---|---|---|---|---|---|
Main paths in the model | |||||||
WPt1 | → | WPt2 | 0.697 | .050 | 14.053 | *** | 0.667 |
SRt1 | → | SRt2 | 0.512 | .075 | 6.860 | *** | 0.431 |
SRt1 | → | WPt2 | 0.760 | 0.264 | 2.874 | .004 | 0.142 |
PFt1 | → | PFt2 | 0.531 | .063 | 8.462 | *** | 0.495 |
PFt1 | → | SRt2 | 0.192 | .069 | 2.792 | .005 | 0.175 |
SRt1 | → | PFt2 | 0.235 | .068 | 3.442 | *** | 0.201 |
PFt1 | → | WPt2 | 0.453 | 0.222 | 2.043 | .041 | .092 |
Correlation coefficients in the model | |||||||
WPt1 | <--> | SRt1 | 1.346 | 0.167 | 8.057 | *** | 0.595 |
SRt1 | <--> | PFt1 | 0.254 | .034 | 7.379 | *** | 0.530 |
WPt1 | <--> | PFt1 | 1.163 | 0.173 | 6.740 | *** | 0.474 |
e1 | <--> | e2 | .089 | .026 | 3.410 | *** | 0.222 |
Note: ***p<.001
In the autoregressive paths, SRT1 significantly and positively predicts SRT2. PFT1 significantly and positively predicts PFT2. WPT1 significantly and positively predicts WPT2, indicating the relative stability of the variables over time. In the lagged paths, SRT1 positively predicts PFT2 (β =.20, p <.001; this coefficient represents 'a'). PFT1 positively predicts WPT2 (β =.09, p <.05; this coefficient represents 'b'). Therefore, both the first path (a) and the second path (b) of the mediation model are significant. The longitudinal mediating effect of PF is established, with the mediation effect of ab = 0.018, SE = 0.016, 90 % CI [.002,.063]. Furthermore, SRT1 significantly and positively predicts WPT2 (β =.14, p <.01), indicating a significant direct effect in the mediation model. Thus, peer feedback plays a longitudinal partial mediating role between self-regulation and writing performance.
Discussion
Peer feedback, self-regulation, and writing performance
To begin with, the research sheds light on the interconnectedness of peer feedback, self-regulation, and writing performance. Self-regulation plays a pivotal role in facilitating students’ engagement in the peer feedback process (Molnar, 2025). SR in writing involves strategizing resources for writing, setting clear objectives, and taking deliberate steps to enhance their writing skills, reflecting a self-regulatory perspective on student feedback literacy, for which the three sub-processes of self-regulation (i.e., self-observation, self-judgement, and self-reaction) are integral to essential feedback-related activities such as generating, seeking, processing, and utilizing feedback effectively (Ma, 2023). This aligns with the findings of Xiao and Yang (2019), where active participation in formative assessment, such as peer feedback, mirrored the characteristics of self-regulated learners. In the present study, these self-regulatory traits encompassed several aspects: (a) the understanding and formulation of learning objectives, (b) the deployment of strategies to meet those objectives, (c) resource management, and (d) sustained efforts in the writing process. These diverse facets of self-regulation provide empirical support for Zimmerman and Risemberg’s (1997) theoretical framework on the self-regulated writing process, which comprises three principal categories of self-regulatory influences: environmental procedures, behavioral procedures, and personal procedures.
The findings highlighted the potential benefits of integrating peer support into self-regulated writing development (Li, 2025). Given the insights gained, we advocate for the recognition of the intricate relationship between peer feedback and self-regulation. Peer feedback prompts students to reflect on their roles in metacognitive oversight, nurturing self-regulated learning. Furthermore, these self-regulated learners appear to exhibit proactive behavior by seeking assistance and making a concerted effort to act on feedback, which is essential for their ongoing development as proficient writers.
The significance of self-regulation in writing becomes evident when we consider the three recurring stages of self-regulated learning, as outlined by Zimmerman (2002), within the context of writing. In the forethought phase, students plan their learning strategies, such as constructing conceptual diagrams of key writing points for fostering self-regulation. During the performance phase, they take on a self-directed role in testing their preplanned strategies. In the self-reflection phase, students engage in reviewing their previous actions and initiating adaptive responses by adjusting their learning approach to achieve their objectives. These elements are crucial in the process of writing, as supported by the works of Teng (2020) and Teng et al. (2022). In addition, the integration of self-regulation in writing not only enhances students’ ability to manage their learning but also empowers them to become more autonomous learners (Bai & Wang, 2023). The iterative cycle of planning, performance, and reflection encourages continuous improvement and deeper engagement with the writing tasks (Zhang & Zhang, 2024), leading to reduced writing anxiety (Shen & Tao, 2025). Furthermore, this approach aligns with contemporary educational theories that emphasize the importance of metacognition and self-regulated learning in achieving writing (Graham et al., 2021). Peer feedback in the context of writing further underscores the potential of self-regulation in writing, in line with Tsui and Ng (2000). The various stages of peer feedback have the potential to influence the motivational undercurrents during the writing process, thereby compelling student writers to regulate their writing performance (Huisman et al., 2019). This, in turn, plays a crucial role in determining their overall writing performance.
The mediating role of peer feedback in the relationship between self-regulation and writing: Longitudinal perspective
The findings presented in this study significantly advance our understanding of the potential impact of self-regulation on peer feedback and its subsequent influence on writing proficiency. In examining the lagged paths, it becomes evident that self-regulation at Time 1 (T1) positively forecasts peer feedback at Time 2 (T2), while peer feedback at Time 1 (T1) positively forecasts writing performance at Time 2 (WPT2). It is worth noting that both paths within the mediation model are statistically significant. This confirms the existence of a longitudinal mediating effect of peer feedback, with this mediation effect demonstrating significance. Consequently, peer feedback emerges as a substantial longitudinal partial mediator between self-regulation and writing performance from a longitudinal perspective. Building on the work of Xiao and Yang (2019), our research underscores the active involvement of students in enhancing their peer feedback through self-regulation. This involvement encompasses a spectrum of actions, including self-diagnosis, strategic planning, self-reflection, information-seeking from both educators and peers, and engagement in remedial writing activities. One plausible explanation for the mediating role of peer feedback may lie in its association with positive critical thinking (Zhan, 2021); passive, active, and constructive engagement with peer feedback (Wu & Schunn, 2023); and the development of cognitive skills such as analysis, comparison, and summarization (Lee, 2020). These cognitive skills may elucidate the mediating effect of peer feedback on self-regulation and writing performance, as peer feedback facilitates the transfer of knowledge acquired during current learning to future situations, thereby contributing to learner agency. This longitudinal phenomenon is potentially attributable to the enduring impact of peer feedback on students’ cognitive development. As students engage in self-regulation to improve the quality of their peer feedback, they are likely to cultivate a deeper understanding of critical thinking processes and cognitive skills, enabling them to apply these skills over time.
In our current investigation, we have observed a fascinating chain reaction that originates with self-regulation, encompassing vital components like planning, monitoring, and writing evaluation. This process extends to various aspects of peer feedback, which include both giving and receiving feedback, ultimately influencing writing development over an extended period. This interplay underscores the value of peer feedback, unlocking a plethora of advantages. It offers learners exposure to diverse perspectives, enabling them to identify strengths and areas in need of improvement within their writing. Furthermore, those actively engaged in providing feedback continuously update their knowledge on best practices, equipping them to offer pertinent and impactful guidance to their peers. This intricate process finds resonance with the principles of SCT outlined by Lantolf (2000). SCT underscores the dynamic interplay between social and cognitive dimensions in language learning. It takes place within the ZPD, where learners receive invaluable support, guidance, and constructive criticism, thereby enhancing their writing proficiency. This viewpoint aligns with the discoveries made by Yang and Zhang (2023) and Ma (2023), who emphasize that the process of formulating effective planning and organization strategies contributes to both the receipt and provision of feedback. As learners iteratively receive, process, and integrate feedback into their writing, their writing skills develop over time (Noroozi et al., 2023). In this longitudinal context, the act of formulating effective planning and organization strategies, combined with both receiving and providing feedback, contributes to enhancing learners’ writing abilities. Engaging in the continual practice of taking control of one’s writing is pivotal to both the receipt and provision of feedback and staying updated on best practices. This further bolsters learners’ feedback practices, ultimately leading to improved writing performance. This holistic approach underscores the interdependence of peer feedback, self-regulation, and, in the end, writing proficiency, underscoring the dynamic and enduring nature of these interactions within the realm of writing.
Limitations
There are some limitations in the present study. The first limitation is the relatively small and homogenous sample. The findings may not generalize to larger, more diverse populations or different cultural contexts. Second, the study relies heavily on self-report measures for assessing self-regulation and the effectiveness of peer feedback. Self-reported data can be subject to bias and may not always accurately reflect participants’ actual behaviors and experiences. Third, due to time constraints, this study may not have captured the long-term effects of self-regulation and peer feedback on writing proficiency fully. A longer-term study could provide more insights into the persistence of these effects. Fourth, the study lacks a control group for comparison, making it challenging to ascertain whether the observed improvements in writing proficiency are solely due to self-regulation and peer feedback or influenced by other external factors. Finally, the study does not use a qualitative way to extensively examine the quality of peer feedback. The subjective nature of feedback, its consistency, and its alignment with writing improvement may vary among participants.
Implications and conclusions
The present study contributes to the theories and pedagogical implications of peer feedback and self-regulation in several ways. In terms of theoretical implications, the findings advance the integration of Vygotsky’s sociocultural theory (SCT) and Zimmerman’s self-regulation model, offering a nuanced framework to explore the interplay between social interaction and individual cognition in L2 writing. By emphasizing the ZPD as a dynamic space for collaborative learning, the study highlights how peer feedback serves as a mediator that scaffolds self-regulatory behaviors, such as goal setting, monitoring, and reflection. This theoretical synthesis not only deepens the understanding of how peer feedback fosters writing proficiency but also provides a foundation for future research to investigate the bidirectional relationship between social and cognitive processes in diverse educational contexts.
In terms of pedagogical implications, first, the findings highlight the importance of fostering self-regulation and peer feedback practices among students, suggesting that these can lead to improved writing proficiency over time. It also emphasizes the need for institutions and educators to implement peer feedback training programs, which can enhance the quality of feedback provided by students and, in turn, improve their writing skills. For instance, workshops on effective feedback techniques, coupled with the use of rubrics and role-playing exercises, can equip students with the tools they need to engage in productive feedback exchanges. Moreover, instructors should be trained to facilitate these sessions and provide additional guidance to ensure feedback is actionable and relevant. Additionally, scaffolding writing assignments to progressively incorporate peer feedback can ensure that students learn to give and receive constructive criticism meaningfully.
Second, the study underscores the value of conducting longitudinal research to explore the relationship between self-regulation, peer feedback, and writing proficiency, offering insights for the development of long-term educational strategies aimed at cultivating these skills. By tracking students’ progress over time, researchers can gain deeper insights into how these skills develop and interact. This knowledge can inform the design of long-term educational strategies aimed at cultivating self-regulation and peer feedback competencies across different stages of learning.
Finally, the study proposes a deeper investigation into the interplay between self-regulation and peer feedback within the context of language testing, particularly for high-stakes writing assessments. While this area remains underexplored, it offers substantial potential to refine both assessment methodologies and learner outcomes. For example, integrating self-regulation strategies, such as goal setting, time management, and progress monitoring, into peer feedback processes could empower learners to approach their preparation more systematically and effectively. Simultaneously, peer feedback could provide learners with diverse perspectives and constructive critiques, enabling them to identify their strengths and address areas needing improvement. This dual approach not only enhances individual performance but also fosters a more collaborative and reflective learning environment, ultimately contributing to greater success in high-stakes writing tests.
Authors’ contributions
Author 1 and Author 2 wrote the main manuscript text. Author 1 and Author 2 prepared Figures and Tables. All authors reviewed the manuscript.
Funding
There is no funding received for this study.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
This study was reviewed and approved by the Research Ethics Committee at Beijing Normal University (Approval No. 2023-0809). All procedures were conducted in accordance with the Declaration of Helsinki and relevant institutional policies. Written consent was obtained from all individual participants included in the study. Participants were informed about the study’s purpose, procedures, risks, benefits, and their right to withdraw at any time without consequence.
Consent for publication
This is to state that we give our full permissions for the publication in Language Testing in Asia.
Competing interests
The authors declare no competing interests.
Abbreviations
English as a foreign language
Sociocultural theory
Zone of proximal development
Writer(s)-within community
Self-regulation
Peer feedback
Cross-lagged panel regression model
Planning
Monitoring
Evaluating
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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