L2 learners’ behavioral and cognitive engagement in AI-supported English writing

L2 learners’ behavioral and cognitive engagement in AI-supported English writing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article L2 learners’ behavioral and cognitive engagement in AI-supported English writing Fahad Alqurashi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6804457/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Advancements in technology and artificial intelligence (AI) are increasingly influencing second and foreign language (L2) learning. The integration of AI in L2 education highlights the importance of understanding and investigating its pedagogical and psychological roles and effects. Unlike conventional methods, AI-driven models offer L2 writing students personalized corrective feedback, real-time adjustments, and adaptive scaffolding that empower them to tackle unique challenges at their own pace. In addition, these platforms boost learners' motivation, bridge the gap between technical skill acquisition and emotional engagement. Utilizing qualitative mixed methods (classroom observations, student reflective journals, and semi-structured interviews), the current research assesses the perspectives of 54 Saudi undergraduate students on AI tools in L2 writing classrooms. The findings accentuate the dual impact of AI: technical enhancing writing skills and improving writing outcomes while promoting learners' motivation and fostering a positive attitude towards the writing process. Ultimately, such atmospheres have the potential for nurturing a more engaged, autonomous, and confident generation of EFL learners. The findings also underscore the necessity of integrating such technologies into language education and encouraging innovative teaching strategies. Future research should optimize these platforms for various educational contexts and evaluate their long-term effects on writing skills, feedback literacy, and learner motivation, Humanities/Language and linguistics Social science/Education artificial intelligence L2 writing learner cognition behavioral patterns Introduction The increasing use of artificial intelligence (AI) is fundamentally transforming the landscape of language education and impacting both the methods educators employ and the ways in which students acquire language skills. AI shows great promise in second/foreign language education. AI-powered tools offer instant feedback on pronunciation, grammar, vocabulary, and structure, which is changing how students think and act in language classrooms and consequently leading to more efficient and engaging learning experiences (Godwin-Jones, 2024 ). Writing, particularly in a second/foreign language, is a complex task that requires advanced skills and often presents challenges due to potential gaps in syntax, pragmatics style, or rhetoric. In the field of L2 writing, AI generative chatbots act as helpful virtual assistants that provide instant suggestions, which is especially useful for students who have difficulty writing smoothly and accurately (Jomaa, 2025 ). In L2 writing, artificial intelligence technologies function as virtual assistants that provide immediate corrective feedback, which is especially advantageous for learners facing challenges with writing fluency and accuracy. This real-time support plays a crucial role in helping learners identify and rectify errors as they write, fostering a more effective learning environment. Accordingly, students can practice writing at their own pace, allowing for a more personalized learning experience. This self-directed approach encourages learners to explore their writing styles and experiment with language without the constant need for teacher intervention which promotes independent learning and inspire students to edit their own work. Furthermore, it helps students build critical editing skills, increase their confidence by offering different ways to express themselves, gain trust in their abilities, and adopt a proactive approach to writing (Wang, 2024 ). Moreover, cognitive factors, such as perceived usefulness and ease of use along with motivational factors such as perceived enjoyment and emotional engagement in the use of AI systems are significant to consider for understanding their impact of virtual assistants on student learning. Recognizing these factors is crucial for harnessing the full potential of AI in educational and professional writing contexts. By examining such factors, educators and developers can better analyze students’ attitudes and foster a positive interaction atmosphere to utilize generative AI that can lead to increased confidence, enhanced writing competence, and a more enriching overall writing experience, which in turn optimize the learners’ intellectual and personal development (Richards, 2022 ). This research adds to the ongoing discussion about the role of AI in language learning and explores how L2 learners perceive and use AI-powered tools when writing in English as a foreign language. Literature Review Using AI Tools in L2 Writing Initial studies on AI in language education centered on automated writing evaluation (AWE) tools like Pigai and Grammarly, representing the first step in incorporating AI into writing instruction. Much of the research evaluated how well these tools worked within different teaching methods and their potential to enhance writing skills through immediate feedback and structured support. With the emergence of AI generative tools such as ChatGPT, research is now broadening to investigate a wider array of AI applications in English writing instruction. This step reflects a growing interest in how AI can support various aspects of the writing process, from brainstorming ideas to refining drafts. Ongoing research will help identify best practices and optimize the use of AI in fostering writing skills among students (Aljuaid, 2024 ). Despite progress in AI-generated feedback, differences persist in how effectively they improve language skills, often due to methodological and contextual variables, such as various feedback approaches: AI-only, combined teacher and AI response, or peer response (Zhang & Hyland, 2018; Kundu & Bej, 2025 ). The swift development of AI technologies has greatly increased their importance in second/foreign language education. Researchers are now examining how AI affects different parts of English writing, including the writing process itself, how humans, academic honesty, and AI work together. Recent studies indicated that AI generative chatbots can perform tasks typically done by teachers, such as creating activities, providing language and cultural information, overseeing language use, and reviewing essays. As a result, teachers may take on new roles, such as AI trainers, evaluators, risk managers, and reflection facilitators. This change redefines the teacher’s role in AI-supported writing instruction and highlights the need for teachers to become more knowledgeable about AI As technology plays a larger part in the writing process. Accordingly, teachers need to familiarize themselves with various AI applications and their functionalities. Teachers also must adapt their approaches to effectively integrate these technologies into their teaching and support student learning (Chen & Lv, 2024 ). More particularly, AI technologies augmented written corrective feedback (WCF) which is an essential part of the writing process to provide students with targeted guidance to improve their writing skills. These tools provide synchronous and immediate corrective feedback that meet individual students’ needs in identifying errors and suggesting corrections. Human-AI Collaboration could lead to facilitate tasks such as spotting research ideas, reviewing drafts, creating outlines, providing insights, and improving the overall quality of writing. L2 writing students who actively and repeatedly interacted with AI tools were found to produce better writing than those who simply used AI as an extra resource (Ranalli, 2018 ). These developments have been made possible by AI applications and systems that gather extensive data sets and utilize artificial neural networks and machine learning technologies. This has led to significant improvements in transforming text into structured data and extracting meaning through AI-driven natural language processing (NLP) and natural language understanding (NLU). However, incorporating AI into L2 writing has raised concerns about academic honesty, especially the risk of plagiarism. The extensive access to digital resources and essay-writing services has made cheating easier. AI technologies, including paraphrasing tools and deepfake content generators, complicate the detection of conventional forms of plagiarism. Educational institutions might have to develop clear guidelines and policies regarding the use of AI in academic settings. These policies should educate students about the ethical implications of using AI and emphasize the importance of original thought and proper attribution. For example, while plagiarism detection systems are used to uphold academic standards, it is crucial to educate students about proper writing practices at the same time. This proactive approach not only discourages academic dishonesty but also fosters a deeper understanding of academic integrity among students. These caveats emphasizes the need for more research into human-AI collaboration to address multiple controversies surrounding AI-supported writing instruction, stressing the need for AI developers and education researchers to work together to prevent both obvious and subtle forms of academic misconduct (Dale & Viethen, 2021). AI in Language Learning: Learner Perspectives Research in L2 learner cognitive psychology emphasizes that various factors including perception, attention, behavior, emotion, motivation, cognition, and memory deeply interact with and significantly influence teaching and learning outcomes. Among these, learner behavior, emotion, and cognition are three interconnected elements that play a crucial role in shaping educational experiences. Emotions and cognition directly affect human behavior and the nature of learning behaviors, such as engagement and participation which impact academic results (Pessoa, 2008 ). Positive learning behavior, characterized by active involvement in various academic tasks, is essential for achieving favorable academic outcomes. Likewise, emotions, whether positive (like interest and happiness) or negative (such as boredom, sadness, and anxiety), can trigger corresponding responses that affect learning processes. Cognition encompasses psychological investment and the learning strategies needed to understand complex concepts and master advanced skills. The integration of artificial intelligence has fundamentally reshaped the landscape of foreign language education in several transformative ways and created significant advancements in how languages are taught and learned, and how the writing process becomes more efficient and engaging (Zhang & Hyland, 2018). More particularly, the traditional dyad of "teacher-student" has evolved into a more complex and potentially richer "teacher-student-AI" triad. This shift is driven by the capacity of AI to personalize learning experiences and provide immediate feedback and targeted support. Research consistently demonstrates a generally positive reception from students towards AI-powered language instruction. This stems from the ability of different chatbots to adapt to individual learning needs and paces and offer a customized educational experience that traditional methods often struggle to achieve. Students appreciate the real-time guidance and instant response provided by AI, which allow them to immediately identify and correct errors and foster a more efficient and effective learning process (Wu et al., 2024). Specifically, when writing in English as a second/foreign language, L2 learners acknowledge AI’s significant contribution to educational innovation. Research in this area reported progressive attitudes and positive perceptions of L2 learners about utilizing AI which noticeably enhances their motivation to write and demonstrably improves their writing skills ((Alsadoon, 2021 ). These transformations suggest that AI is not merely a supplementary tool but a catalyst for skill development in crucial aspects of writing proficiency. Moreover, research indicates that when AI is thoughtfully employed and appropriately integrated into the learning process, it can provide efficient and targeted support, leading to a boost in students’ motivation, engagement, and overall confidence in tackling academic tasks. This increased confidence, coupled with the efficient support provided the teacher, ultimately facilitates students’ progress in writing and contributes to a more positive and productive learning experience (Feng, 2025). In essence, the "teacher-student-AI" triad represents a potentially powerful synergy, where the teacher provides guidance and expertise, the student actively engages in the learning process, and AI offers personalized support and feedback, creating a more dynamic and effective learning environment. However, the "when used appropriately" stipulation is crucial, highlighting the need for careful consideration of pedagogical strategies and ethical implications when integrating AI into language education (Kundu & Bej, 2025 ). Despite the growing interest in AI technology, research on its application in L2 teaching and learning remains limited. Specifically, studies focusing on the cognitive psychology of L2 learners regarding AI-driven written corrective feedback (WCF) are particularly scarce. This area requires a complex, multidisciplinary understanding that spans AI technology, linguistics, and cognitive psychology, among other fields. This study aims to fill this gap by examining learners’ behavioral and cognitive involvement in AI-supported English writing, focusing on the following two research questions: Q1: What are the common ways students interact with and utilize AI in English writing? Q2: How do students recognize, perceive, and evaluate the function of AI when writing in English as a foreign language? What benefits do they see in the use of AI for various aspects of writing? Methodology Participants The study involved 54 male undergraduate English-major students enrolled in two sections of the Advanced Writing course, which is part of the fourth level of the Bachelor of Arts program at a university in Saudi Arabia. These students had previously completed three levels of writing courses during their first three semesters in the program, providing them with a solid foundation in writing skills. Throughout their initial coursework, the participants encountered a variety of writing tasks designed to enhance their proficiency. They studied under different instructors, each bringing unique teaching styles and perspectives. This exposure allowed the participants to engage with diverse writing genres, ranging from paragraphs to essays, which enriched their understanding of writing’s multifaceted nature. Additionally, the participants engaged in numerous peer response activities, fostering collaborative learning and critical feedback skills. This interaction not only helped them refine their writing but also encouraged them to think critically about their peers’ work. Throughout the process, they received various forms of written corrective feedback, which guided their improvement and development as writers. Overall, the participants’ experiences and interactions in the writing program were diverse and enriching and contributed to a well-rounded understanding of writing. Ethical considerations regarding the protection of participants’ rights and well-being were thoroughly examined during the development of this study to ensure the integrity of the research process. The researcher first secured approval from the Institutional Review Board (IRB) at the university, which involved a detailed review of the study’s design, purpose, and potential risks. This step was crucial for safeguarding participants’ rights and welfare. This approval was essential not only for compliance with institutional policies but also for fostering trust between the research team and the university community. To further ensure ethical standards, the researcher informed students that participation in the study was entirely voluntary, meaning that students could choose whether or not to participate without any repercussions on their academic evaluations. This transparency was vital in promoting a sense of autonomy among participants. Moreover, the researcher assured students that all data collected would remain confidential and used only for research purposes. These ethical safeguards were designed to create a respectful and secure environment for participants, ultimately enhancing the credibility and reliability of the research findings. Instruments Data for this study were gathered using a combination of qualitative instruments that included classroom observations, student reflective journals, and semi-structured interviews. Using a multi-method qualitative approach can enrich the exploration of language learning by combining various data collection techniques that are effective in gathering in-depth insights into participants’ experiences, emotions, and perspectives on language learning and AI tool usage (Creswell, 2020 ). Classroom observations are employed in research to yield rich and detailed insights into students’ behaviors, interactions, and overall activities within the classroom. By analyzing this data, educators can better contextualize students’ experiences, identifying their strengths and areas for improvement. This understanding is crucial for tailoring instructional strategies to meet individual learning needs, ensuring that the integration of AI tools effectively supports students’ writing development and enhances their educational experience. Ultimately, these insights can inform future teaching practices and AI tool implementation, promoting a more effective learning environment (Alam & Mohanty, 2023 ). Student reflective journals in language education serve as a powerful tool for enhancing learning and self-awareness and encourage students to reflect on their learning experiences, helping them identify strengths and areas for improvement. Reflective writing fosters critical thinking by prompting students to analyze their experiences, challenges, and successes in language learning. Students also can set personal language goals and track their progress over time, which can motivate them to stay engaged (Barber, 2021 ). Semi-structured interviews are a good instrument designed to facilitate meaningful discussions about different aspects pertinent to language learning. This flexible format allow for exploring various topics including participants’ experiences with AI tools, emotional responses to interactive learning activities, the impact of personalized feedback on language skill development, and the influence of motivation and autonomy on engagement. Participants also could discuss any issues related to challenges they encountered (Karatsareas, 2022 ). Procedures The researcher initiated the study by offering a concise overview of its nature and objectives. This introduction aimed to clarify the purpose of the research and outline the key themes and questions that would be explored. By doing so, the researcher set the stage for a meaningful dialogue to ensure that students understood the context and relevance of their participation. To foster an open and inclusive atmosphere, the researcher encouraged students to voice any pertinent issues or concerns they might have. This invitation was crucial for creating a safe space where participants felt comfortable to share their thoughts and experiences. By actively engaging students in this manner, the researcher aimed to promote a collaborative environment and emphasize the value of their insights in shaping the study’s findings. Over a period of 12 weeks during the semester, the participants had access to different AI-powered tools on their smart phones. Accordingly, classroom observations were carried out to closely monitor and analyze how students utilized AI chatbots in writing English as a foreign language. These observations aimed to examine the dynamics of student interaction with AI, particularly how they integrated AI-generated feedback into their drafts for various writing tasks and to meticulously track and document the diverse activities students undertake while using these chatbot. This includes noting how they initiate tasks, seek assistance, and integrate feedback provided by the AI. Observations also focused on the collaborative dynamics among students, as they often engage in discussions about their writing, share tips, and provide peer response in conjunction with AI suggestions. By closely monitoring these interactions, the researcher aimed to verify the various techniques to benefit from AI-generated feedback and gain a clearer understanding of how these technologies influence student engagement and motivation. In Week 8 of the semester, students were prompted to complete a reflective journal focused on their experiences with AI support in L2 writing. This exercise aimed to foster deeper engagement with their learning journey and encourage them to articulate their thoughts on how technology integrates into their writing practices. The journal entries were crafted to explore various aspects of utilizing AI, such as its impact on their writing skills, motivation, and overall confidence. By reflecting on these experiences, students could gain valuable insights into their growth and challenges. In particular, the journal entries included: Initial Thoughts Students began by articulating their expectations and initial feelings about using AI in their writing. This set the stage for understanding their mindset before engaging with the technology. Documentation of Methods Students were encouraged to describe the specific ways they utilized AI tools throughout their writing tasks. This included detailing the types of AI applications they employed, such as grammar checkers, content generators, or research assistants. By documenting these methods, students could better understand how these tools influenced their writing strategies. Identifying Challenges This stage focused on introducing the challenges encountered while using AI. This included technical difficulties, such as software malfunctions or navigation issues, as well as conceptual challenges, like understanding how to effectively incorporate AI-generated suggestions into their own writing. Identifying these obstacles helped students recognize areas for improvement and seek solutions. Assessment of Effectiveness Students were prompted to evaluate the overall effectiveness of AI tools in supporting their writing process. This involved reflecting on whether AI enhanced their writing quality, improved their productivity, or helped them gain new insights into their writing style. By assessing the impact of AI, students could critically analyze its role in their academic development. Concluding Insights In their final entries, students summarized their overall experiences, highlighting key takeaways and personal growth. They reflected on how their perceptions of AI shifted over the course of their writing assignments and how they planned to integrate AI tools into future academic endeavors. At the conclusion of the semester, 11 students volunteered for 30-minute semi-structured interviews. These interviews provided an opportunity for deeper insights and were conducted alongside the reflective journal analysis. With the students’ consent, the interviews were recorded and subsequently transcribed to allow for a thorough examination of their perspectives and experiences regarding the use of AI in their writing. Also, the students had the opportunity to talk freely about any other aspects that affected their learning and raise any issues related to their ability and skills to utilize AI-powered tools effectively in writing in English. This multi-faceted approach ensured a rich collection of qualitative data to enhance the study’s findings. Data analysis This study utilized qualitative thematic analysis to interpret the data and derive significant themes from the participants’ input collected through the three instruments. This approach involved using multiple data sources to create a more comprehensive understanding of the research topic. In this study, interviews and reflective journals were identified as the primary data sources to capture students’ personal insights and experiences regarding the use of AI in their writing processes. Audio recordings from interviews were transcribed verbatim, allowing for a faithful representation of the participants’ voices. Furthermore, student reflective journals were collected to gain insights into their views and attitudes toward using AI systems to learn L2 writing. The complete transcripts from interviews and student journals were then thoroughly reviewed to facilitate in-depth exploration of individual perspectives, extract key experiences that reflected student engagement with AI tools, and identify recurring patterns within the data. These patterns were then carefully categorized and coded into specific themes, ensuring clarity, meticulousness, and precision throughout the analysis in order to reach a comprehensive understanding of students’ reactions and capture the nuances of their experiences and insights. The analysis process consisted of three levels of coding which illustrates the transition from initial codes to overarching themes as follows: Open Coding The analysis began with a thorough examination of the textual data, with open coding conducted line by line and sentence by sentence. This meticulous approach aimed to identify initial codes that encapsulated key ideas and recurring patterns within the data. Categorization Once initial codes were established, similar codes were grouped together to form preliminary themes. For instance, first-level codes such as “corrections,” “improvement,” and “difficulties” were categorized under a second-level code labeled “writing processing.” This categorization helped streamline the data and highlighted the interconnectedness of various concepts. Theme Development Following categorization, the second-level codes were reviewed, compared, and subjected to further analysis to identify central themes that represented the core findings of the study. For example, codes like “writing processing,” “strategic support” and “content generation,” were synthesized into a primary theme indicating that AI significantly contributes to writing efficiency. This theme reflects the broader implications of AI tools in enhancing students’ writing processes. To ensure both consistency and validity in the analysis, the study utilized data triangulation, as recommended by Creswell ( 2020 ). Alongside primary sources, classroom observations were conducted to validate and triangulate participants’ feedback, offering valuable complementary insights. By observing students in real-time as they interacted with AI tools in an academic writing setting, the researcher gathered contextual information that enriched the overall analysis. The observational data supported the findings from reflective journals and interviews and provided a broader perspective on students’ practical interactions with AI. This multi-source approach enhanced the analysis and credibility of the study by corroborating results across various data collection methods. Consistent categories were applied across the datasets to develop main codes and themes and promote a cohesive exploration of the relationships among the three datasets which facilitated a deeper understanding of participants’ perceptions and preferences. Triangulation ensured that the identified themes accurately reflected students’ experiences, reinforcing the reliability of the conclusions and offering a nuanced interpretation of how AI influences L2 writing. To further enhance the credibility and validity of the study’s analytical process the researcher worked alongside two independent raters, who provided additional perspectives and insights during the review of student participation. This collaborative effort not only enhanced the rigor of the coding and thematic development but also ensured that the findings were well-rounded and reflective of the participants’ true experiences. By incorporating multiple viewpoints, the analysis was bolstered, leading to more reliable and valid conclusions regarding the effectiveness of generative AI written corrective feedback in L2 context. The three evaluators achieved a 92% agreement rate on the codes and themes from participants’ responses which indicates strong inter-rater reliability. This high agreement suggests successful investigator triangulation that helps reduce researcher bias (Bryfonski, 2023). Findings & Discussion The qualitative thematic analysis reveals that students perceive AI as a valuable support tool in writing in English as a foreign language and make use of its sophisticated benefits and implications for their learning processes. AI fosters a positive attitude toward writing by creating an encouraging and supportive environment that motivates learners to engage actively in writing tasks. This encouragement is achieved through several key mechanisms. For example, consulting chatbot about different writing aspects reduced anxiety about writing, particularly in a foreign language. Several participants mentioned in the journals and interviews that “ writing isn’t a problem with AI. It became fun ,” “ I don’t worry about essay assignments ,” “ I wish we were allowed to use AI last semester to write better and get good grades.” These responses reflect a positive attitude toward writing. It is clear that the participants enjoyed the ability of AI to create a supportive, engaging, and personalized writing environment. AI writing tools create a non-judgmental space where students can experiment with their ideas and language without the fear of negative critique, thus promoting a more positive writing experience. Such emotional/motivational advantages promoted various academic benefits as follows: 1. Enhancing Writing Quality Effective writing is a multifaceted endeavor that goes beyond mere language proficiency. It requires a combination of linguistic skills, relevant content, and logical structure. It also involves a keen awareness of the writing’s purpose, whether to inform, persuade, entertain, or analyze, and audience’s background, expectations, and preferences. Producing relevant content necessitates a genuine interest in the subject matter as well as a solid understanding of the topic at hand. Student-writers must be able to gather and synthesize information effectively and ensure that their arguments are well-supported and grounded in credible sources. Student-writers achieve writing proficiency by integrating these elements where they can produce high-quality work and construct clear, relevant, and logical arguments that communicate their message appropriately and resonate with readers successfully (Kano, 2021 ; Raims, 1983 ). Participants’ input from journals and interviews and results of observation confirmed that they found AI very helpful in optimizing their writing quality and achieving greater success in their writing endeavors. Students widely recognized that AI is a significant tool to optimize their language use, which, in turn, enhances the readability and quality of their writing at different levels. This recognition is evident in their reflective journals and interview responses, where they detail the various ways AI chatbots support their writing endeavors. One of the participants stated in his journal, “ I ask Chatly to give me ideas and arguments for the topic, so I have no problem in this step. This makes my writing good. ” Another participant mentioned in the interview that in some cases he wrote sentences in Arabic and used AI to translate those parts into English. This focus on quality enhancement allows learners to refine their writing and express ideas more clearly, making their arguments easier to understand and their compositions richer and more polished. Previous studies indicated that implementing personalized interventions and utilizing a variety of AI-powered tools helped students engage in focused activities that significantly enhanced their writing abilities and equipd them with the skills necessary for success in various writing contexts (Zhao, 2025 ). Participants in this study were observed to take advantage of different AI writing tools as effective means to boost up both the writing process and the final output. In particular, the participants made use of those tools to increase the writing quality enabling them to present a clear and unique perspective in their texts. A third student revealed in his journal, “ Wordtune helped me to fix errors and make adjustments, but the best thing is help with paraphrasing. Now I don’t worry about writing the same ideas in different ways .” AI-powered tools helped participants refine their language, ensuring that their ideas were articulated clearly. This clarity makes it easier for readers to understand the main arguments and themes presented in their writing. With advanced algorithms, those tools can analyze text and provide feedback that enhances both the content and the overall flow of ideas. EFL student-writers could utilize AI suggestions to modify content to match specific tones, improve engagement and effectiveness and ensure consistency across the essay (Wang, 2024 ). Most students seemed very inspired by the help of AI writing tools. Several students mentioned during the interviews that they usually use two or three of these tools to check their drafts and compare the suggestions because they want to “ be as perfect as possible ,” “ get full marks ,” or “ know how write things in different ways. ” By prioritizing quality, students learn to critically evaluate their work and strive for excellence. This commitment leads to more thoughtful writing, where clarity, coherence, and creativity are emphasized. Frequent revisions promote greater awareness of the writing process. Students learn to identify areas for improvement and understand the importance of drafting, feedback, and revision in developing quality writing. One significant advantage of Automated Writing Evaluation (AWE) systems is that they allow students to revise their drafts as many times as needed before submission. This flexibility encourages a more iterative approach to writing, where learners can refine their work continually (Hayes, 2012 ). 2. Instant Feedback Traditionally, written corrective feedback (WCF) has involved teachers manually marking students’ written assignments to identify errors and suggest improvements (Ferris, 2004). Previous studies highlighted the significance of written corrective feedback on students’ work to help them identify and correct errors, which promotes their composing skills and facilitates the revision process (Bitchener & Knoch, 2010 ). While this method has shown effectiveness, it is often time-consuming, may lack consistency, and can place a significant burden on teachers when they are required to provide immediate feedback to every student, especially in classes with a large number of students (Wang & Jiang, 2014). Research on automated written corrective feedback (AWCF) and various forms of digital corrective feedback (DCF) has produced mixed findings, yet it does indicate their positive impact in providing several features that set it apart from traditional teacher-fronted feedback. The participants in this study were observed to consult different AI-powered tools to check various aspects of their writing and seemed happy to get immediate responses. They ask questions like: “ Is this sentence correct? ” and “ How can I improve this idea? ” Some participants were heavily reliant on AI when asking questions such as “ What should I write next? ” and “ Is this enough or should I explain more? ” which indicates huge trust in AI feedback. The quick processing of AI feedback allows students to make timely revisions and reinforce their trust in the tool’s reliability especially it is based on algorithms and data, which can make it seem more objective and reduce bias, compared to human feedback (Barrot, 2021). Key distinctions of AI-supported corrective feedback include: Rapid Error Identification AI systems can quickly identify a wide range of errors and provide comprehensive corrections within seconds, allowing students more time to revise their work and correct mistakes promptly. Research shows that instant feedback effectively draws students’ attention to errors, leading to more efficient corrections (Lee, 2017). Receiving feedback immediately after completing a writing task help L2 writers to address errors while the content is still fresh in their minds. This immediacy helps reinforces learning and ensures that they can connect corrections to specific parts of their writing. When feedback is provided swiftly, students are more likely to remember the corrections and understand the rationale behind them. This leads to better retention of the concepts and strategies discussed in the feedback. Moreover, Instant responses can help students, who often feel anxious about receiving feedback, to alleviate some of that anxiety, as learners can see where they stand and understand their progress without prolonged uncertainty (Ranalli, 2018 ). Real-Time Metalinguistic Explanations AI writing tools offer consistent and accurate metalinguistic explanations in real time, which teachers may struggle to provide due to time constraints. Unlike teachers, who may need time to review and respond to each student’s work, AI can provide feedback right when each student needs explanations. When combined with direct corrections, these explanations help learners address errors, reflect on their use of feedback, and consider more choices. This reflection is an essential step for the development of critical thinking skills and deeper understanding of the writing process. In addition, the metalinguistic explanations generated by chatbots are based on established linguistic rules and patterns, reducing the likelihood of human error. This accuracy enables students to learn the correct usage and reasoning behind their mistakes (Woodworth & Barkaoui, 2020). Neutral & consistent Feedback : The feedback generated by automated writing systems is inherently neutral and provides several important benefits that enhance the learning experience for students. AI provides feedback that is solely focused on the writing itself. This kind of feedback is not influenced by the teacher’s mood or state of mind, such as fatigue from grading or personal attitudes toward students. This means that students receive evaluations based on their work rather than any external emotional states of the teacher. AI systems deliver uniform feedback for similar errors across different pieces of writing. Such consistency allows students to receive the same level of critique each time they submit work which fosters a fair learning environment. Automated feedback is based on predefined algorithms and linguistic rules to ensure that evaluations are objective and not subject to personal biases. This objectivity helps maintain consistent standards across all students, regardless of any external factors (Barrot, 2021). 3. Enriching Content & Organization The content and organization of writing are equally significant components and considerably crucial for enhancing reader understanding and engagement. Content is the core of writing, encompassing the ideas and messages the writer wants to convey. It is the real substance, the “what,” of the writing. High-quality content is relevant, informative, original, and meaningful, effectively serving its purpose, whether to inform, persuade, entertain, or provoke thought. Students participating in this study stressed that AI-powered tools can extensively assist them in brainstorming and fostering a clear, logical flow of thoughts in several ways. A participant mentioned in his journal, “ I don’t have to worry about creating more ideas. Quillbot gives me hundreds of them each time. ” Generating a wide range of ideas based on different prompts is a key aspect in AI assistance to overcome writer’s block and explore different angles on a topic. By providing multiple viewpoints, AI encourages students to consider various aspects of a subject, enriching their understanding and creativity (Tsufim & Pomerleau, 2024 ). AI-mediated structured prompts have been found useful to offer valuable guidance to students in developing their ideas systematically. AI assistance covers essential composing points which positively affects their ability to construct logical arguments and cohesive narratives. Another participant highlighted the following points during the interview, “ In many cases I don’t know what to say next. I feel I come to a dead end. AI solved this problem. AI opens my eyes to hidden parts so I can write more. It helps also with giving many examples so I can sound more convincing. ” L2 learners in many settings have utilized AI writing tools in fostering a clear and logical flow of thoughts in written work and suggesting better phrasing to express their ideas more succinctly and effectively. Also, they used AI writing tools to detect logical inconsistencies in arguments, alerting to areas where their reasoning may be flawed. This critical analysis encourages a more robust and persuasive argumentation structure to enhance the readability of the text (Wang, 2024 ). On the other hand, organization refers to the structure of the writing that determines how content is arranged and how ideas are connected. Effective organization guides the reader logically through the piece, impacting comprehension, persuasiveness, and engagement. Good organization ensures a smooth flow of ideas, making the writing clearer and more impactful (Lee & Yuan, 2021 ). AI- powered writing tools can help arrange ideas and structure content logically to ensure that arguments are clearly presented to improve text coherence. Previous studies in the Saudi context reported that L2 learners found AI very helpful in providing tips on how to select the right words and phrases as transitional language elements for linking ideas in writing and enhancing its fluidity and consistency. By processing students’ texts, AI-mediated tools analyze the flow of ideas and suggest modifications that improve transitions between sentences and paragraphs to clarify how ideas relate to one another and certify that the writing feels cohesive and logical (AlGhamdi, 2024 ). One of the participants expressed diverging opinions in the interview about AI help with organization. He said, “ I always thought that I can arrange my ideas very well. Everything looked fine. However, ChatGPT changed my sentences and put them in a different order. They look good now also and the teacher was happy with the essay. I just want more marks. ” Usually L2 writers tend to express each idea individually without looking at the broader context. AI writing tools can suggest appropriate transitional words and phrases based on the context of the writing to serve as bridges between sentences and paragraphs, clarify relationships and priorities among ideas, reinforce the writer’s intent, and help to guide the reader through the text. This guidance helps students learn how to effectively incorporate transitions, build compelling and well-supported arguments, highlight essential components such as claims, evidence, and counterarguments, which helps to develop a deeper understanding of effective writing techniques (Tsufim & Pomerleau, 2024 ). 4. Vocabulary and Style Suggestions Writing motivates learners to explore and employ a variety of vocabulary to express their ideas, which is essential for effective communication. In searching for suitable words for different contexts, L2 learners’ vocabulary collection grows and their language skills develop. This process not only improves their writing abilities but also boosts their confidence and enhances their overall communication skills (Nation, 2009). Due to different levels of proficiency constraints in the target language, L2 writing learners often face several difficulties in word choice that can hinder their writing effectiveness. Technology-assisted vocabulary learning and teaching methods were introduced in the field of Computer-Assisted Language Learning (CALL) through which researchers explored various tools, such as online dictionaries, to improve vocabulary learning outcomes (Peters, 2007 ). More recently, AI-enhanced writing systems have been widely utilized to provide recommendations for word choice and stylistic improvements, helping writers to reinforce the sophistication of their writing. Those automated systems serve as powerful tools for language learning and enhancing vocabulary acquisition while simultaneously offering valuable diagnostic insights into individual learners’ progress. One of the participants mentioned in the interview, “ Quillbot helped me to remember many words that I took before. I can’t imagine I forgot those words. ” Obviously, memorizing vocabulary is a crucial initial step in effectively learning a second/foreign language. AI systems aid learners in retaining less frequently used words by simulating human long-term memory processes. This approach is based on the idea that memories fade over time but can be strengthened through spaced repetition (Ebbinghaus, 2013). Another participant highlighted, “ Usually when I write I mix things up, but now I started to distinguish the right word to use in the right place. ChatGPT is very generous with giving many options. ” AI-generated prompts provide examples of vocabulary in relevant contexts and tailor exercises and suggestions to meet individual needs, helping students understand how words are used in different situations. Such engaging encounters provide learners with context-rich learning experiences and reinforces appropriate vocabulary usage, ultimately leading to improved language proficiency (Jeon, 2021 ). After all, making use of adequately advanced vocabulary in writing is one of the challenges that face even higher proficiency L2 leaners as they may still have limited exposure to sophisticated vocabulary in real-world contexts. Advanced vocabulary often carries nuanced meanings and connotations that can be difficult to navigate. Without frequent encounters with advanced terms, L2 learners may struggle to integrate them effectively into their writing. They may find it difficult to grasp these subtleties which could lead to potential misuse or overgeneralization of certain terms. Previous studies on Saudi L2 learners reported that AI can help bridge this gap by providing learners with curated examples of advanced vocabulary in context, allowing them to see how these words function in authentic writing and conversation. AI can play a crucial role in teaching these subtleties. By providing definitions, usage examples, and explanations of connotations, AI writing tools can help learners understand the complexities of advanced words. This targeted instruction can enhance their ability to choose the right words for specific contexts, which in turn improves their writing skills and communicative competence (Alsadoon, 2021 ). In addition, AI provided students with effective vocabulary-based strategies to enhance clarity, variety, and engagement in the text. One of those strategies is using synonyms to help maintain reader interest, improve the flow of the text, and avoid repeating the same words which can make writing monotonous. A third participant mentioned in the interview, “ Finding synonyms or good words is not a problem anymore. Instead of one word you can have many of them. ” AI writing tools help students in many different cases to minimize unnecessary repetition and avoid redundancy in their writing. During observation, the participants in this study seemed happy with diverse and innovative suggestions for restructuring sentences which allowed them to avoid overusing basic vocabulary that can result in repetitive and unengaging writing. To improve text attractiveness and readability, L2 writers should avoid unnecessary repetitions by incorporating a range of synonyms to demonstrate a strong command of language and make writing more sophisticated (Yang, 2025 ). Each writer possesses a unique style characterized by distinct word choices, sentence structures, and rhetorical devices that reflect their individuality. This individuality enhances the aesthetic quality of writing, as variations in sentence length and structure create rhythm and emotional impact. AI programs provide diverse feedback to optimize clarity and improve style. For instance, a fourth participant stressed in the journal, “ I wrote two examples in the last essay, but Chatly said they are one because you are expressing the same idea. So I combined the two examples in one and Chatly gave me another good example. ” AI can suggest alternative phrases and claims to maintain the writing style and avoid repetition, which enriches the text and makes it more engaging. Chatbots may also prompt writers to explore additional points or consider larger, more complex concepts, thus deepening their arguments. For example, an AI might encourage learners to reflect on how their ideas relate to societal trends or theoretical frameworks, fostering critical thinking and a more nuanced approach to writing (Zhao, 2025 ). Conclusion This study contributes valuable insights into the Saudi context, enhancing the growing body of research on AI applications in L2 education. It demonstrates the transformative potential of AI-driven dynamic writing platforms in second and foreign language learning settings. The study provides a comprehensive assessment of Saudi undergraduate English-major students’ views on AI-powered tools for L2 writing. The findings of this research accentuate the dual impact of AI platforms, enhancing both the technical aspects of writing and fostering a positive attitude toward writing as a creative endeavor. Overall, these tools are well-received and positively influence participants’ writing quality and efficiency. More particularly, utilizing adaptive and interactive AI chatbots facilitate effective written corrective feedback (WCF), and lead to measurable improvements in students’ writing skills, including fluency, coherence, lexical diversity, style, and grammatical accuracy. Moreover, these platforms significantly boost learners’ motivation to engage in writing tasks, helping bridge the gap between technical skill acquisition and emotional involvement. Furthermore, the current research makes a significant contribution to the field of teaching English as a foreign language (EFL) by illustrating how artificial intelligence (AI) can improve linguistic skills and foster learner autonomy. The results emphasize the necessity of incorporating such technologies into language education, encouraging educators to adopt innovative strategies for more interactive and effective writing programs. AI platforms succeeded in creating a shift in L2 education by promoting learners’ intrinsic motivation, offering customized learning opportunities, and empowering students to take an active role in their learning rather than simply absorbing information. Additionally, the research points to the need to further explore the changing dynamics of AI that could enhance the learning experience in different ways. Future research should aim to optimize these platforms for diverse educational settings and assess their long-term effects on writing skills and learner motivation. Ultimately, AI-powered writing tools not only enhance language abilities but also serve as catalysts for nurturing a more engaged, autonomous, and confident generation of EFL learners. Declarations Ethical Approval This research was carried out in consonance with the ethical principles outlined in the Declaration of Helsinki. The Ethics Committee for Research in Social and Human Sciences at Umm Al-Qura University granted approval for the study [reference approval # 2024-16] on October 11, 2024. Following a comprehensive evaluation of the research methods and data collection tools, the committee ensured that the rights and welfare of participants were prioritized. This included confirming voluntary participation, obtaining informed consent, maintaining anonymity and confidentiality, and assessing any potential risks to participants. Informed Consent According to the university calendar, the second semester started on Sunday 24 October 2024 and ended on Thursday 20 February 2025. In the first week of the semester, the researcher provided the participants with detailed information regarding the objectives of the study, the voluntary aspect of their involvement, measures taken to safeguard their privacy and personal information, and the use of collected data solely for research purposes. Additionally, the researcher informed the participants about the publication of the findings. Written consent reflecting this information was acquired from every participant involved in the research. Author Contribution My paper is relevant to the scope of this collection, Large language models in psychological science, as it investigates cognitive and behavioral aspects related to utilizing AI in learning writing in English as a foreign language. It also explores the significance of understanding how AI-powered tools help L2 learners develop their writing skills. The study was conducted in Saudi Arabia, which is an under-researched learning context. Getting this paper published in Humanities and social sciences communications will have a positive effect on the academic atmosphere and encourage other researchers to plan and do more research on different topics related to learning English as a foreign language. Many thanks for considering my paper for publication. Data Availability The data that support the findings of this study would be made available upon reasonable request from the corresponding author. References Alam A, Mohanty A (2023) Educational technology: Exploring the convergence of technology and pedagogy through mobility, interactivity, AI, and learning tools. Cogent Eng 10(2):2283282. https://doi.org/10.1080/23311916.2023.2283282 AlGhamdi R (2024) Exploring the impact of ChatGPT-generated feedback on technical writing skills of computing students: A blinded study. Educ Inform Technol 29(14):18901–18926. https://doi.org/10.1007/s10639-024-12594-2 Aljuaid H (2024) The Impact of Artificial Intelligence Tools on Academic Writing Instruction in Higher Education: A Systematic Review. Arab World English Journal (AWEJ) Special Issue on ChatGPT, April 2024 . 26–55. https://dx.doi.org/10.24093/awej/ChatGPT.2 Alsadoon R (2021) Chatting with AI Bot: Vocabulary learning assistant for Saudi EFL learners. Engl Lang Teach 14(6):135–157. https://doi.org/10.5539/elt.v14n6p135 Barber JD (2021) Using course journals to encourage reflective practice in second language teacher education. Reflective Pract 22(1):128–141. https://doi.org/10.1080/14623943.2020.1851670 Bitchener J, Knoch U (2010) The contribution of written corrective feedback to language development: A ten month investigation. Appl Linguist 31(2):193–214. https://doi.org/10.1093/applin/amp016 Chen M, Lv MC (2024) College English writing instruction in a ChatGPT context. Contemporary Foreign Language Studies, 2(1), 161–168. https://www.qk.sjtu.edu.cn/cfls/EN/10.3969/j.issn.1674-8921.2024.01.013 Creswell JW (2020) Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson Education, London Dale R, Viethen J (2021) The automated writing assistance landscape in 2021. Natural Language Engineering , 27 (4), 511–518. https://doi.org/10.1017/S1351324921000164 Ferris, D. R. (2004). The grammar correction debate in L2 writing: Where are we, and where do we go from here? (and what do we do in the meantime… Journal of Second Language Writing, 13 (1), 49–62. https://doi.org/10.1016/j.jslw.2004.04.005 Godwin-Jones R (2024) Generative AI, Pragmatics, and Authenticity in Second Language Learning. Computation and Language . 1–14. https://arxiv.org/abs/2410.14395 Hayes JR (2012) Modeling and remodeling writing. Writ Communication 29(3):369–388. https://doi.org/10.1177/0741088312451260 Jarrah am, Wardat Y, Fidalgo P (2023) Using ChatGPt in academic writing is (not) a form of plagiarism: What does the literature say. Online J Communication Media Technol 13(4):e202346. https://doi.org/10.30935/ojcmt/13572 Jomaa NJ (2025) Corrective Feedback of AI Tools in Writing and Translation. In: Jomaa N (ed) Using AI Tools in Text Analysis, Simplification, Classification, and Synthesis. IGI Global Scientific Publishing, New York, pp 295–320. https://doi.org/10.4018/979-8-3693-9511-0 Jeon J (2021) Chatbot- assisted dynamic assessment (CA- DA) for L2 vocabulary learning and diagnosis. Comput Assist Lang Learn 30:1–27. https://doi.org/10.1080/09588221.2021.1987272 Kano N (2021) The Efficiency of the Academic Writing System: Can Prewriting Discussion be Eliminated? LET Kanto J 5:39–57. https://doi.org/10.24781/letkj.5.0_39 Karatsareas P (2022) Semi-Structured Interviews. In: Kircher R, Zipp L (eds) Research Methods in Language Attitudes. Cambridge University Press, Cambridge, UK, pp 99–113. https://doi.org/10.1017/9781108867788.010 Kundu A, Bej T (2025) Transforming EFL Teaching with AI: A Systematic Review of Empirical Studies. Int J Artif Intell Educ 1–34. https://doi.org/10.1007/s40593-025-00470-0 Lee I, Yuan RE (2021) Understanding L2 writing teacher expertise. J Second Lang Writ 52:100755. https://doi.org/10.1016/j.jslw.2020.100755 Pessoa L (2008) On the relationship between emotion and cognition. Nat Rev Neurosci 9:148–158. https://doi.org/10.1038/nrn2317 Peters E (2007) Manipulating L2 learners’ online dictionary use and its effect on L2 word retention. Lang Learn Technol 11(2):36–58. http://llt.msu.edu/vol11num2/peters/ Raims A (1983) Techniques in teaching writing. Oxford University Press, New York, NY Ranalli J (2018) Automated written corrective feedback: How well can students make use of it? Comput Assist Lang Learn 31(7):653–674. https://doi.org/10.1080/09588221.2018.1428994 Richards JC (2022) Exploring emotions in language teaching. RELC J 53(1):225–239. https://doi.org/10.1177/0033688220927531 Tsufim F, Pomerleau L (2024) More is less? Using generative AI for idea generation and diversification in early writing processes. In B. Buyserie & T.N. Thurston (Eds.), Teaching and generative AI: Pedagogical possibilities and productive tensions (pp. 99–112). Utah State University. https://uen.pressbooks.pub/teachingandgenerativeai/chapter/more-isless-using-generative-ai-for-idea-generation-and-diversification-in-early-writing-processe s/ Wang C (2024) Exploring Students’ Generative AI-Assisted Writing Processes: Perceptions and Experiences from Native and Nonnative English Speakers. Technology, Knowledge and Learning , 1–22. https://doi.org/10.1007/s10758-024-09744-3 Yang Y (2025) AI-supported L2 vocabulary acquisition–a systematic review from 2015 to 2023. Educ Inform Technol, 1–35 https://doi.org/10.1007/s10639-025-13417-8 Zhao D (2025) The impact of AI-enhanced natural language processing tools on writing proficiency: An analysis of language precision, content summarization, and creative writing facilitation. Educ Inform Technol 30(6):8055–8086. https://doi.org/10.1007/s10639-024-13145-5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6804457","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":509786528,"identity":"ced9a2b2-df3d-4952-9f4e-7264f20c34c1","order_by":0,"name":"Fahad Alqurashi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBAC9gYIncAGZTE2ENLCcwCmBcoiQQuDRAKxWsQOb5OuqKnL45N8Y3ibh8FGdsMB9ocf8GqRTiuTPHPscDGbdI6xNQ9DmvGGAzzGEvi02EvnmEk2sB1IbAMypHkYDicCtTDg1cID1vKvLrFN8gxIy3+gFvbHPwhqaWxjTmyT4AFpOQDUwmBGwJa0YsvGvsOJbTxAxhyDZOOZh3nMLPBrSd54s+FbXeL89sMbb7ypsJPtO97++AY+LUBgAGdJgNnMBNSjaRkFo2AUjIJRgAUAAK68RE2GwojhAAAAAElFTkSuQmCC","orcid":"","institution":"Umm Al-Qura University","correspondingAuthor":true,"prefix":"","firstName":"Fahad","middleName":"","lastName":"Alqurashi","suffix":""}],"badges":[],"createdAt":"2025-06-02 17:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6804457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6804457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94984897,"identity":"5791ccf9-53c4-4c70-8c43-827ed1619d48","added_by":"auto","created_at":"2025-11-03 06:56:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":590388,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6804457/v1/fce50b30-31fe-45df-b8e5-db1b314d00fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"L2 learners’ behavioral and cognitive engagement in AI-supported English writing","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe increasing use of artificial intelligence (AI) is fundamentally transforming the landscape of language education and impacting both the methods educators employ and the ways in which students acquire language skills. AI shows great promise in second/foreign language education. AI-powered tools offer instant feedback on pronunciation, grammar, vocabulary, and structure, which is changing how students think and act in language classrooms and consequently leading to more efficient and engaging learning experiences (Godwin-Jones, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Writing, particularly in a second/foreign language, is a complex task that requires advanced skills and often presents challenges due to potential gaps in syntax, pragmatics style, or rhetoric. In the field of L2 writing, AI generative chatbots act as helpful virtual assistants that provide instant suggestions, which is especially useful for students who have difficulty writing smoothly and accurately (Jomaa, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn L2 writing, artificial intelligence technologies function as virtual assistants that provide immediate corrective feedback, which is especially advantageous for learners facing challenges with writing fluency and accuracy. This real-time support plays a crucial role in helping learners identify and rectify errors as they write, fostering a more effective learning environment. Accordingly, students can practice writing at their own pace, allowing for a more personalized learning experience. This self-directed approach encourages learners to explore their writing styles and experiment with language without the constant need for teacher intervention which promotes independent learning and inspire students to edit their own work. Furthermore, it helps students build critical editing skills, increase their confidence by offering different ways to express themselves, gain trust in their abilities, and adopt a proactive approach to writing (Wang, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, cognitive factors, such as perceived usefulness and ease of use along with motivational factors such as perceived enjoyment and emotional engagement in the use of AI systems are significant to consider for understanding their impact of virtual assistants on student learning. Recognizing these factors is crucial for harnessing the full potential of AI in educational and professional writing contexts. By examining such factors, educators and developers can better analyze students\u0026rsquo; attitudes and foster a positive interaction atmosphere to utilize generative AI that can lead to increased confidence, enhanced writing competence, and a more enriching overall writing experience, which in turn optimize the learners\u0026rsquo; intellectual and personal development (Richards, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This research adds to the ongoing discussion about the role of AI in language learning and explores how L2 learners perceive and use AI-powered tools when writing in English as a foreign language.\u003c/p\u003e\n\u003ch3\u003eLiterature Review\u003c/h3\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eUsing AI Tools in L2 Writing\u003c/h2\u003e\u003cp\u003eInitial studies on AI in language education centered on automated writing evaluation (AWE) tools like Pigai and Grammarly, representing the first step in incorporating AI into writing instruction. Much of the research evaluated how well these tools worked within different teaching methods and their potential to enhance writing skills through immediate feedback and structured support. With the emergence of AI generative tools such as ChatGPT, research is now broadening to investigate a wider array of AI applications in English writing instruction. This step reflects a growing interest in how AI can support various aspects of the writing process, from brainstorming ideas to refining drafts. Ongoing research will help identify best practices and optimize the use of AI in fostering writing skills among students (Aljuaid, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Despite progress in AI-generated feedback, differences persist in how effectively they improve language skills, often due to methodological and contextual variables, such as various feedback approaches: AI-only, combined teacher and AI response, or peer response (Zhang \u0026amp; Hyland, 2018; Kundu \u0026amp; Bej, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe swift development of AI technologies has greatly increased their importance in second/foreign language education. Researchers are now examining how AI affects different parts of English writing, including the writing process itself, how humans, academic honesty, and AI work together. Recent studies indicated that AI generative chatbots can perform tasks typically done by teachers, such as creating activities, providing language and cultural information, overseeing language use, and reviewing essays. As a result, teachers may take on new roles, such as AI trainers, evaluators, risk managers, and reflection facilitators. This change redefines the teacher\u0026rsquo;s role in AI-supported writing instruction and highlights the need for teachers to become more knowledgeable about AI As technology plays a larger part in the writing process. Accordingly, teachers need to familiarize themselves with various AI applications and their functionalities. Teachers also must adapt their approaches to effectively integrate these technologies into their teaching and support student learning (Chen \u0026amp; Lv, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMore particularly, AI technologies augmented written corrective feedback (WCF) which is an essential part of the writing process to provide students with targeted guidance to improve their writing skills. These tools provide synchronous and immediate corrective feedback that meet individual students\u0026rsquo; needs in identifying errors and suggesting corrections. Human-AI Collaboration could lead to facilitate tasks such as spotting research ideas, reviewing drafts, creating outlines, providing insights, and improving the overall quality of writing. L2 writing students who actively and repeatedly interacted with AI tools were found to produce better writing than those who simply used AI as an extra resource (Ranalli, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These developments have been made possible by AI applications and systems that gather extensive data sets and utilize artificial neural networks and machine learning technologies. This has led to significant improvements in transforming text into structured data and extracting meaning through AI-driven natural language processing (NLP) and natural language understanding (NLU).\u003c/p\u003e\u003cp\u003eHowever, incorporating AI into L2 writing has raised concerns about academic honesty, especially the risk of plagiarism. The extensive access to digital resources and essay-writing services has made cheating easier. AI technologies, including paraphrasing tools and deepfake content generators, complicate the detection of conventional forms of plagiarism. Educational institutions might have to develop clear guidelines and policies regarding the use of AI in academic settings. These policies should educate students about the ethical implications of using AI and emphasize the importance of original thought and proper attribution. For example, while plagiarism detection systems are used to uphold academic standards, it is crucial to educate students about proper writing practices at the same time. This proactive approach not only discourages academic dishonesty but also fosters a deeper understanding of academic integrity among students. These caveats emphasizes the need for more research into human-AI collaboration to address multiple controversies surrounding AI-supported writing instruction, stressing the need for AI developers and education researchers to work together to prevent both obvious and subtle forms of academic misconduct (Dale \u0026amp; Viethen, 2021).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAI in Language Learning: Learner Perspectives\u003c/h3\u003e\n\u003cp\u003eResearch in L2 learner cognitive psychology emphasizes that various factors including perception, attention, behavior, emotion, motivation, cognition, and memory deeply interact with and significantly influence teaching and learning outcomes. Among these, learner behavior, emotion, and cognition are three interconnected elements that play a crucial role in shaping educational experiences. Emotions and cognition directly affect human behavior and the nature of learning behaviors, such as engagement and participation which impact academic results (Pessoa, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Positive learning behavior, characterized by active involvement in various academic tasks, is essential for achieving favorable academic outcomes. Likewise, emotions, whether positive (like interest and happiness) or negative (such as boredom, sadness, and anxiety), can trigger corresponding responses that affect learning processes. Cognition encompasses psychological investment and the learning strategies needed to understand complex concepts and master advanced skills. The integration of artificial intelligence has fundamentally reshaped the landscape of foreign language education in several transformative ways and created significant advancements in how languages are taught and learned, and how the writing process becomes more efficient and engaging (Zhang \u0026amp; Hyland, 2018).\u003c/p\u003e\u003cp\u003eMore particularly, the traditional dyad of \"teacher-student\" has evolved into a more complex and potentially richer \"teacher-student-AI\" triad. This shift is driven by the capacity of AI to personalize learning experiences and provide immediate feedback and targeted support. Research consistently demonstrates a generally positive reception from students towards AI-powered language instruction. This stems from the ability of different chatbots to adapt to individual learning needs and paces and offer a customized educational experience that traditional methods often struggle to achieve. Students appreciate the real-time guidance and instant response provided by AI, which allow them to immediately identify and correct errors and foster a more efficient and effective learning process (Wu et al., 2024). Specifically, when writing in English as a second/foreign language, L2 learners acknowledge AI\u0026rsquo;s significant contribution to educational innovation. Research in this area reported progressive attitudes and positive perceptions of L2 learners about utilizing AI which noticeably enhances their motivation to write and demonstrably improves their writing skills ((Alsadoon, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese transformations suggest that AI is not merely a supplementary tool but a catalyst for skill development in crucial aspects of writing proficiency. Moreover, research indicates that when AI is thoughtfully employed and appropriately integrated into the learning process, it can provide efficient and targeted support, leading to a boost in students\u0026rsquo; motivation, engagement, and overall confidence in tackling academic tasks. This increased confidence, coupled with the efficient support provided the teacher, ultimately facilitates students\u0026rsquo; progress in writing and contributes to a more positive and productive learning experience (Feng, 2025). In essence, the \"teacher-student-AI\" triad represents a potentially powerful synergy, where the teacher provides guidance and expertise, the student actively engages in the learning process, and AI offers personalized support and feedback, creating a more dynamic and effective learning environment. However, the \"when used appropriately\" stipulation is crucial, highlighting the need for careful consideration of pedagogical strategies and ethical implications when integrating AI into language education (Kundu \u0026amp; Bej, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the growing interest in AI technology, research on its application in L2 teaching and learning remains limited. Specifically, studies focusing on the cognitive psychology of L2 learners regarding AI-driven written corrective feedback (WCF) are particularly scarce. This area requires a complex, multidisciplinary understanding that spans AI technology, linguistics, and cognitive psychology, among other fields. This study aims to fill this gap by examining learners\u0026rsquo; behavioral and cognitive involvement in AI-supported English writing, focusing on the following two research questions:\u003c/p\u003e\u003cp\u003eQ1: What are the common ways students interact with and utilize AI in English writing?\u003c/p\u003e\u003cp\u003eQ2: How do students recognize, perceive, and evaluate the function of AI when writing in English as a foreign language? What benefits do they see in the use of AI for various aspects of writing?\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eThe study involved 54 male undergraduate English-major students enrolled in two sections of the \u003cem\u003eAdvanced Writing\u003c/em\u003e course, which is part of the fourth level of the Bachelor of Arts program at a university in Saudi Arabia. These students had previously completed three levels of writing courses during their first three semesters in the program, providing them with a solid foundation in writing skills. Throughout their initial coursework, the participants encountered a variety of writing tasks designed to enhance their proficiency. They studied under different instructors, each bringing unique teaching styles and perspectives. This exposure allowed the participants to engage with diverse writing genres, ranging from paragraphs to essays, which enriched their understanding of writing\u0026rsquo;s multifaceted nature. Additionally, the participants engaged in numerous peer response activities, fostering collaborative learning and critical feedback skills. This interaction not only helped them refine their writing but also encouraged them to think critically about their peers\u0026rsquo; work. Throughout the process, they received various forms of written corrective feedback, which guided their improvement and development as writers. Overall, the participants\u0026rsquo; experiences and interactions in the writing program were diverse and enriching and contributed to a well-rounded understanding of writing.\u003c/p\u003e\u003cp\u003eEthical considerations regarding the protection of participants\u0026rsquo; rights and well-being were thoroughly examined during the development of this study to ensure the integrity of the research process. The researcher first secured approval from the Institutional Review Board (IRB) at the university, which involved a detailed review of the study\u0026rsquo;s design, purpose, and potential risks. This step was crucial for safeguarding participants\u0026rsquo; rights and welfare. This approval was essential not only for compliance with institutional policies but also for fostering trust between the research team and the university community. To further ensure ethical standards, the researcher informed students that participation in the study was entirely voluntary, meaning that students could choose whether or not to participate without any repercussions on their academic evaluations. This transparency was vital in promoting a sense of autonomy among participants. Moreover, the researcher assured students that all data collected would remain confidential and used only for research purposes. These ethical safeguards were designed to create a respectful and secure environment for participants, ultimately enhancing the credibility and reliability of the research findings.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eInstruments\u003c/h3\u003e\n\u003cp\u003eData for this study were gathered using a combination of qualitative instruments that included classroom observations, student reflective journals, and semi-structured interviews. Using a multi-method qualitative approach can enrich the exploration of language learning by combining various data collection techniques that are effective in gathering in-depth insights into participants\u0026rsquo; experiences, emotions, and perspectives on language learning and AI tool usage (Creswell, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Classroom observations are employed in research to yield rich and detailed insights into students\u0026rsquo; behaviors, interactions, and overall activities within the classroom. By analyzing this data, educators can better contextualize students\u0026rsquo; experiences, identifying their strengths and areas for improvement. This understanding is crucial for tailoring instructional strategies to meet individual learning needs, ensuring that the integration of AI tools effectively supports students\u0026rsquo; writing development and enhances their educational experience. Ultimately, these insights can inform future teaching practices and AI tool implementation, promoting a more effective learning environment (Alam \u0026amp; Mohanty, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStudent reflective journals in language education serve as a powerful tool for enhancing learning and self-awareness and encourage students to reflect on their learning experiences, helping them identify strengths and areas for improvement. Reflective writing fosters critical thinking by prompting students to analyze their experiences, challenges, and successes in language learning. Students also can set personal language goals and track their progress over time, which can motivate them to stay engaged (Barber, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Semi-structured interviews are a good instrument designed to facilitate meaningful discussions about different aspects pertinent to language learning. This flexible format allow for exploring various topics including participants\u0026rsquo; experiences with AI tools, emotional responses to interactive learning activities, the impact of personalized feedback on language skill development, and the influence of motivation and autonomy on engagement. Participants also could discuss any issues related to challenges they encountered (Karatsareas, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eProcedures\u003c/h2\u003e\u003cp\u003eThe researcher initiated the study by offering a concise overview of its nature and objectives. This introduction aimed to clarify the purpose of the research and outline the key themes and questions that would be explored. By doing so, the researcher set the stage for a meaningful dialogue to ensure that students understood the context and relevance of their participation. To foster an open and inclusive atmosphere, the researcher encouraged students to voice any pertinent issues or concerns they might have. This invitation was crucial for creating a safe space where participants felt comfortable to share their thoughts and experiences. By actively engaging students in this manner, the researcher aimed to promote a collaborative environment and emphasize the value of their insights in shaping the study\u0026rsquo;s findings.\u003c/p\u003e\u003cp\u003eOver a period of 12 weeks during the semester, the participants had access to different AI-powered tools on their smart phones. Accordingly, classroom observations were carried out to closely monitor and analyze how students utilized AI chatbots in writing English as a foreign language. These observations aimed to examine the dynamics of student interaction with AI, particularly how they integrated AI-generated feedback into their drafts for various writing tasks and to meticulously track and document the diverse activities students undertake while using these chatbot. This includes noting how they initiate tasks, seek assistance, and integrate feedback provided by the AI. Observations also focused on the collaborative dynamics among students, as they often engage in discussions about their writing, share tips, and provide peer response in conjunction with AI suggestions. By closely monitoring these interactions, the researcher aimed to verify the various techniques to benefit from AI-generated feedback and gain a clearer understanding of how these technologies influence student engagement and motivation.\u003c/p\u003e\u003cp\u003eIn Week 8 of the semester, students were prompted to complete a reflective journal focused on their experiences with AI support in L2 writing. This exercise aimed to foster deeper engagement with their learning journey and encourage them to articulate their thoughts on how technology integrates into their writing practices. The journal entries were crafted to explore various aspects of utilizing AI, such as its impact on their writing skills, motivation, and overall confidence. By reflecting on these experiences, students could gain valuable insights into their growth and challenges. In particular, the journal entries included:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInitial Thoughts\u003c/strong\u003e\u003cp\u003eStudents began by articulating their expectations and initial feelings about using AI in their writing. This set the stage for understanding their mindset before engaging with the technology.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDocumentation of Methods\u003c/strong\u003e\u003cp\u003eStudents were encouraged to describe the specific ways they utilized AI tools throughout their writing tasks. This included detailing the types of AI applications they employed, such as grammar checkers, content generators, or research assistants. By documenting these methods, students could better understand how these tools influenced their writing strategies.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eIdentifying Challenges\u003c/strong\u003e\u003cp\u003eThis stage focused on introducing the challenges encountered while using AI. This included technical difficulties, such as software malfunctions or navigation issues, as well as conceptual challenges, like understanding how to effectively incorporate AI-generated suggestions into their own writing. Identifying these obstacles helped students recognize areas for improvement and seek solutions.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAssessment of Effectiveness\u003c/strong\u003e\u003cp\u003eStudents were prompted to evaluate the overall effectiveness of AI tools in supporting their writing process. This involved reflecting on whether AI enhanced their writing quality, improved their productivity, or helped them gain new insights into their writing style. By assessing the impact of AI, students could critically analyze its role in their academic development.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConcluding Insights\u003c/strong\u003e\u003cp\u003eIn their final entries, students summarized their overall experiences, highlighting key takeaways and personal growth. They reflected on how their perceptions of AI shifted over the course of their writing assignments and how they planned to integrate AI tools into future academic endeavors.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eAt the conclusion of the semester, 11 students volunteered for 30-minute semi-structured interviews. These interviews provided an opportunity for deeper insights and were conducted alongside the reflective journal analysis. With the students\u0026rsquo; consent, the interviews were recorded and subsequently transcribed to allow for a thorough examination of their perspectives and experiences regarding the use of AI in their writing. Also, the students had the opportunity to talk freely about any other aspects that affected their learning and raise any issues related to their ability and skills to utilize AI-powered tools effectively in writing in English. This multi-faceted approach ensured a rich collection of qualitative data to enhance the study\u0026rsquo;s findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThis study utilized qualitative thematic analysis to interpret the data and derive significant themes from the participants\u0026rsquo; input collected through the three instruments. This approach involved using multiple data sources to create a more comprehensive understanding of the research topic. In this study, interviews and reflective journals were identified as the primary data sources to capture students\u0026rsquo; personal insights and experiences regarding the use of AI in their writing processes. Audio recordings from interviews were transcribed verbatim, allowing for a faithful representation of the participants\u0026rsquo; voices. Furthermore, student reflective journals were collected to gain insights into their views and attitudes toward using AI systems to learn L2 writing.\u003c/p\u003e\u003cp\u003eThe complete transcripts from interviews and student journals were then thoroughly reviewed to facilitate in-depth exploration of individual perspectives, extract key experiences that reflected student engagement with AI tools, and identify recurring patterns within the data. These patterns were then carefully categorized and coded into specific themes, ensuring clarity, meticulousness, and precision throughout the analysis in order to reach a comprehensive understanding of students\u0026rsquo; reactions and capture the nuances of their experiences and insights. The analysis process consisted of three levels of coding which illustrates the transition from initial codes to overarching themes as follows:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOpen Coding\u003c/strong\u003e\u003cp\u003eThe analysis began with a thorough examination of the textual data, with open coding conducted line by line and sentence by sentence. This meticulous approach aimed to identify initial codes that encapsulated key ideas and recurring patterns within the data.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCategorization\u003c/strong\u003e\u003cp\u003eOnce initial codes were established, similar codes were grouped together to form preliminary themes. For instance, first-level codes such as \u0026ldquo;corrections,\u0026rdquo; \u0026ldquo;improvement,\u0026rdquo; and \u0026ldquo;difficulties\u0026rdquo; were categorized under a second-level code labeled \u0026ldquo;writing processing.\u0026rdquo; This categorization helped streamline the data and highlighted the interconnectedness of various concepts.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTheme Development\u003c/strong\u003e\u003cp\u003e Following categorization, the second-level codes were reviewed, compared, and subjected to further analysis to identify central themes that represented the core findings of the study. For example, codes like \u0026ldquo;writing processing,\u0026rdquo; \u0026ldquo;strategic support\u0026rdquo; and \u0026ldquo;content generation,\u0026rdquo; were synthesized into a primary theme indicating that AI significantly contributes to writing efficiency. This theme reflects the broader implications of AI tools in enhancing students\u0026rsquo; writing processes.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eTo ensure both consistency and validity in the analysis, the study utilized data triangulation, as recommended by Creswell (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Alongside primary sources, classroom observations were conducted to validate and triangulate participants\u0026rsquo; feedback, offering valuable complementary insights. By observing students in real-time as they interacted with AI tools in an academic writing setting, the researcher gathered contextual information that enriched the overall analysis. The observational data supported the findings from reflective journals and interviews and provided a broader perspective on students\u0026rsquo; practical interactions with AI. This multi-source approach enhanced the analysis and credibility of the study by corroborating results across various data collection methods. Consistent categories were applied across the datasets to develop main codes and themes and promote a cohesive exploration of the relationships among the three datasets which facilitated a deeper understanding of participants\u0026rsquo; perceptions and preferences. Triangulation ensured that the identified themes accurately reflected students\u0026rsquo; experiences, reinforcing the reliability of the conclusions and offering a nuanced interpretation of how AI influences L2 writing.\u003c/p\u003e\u003cp\u003eTo further enhance the credibility and validity of the study\u0026rsquo;s analytical process the researcher worked alongside two independent raters, who provided additional perspectives and insights during the review of student participation. This collaborative effort not only enhanced the rigor of the coding and thematic development but also ensured that the findings were well-rounded and reflective of the participants\u0026rsquo; true experiences. By incorporating multiple viewpoints, the analysis was bolstered, leading to more reliable and valid conclusions regarding the effectiveness of generative AI written corrective feedback in L2 context. The three evaluators achieved a 92% agreement rate on the codes and themes from participants\u0026rsquo; responses which indicates strong inter-rater reliability. This high agreement suggests successful investigator triangulation that helps reduce researcher bias (Bryfonski, 2023).\u003c/p\u003e\u003c/div\u003e"},{"header":"Findings \u0026 Discussion","content":"\u003cp\u003eThe qualitative thematic analysis reveals that students perceive AI as a valuable support tool in writing in English as a foreign language and make use of its sophisticated benefits and implications for their learning processes. AI fosters a positive attitude toward writing by creating an encouraging and supportive environment that motivates learners to engage actively in writing tasks. This encouragement is achieved through several key mechanisms. For example, consulting chatbot about different writing aspects reduced anxiety about writing, particularly in a foreign language. Several participants mentioned in the journals and interviews that \u0026ldquo;\u003cem\u003ewriting isn\u0026rsquo;t a problem with AI. It became fun\u003c/em\u003e,\u0026rdquo; \u0026ldquo;\u003cem\u003eI don\u0026rsquo;t worry about essay assignments\u003c/em\u003e,\u0026rdquo; \u0026ldquo;\u003cem\u003eI wish we were allowed to use AI last semester to write better and get good grades.\u0026rdquo;\u003c/em\u003e These responses reflect a positive attitude toward writing. It is clear that the participants enjoyed the ability of AI to create a supportive, engaging, and personalized writing environment. AI writing tools create a non-judgmental space where students can experiment with their ideas and language without the fear of negative critique, thus promoting a more positive writing experience. Such emotional/motivational advantages promoted various academic benefits as follows:\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e1. Enhancing Writing Quality\u003c/h2\u003e\u003cp\u003eEffective writing is a multifaceted endeavor that goes beyond mere language proficiency. It requires a combination of linguistic skills, relevant content, and logical structure. It also involves a keen awareness of the writing\u0026rsquo;s purpose, whether to inform, persuade, entertain, or analyze, and audience\u0026rsquo;s background, expectations, and preferences. Producing relevant content necessitates a genuine interest in the subject matter as well as a solid understanding of the topic at hand. Student-writers must be able to gather and synthesize information effectively and ensure that their arguments are well-supported and grounded in credible sources. Student-writers achieve writing proficiency by integrating these elements where they can produce high-quality work and construct clear, relevant, and logical arguments that communicate their message appropriately and resonate with readers successfully (Kano, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Raims, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). Participants\u0026rsquo; input from journals and interviews and results of observation confirmed that they found AI very helpful in optimizing their writing quality and achieving greater success in their writing endeavors.\u003c/p\u003e\u003cp\u003eStudents widely recognized that AI is a significant tool to optimize their language use, which, in turn, enhances the readability and quality of their writing at different levels. This recognition is evident in their reflective journals and interview responses, where they detail the various ways AI chatbots support their writing endeavors. One of the participants stated in his journal, \u0026ldquo;\u003cem\u003eI ask Chatly to give me ideas and arguments for the topic, so I have no problem in this step. This makes my writing good.\u003c/em\u003e\u0026rdquo; Another participant mentioned in the interview that in some cases he wrote sentences in Arabic and used AI to translate those parts into English. This focus on quality enhancement allows learners to refine their writing and express ideas more clearly, making their arguments easier to understand and their compositions richer and more polished. Previous studies indicated that implementing personalized interventions and utilizing a variety of AI-powered tools helped students engage in focused activities that significantly enhanced their writing abilities and equipd them with the skills necessary for success in various writing contexts (Zhao, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eParticipants in this study were observed to take advantage of different AI writing tools as effective means to boost up both the writing process and the final output. In particular, the participants made use of those tools to increase the writing quality enabling them to present a clear and unique perspective in their texts. A third student revealed in his journal, \u0026ldquo;\u003cem\u003eWordtune helped me to fix errors and make adjustments, but the best thing is help with paraphrasing. Now I don\u0026rsquo;t worry about writing the same ideas in different ways\u003c/em\u003e.\u0026rdquo; AI-powered tools helped participants refine their language, ensuring that their ideas were articulated clearly. This clarity makes it easier for readers to understand the main arguments and themes presented in their writing. With advanced algorithms, those tools can analyze text and provide feedback that enhances both the content and the overall flow of ideas. EFL student-writers could utilize AI suggestions to modify content to match specific tones, improve engagement and effectiveness and ensure consistency across the essay (Wang, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMost students seemed very inspired by the help of AI writing tools. Several students mentioned during the interviews that they usually use two or three of these tools to check their drafts and compare the suggestions because they want to \u0026ldquo;\u003cem\u003ebe as perfect as possible\u003c/em\u003e,\u0026rdquo; \u0026ldquo;\u003cem\u003eget full marks\u003c/em\u003e,\u0026rdquo; or \u0026ldquo;\u003cem\u003eknow how write things in different ways.\u003c/em\u003e\u0026rdquo; By prioritizing quality, students learn to critically evaluate their work and strive for excellence. This commitment leads to more thoughtful writing, where clarity, coherence, and creativity are emphasized. Frequent revisions promote greater awareness of the writing process. Students learn to identify areas for improvement and understand the importance of drafting, feedback, and revision in developing quality writing. One significant advantage of Automated Writing Evaluation (AWE) systems is that they allow students to revise their drafts as many times as needed before submission. This flexibility encourages a more iterative approach to writing, where learners can refine their work continually (Hayes, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2. Instant Feedback\u003c/h2\u003e\u003cp\u003eTraditionally, written corrective feedback (WCF) has involved teachers manually marking students\u0026rsquo; written assignments to identify errors and suggest improvements (Ferris, 2004). Previous studies highlighted the significance of written corrective feedback on students\u0026rsquo; work to help them identify and correct errors, which promotes their composing skills and facilitates the revision process (Bitchener \u0026amp; Knoch, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). While this method has shown effectiveness, it is often time-consuming, may lack consistency, and can place a significant burden on teachers when they are required to provide immediate feedback to every student, especially in classes with a large number of students (Wang \u0026amp; Jiang, 2014). Research on automated written corrective feedback (AWCF) and various forms of digital corrective feedback (DCF) has produced mixed findings, yet it does indicate their positive impact in providing several features that set it apart from traditional teacher-fronted feedback.\u003c/p\u003e\u003cp\u003e The participants in this study were observed to consult different AI-powered tools to check various aspects of their writing and seemed happy to get immediate responses. They ask questions like: \u0026ldquo;\u003cem\u003eIs this sentence correct?\u003c/em\u003e\u0026rdquo; and \u0026ldquo;\u003cem\u003eHow can I improve this idea?\u003c/em\u003e\u0026rdquo; Some participants were heavily reliant on AI when asking questions such as \u0026ldquo;\u003cem\u003eWhat should I write next?\u003c/em\u003e\u0026rdquo; and \u0026ldquo;\u003cem\u003eIs this enough or should I explain more?\u003c/em\u003e\u0026rdquo; which indicates huge trust in AI feedback. The quick processing of AI feedback allows students to make timely revisions and reinforce their trust in the tool\u0026rsquo;s reliability especially it is based on algorithms and data, which can make it seem more objective and reduce bias, compared to human feedback (Barrot, 2021). Key distinctions of AI-supported corrective feedback include:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eRapid Error Identification\u003c/strong\u003e\u003cp\u003eAI systems can quickly identify a wide range of errors and provide comprehensive corrections within seconds, allowing students more time to revise their work and correct mistakes promptly. Research shows that instant feedback effectively draws students\u0026rsquo; attention to errors, leading to more efficient corrections (Lee, 2017). Receiving feedback immediately after completing a writing task help L2 writers to address errors while the content is still fresh in their minds. This immediacy helps reinforces learning and ensures that they can connect corrections to specific parts of their writing. When feedback is provided swiftly, students are more likely to remember the corrections and understand the rationale behind them. This leads to better retention of the concepts and strategies discussed in the feedback. Moreover, Instant responses can help students, who often feel anxious about receiving feedback, to alleviate some of that anxiety, as learners can see where they stand and understand their progress without prolonged uncertainty (Ranalli, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eReal-Time Metalinguistic Explanations\u003c/strong\u003e\u003cp\u003eAI writing tools offer consistent and accurate metalinguistic explanations in real time, which teachers may struggle to provide due to time constraints. Unlike teachers, who may need time to review and respond to each student\u0026rsquo;s work, AI can provide feedback right when each student needs explanations. When combined with direct corrections, these explanations help learners address errors, reflect on their use of feedback, and consider more choices. This reflection is an essential step for the development of critical thinking skills and deeper understanding of the writing process. In addition, the metalinguistic explanations generated by chatbots are based on established linguistic rules and patterns, reducing the likelihood of human error. This accuracy enables students to learn the correct usage and reasoning behind their mistakes (Woodworth \u0026amp; Barkaoui, 2020).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNeutral \u0026amp; consistent Feedback\u003c/b\u003e: The feedback generated by automated writing systems is inherently neutral and provides several important benefits that enhance the learning experience for students. AI provides feedback that is solely focused on the writing itself. This kind of feedback is not influenced by the teacher\u0026rsquo;s mood or state of mind, such as fatigue from grading or personal attitudes toward students. This means that students receive evaluations based on their work rather than any external emotional states of the teacher. AI systems deliver uniform feedback for similar errors across different pieces of writing. Such consistency allows students to receive the same level of critique each time they submit work which fosters a fair learning environment. Automated feedback is based on predefined algorithms and linguistic rules to ensure that evaluations are objective and not subject to personal biases. This objectivity helps maintain consistent standards across all students, regardless of any external factors (Barrot, 2021).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3. Enriching Content \u0026amp; Organization\u003c/h2\u003e\u003cp\u003eThe content and organization of writing are equally significant components and considerably crucial for enhancing reader understanding and engagement. Content is the core of writing, encompassing the ideas and messages the writer wants to convey. It is the real substance, the \u0026ldquo;what,\u0026rdquo; of the writing. High-quality content is relevant, informative, original, and meaningful, effectively serving its purpose, whether to inform, persuade, entertain, or provoke thought. Students participating in this study stressed that AI-powered tools can extensively assist them in brainstorming and fostering a clear, logical flow of thoughts in several ways. A participant mentioned in his journal, \u0026ldquo;\u003cem\u003eI don\u0026rsquo;t have to worry about creating more ideas. Quillbot gives me hundreds of them each time.\u003c/em\u003e\u0026rdquo; Generating a wide range of ideas based on different prompts is a key aspect in AI assistance to overcome writer\u0026rsquo;s block and explore different angles on a topic. By providing multiple viewpoints, AI encourages students to consider various aspects of a subject, enriching their understanding and creativity (Tsufim \u0026amp; Pomerleau, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAI-mediated structured prompts have been found useful to offer valuable guidance to students in developing their ideas systematically. AI assistance covers essential composing points which positively affects their ability to construct logical arguments and cohesive narratives. Another participant highlighted the following points during the interview, \u0026ldquo;\u003cem\u003eIn many cases I don\u0026rsquo;t know what to say next. I feel I come to a dead end. AI solved this problem. AI opens my eyes to hidden parts so I can write more. It helps also with giving many examples so I can sound more convincing.\u003c/em\u003e\u0026rdquo; L2 learners in many settings have utilized AI writing tools in fostering a clear and logical flow of thoughts in written work and suggesting better phrasing to express their ideas more succinctly and effectively. Also, they used AI writing tools to detect logical inconsistencies in arguments, alerting to areas where their reasoning may be flawed. This critical analysis encourages a more robust and persuasive argumentation structure to enhance the readability of the text (Wang, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOn the other hand, organization refers to the structure of the writing that determines how content is arranged and how ideas are connected. Effective organization guides the reader logically through the piece, impacting comprehension, persuasiveness, and engagement. Good organization ensures a smooth flow of ideas, making the writing clearer and more impactful (Lee \u0026amp; Yuan, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). AI- powered writing tools can help arrange ideas and structure content logically to ensure that arguments are clearly presented to improve text coherence. Previous studies in the Saudi context reported that L2 learners found AI very helpful in providing tips on how to select the right words and phrases as transitional language elements for linking ideas in writing and enhancing its fluidity and consistency. By processing students\u0026rsquo; texts, AI-mediated tools analyze the flow of ideas and suggest modifications that improve transitions between sentences and paragraphs to clarify how ideas relate to one another and certify that the writing feels cohesive and logical (AlGhamdi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e One of the participants expressed diverging opinions in the interview about AI help with organization. He said, \u0026ldquo;\u003cem\u003eI always thought that I can arrange my ideas very well. Everything looked fine. However, ChatGPT changed my sentences and put them in a different order. They look good now also and the teacher was happy with the essay. I just want more marks.\u003c/em\u003e\u0026rdquo; Usually L2 writers tend to express each idea individually without looking at the broader context. AI writing tools can suggest appropriate transitional words and phrases based on the context of the writing to serve as bridges between sentences and paragraphs, clarify relationships and priorities among ideas, reinforce the writer\u0026rsquo;s intent, and help to guide the reader through the text. This guidance helps students learn how to effectively incorporate transitions, build compelling and well-supported arguments, highlight essential components such as claims, evidence, and counterarguments, which helps to develop a deeper understanding of effective writing techniques (Tsufim \u0026amp; Pomerleau, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4. Vocabulary and Style Suggestions\u003c/h2\u003e\u003cp\u003eWriting motivates learners to explore and employ a variety of vocabulary to express their ideas, which is essential for effective communication. In searching for suitable words for different contexts, L2 learners\u0026rsquo; vocabulary collection grows and their language skills develop. This process not only improves their writing abilities but also boosts their confidence and enhances their overall communication skills (Nation, 2009). Due to different levels of proficiency constraints in the target language, L2 writing learners often face several difficulties in word choice that can hinder their writing effectiveness. Technology-assisted vocabulary learning and teaching methods were introduced in the field of Computer-Assisted Language Learning (CALL) through which researchers explored various tools, such as online dictionaries, to improve vocabulary learning outcomes (Peters, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). More recently, AI-enhanced writing systems have been widely utilized to provide recommendations for word choice and stylistic improvements, helping writers to reinforce the sophistication of their writing. Those automated systems serve as powerful tools for language learning and enhancing vocabulary acquisition while simultaneously offering valuable diagnostic insights into individual learners\u0026rsquo; progress.\u003c/p\u003e\u003cp\u003eOne of the participants mentioned in the interview, \u0026ldquo;\u003cem\u003eQuillbot helped me to remember many words that I took before. I can\u0026rsquo;t imagine I forgot those words.\u003c/em\u003e\u0026rdquo; Obviously, memorizing vocabulary is a crucial initial step in effectively learning a second/foreign language. AI systems aid learners in retaining less frequently used words by simulating human long-term memory processes. This approach is based on the idea that memories fade over time but can be strengthened through spaced repetition (Ebbinghaus, 2013). Another participant highlighted, \u0026ldquo;\u003cem\u003eUsually when I write I mix things up, but now I started to distinguish the right word to use in the right place. ChatGPT is very generous with giving many options.\u003c/em\u003e\u0026rdquo; AI-generated prompts provide examples of vocabulary in relevant contexts and tailor exercises and suggestions to meet individual needs, helping students understand how words are used in different situations. Such engaging encounters provide learners with context-rich learning experiences and reinforces appropriate vocabulary usage, ultimately leading to improved language proficiency (Jeon, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAfter all, making use of adequately advanced vocabulary in writing is one of the challenges that face even higher proficiency L2 leaners as they may still have limited exposure to sophisticated vocabulary in real-world contexts. Advanced vocabulary often carries nuanced meanings and connotations that can be difficult to navigate. Without frequent encounters with advanced terms, L2 learners may struggle to integrate them effectively into their writing. They may find it difficult to grasp these subtleties which could lead to potential misuse or overgeneralization of certain terms. Previous studies on Saudi L2 learners reported that AI can help bridge this gap by providing learners with curated examples of advanced vocabulary in context, allowing them to see how these words function in authentic writing and conversation. AI can play a crucial role in teaching these subtleties. By providing definitions, usage examples, and explanations of connotations, AI writing tools can help learners understand the complexities of advanced words. This targeted instruction can enhance their ability to choose the right words for specific contexts, which in turn improves their writing skills and communicative competence (Alsadoon, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition, AI provided students with effective vocabulary-based strategies to enhance clarity, variety, and engagement in the text. One of those strategies is using synonyms to help maintain reader interest, improve the flow of the text, and avoid repeating the same words which can make writing monotonous. A third participant mentioned in the interview, \u0026ldquo;\u003cem\u003eFinding synonyms or good words is not a problem anymore. Instead of one word you can have many of them.\u003c/em\u003e\u0026rdquo; AI writing tools help students in many different cases to minimize unnecessary repetition and avoid redundancy in their writing. During observation, the participants in this study seemed happy with diverse and innovative suggestions for restructuring sentences which allowed them to avoid overusing basic vocabulary that can result in repetitive and unengaging writing. To improve text attractiveness and readability, L2 writers should avoid unnecessary repetitions by incorporating a range of synonyms to demonstrate a strong command of language and make writing more sophisticated (Yang, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEach writer possesses a unique style characterized by distinct word choices, sentence structures, and rhetorical devices that reflect their individuality. This individuality enhances the aesthetic quality of writing, as variations in sentence length and structure create rhythm and emotional impact. AI programs provide diverse feedback to optimize clarity and improve style. For instance, a fourth participant stressed in the journal, \u0026ldquo;\u003cem\u003eI wrote two examples in the last essay, but Chatly said they are one because you are expressing the same idea. So I combined the two examples in one and Chatly gave me another good example.\u003c/em\u003e\u0026rdquo; AI can suggest alternative phrases and claims to maintain the writing style and avoid repetition, which enriches the text and makes it more engaging. Chatbots may also prompt writers to explore additional points or consider larger, more complex concepts, thus deepening their arguments. For example, an AI might encourage learners to reflect on how their ideas relate to societal trends or theoretical frameworks, fostering critical thinking and a more nuanced approach to writing (Zhao, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study contributes valuable insights into the Saudi context, enhancing the growing body of research on AI applications in L2 education. It demonstrates the transformative potential of AI-driven dynamic writing platforms in second and foreign language learning settings. The study provides a comprehensive assessment of Saudi undergraduate English-major students\u0026rsquo; views on AI-powered tools for L2 writing. The findings of this research accentuate the dual impact of AI platforms, enhancing both the technical aspects of writing and fostering a positive attitude toward writing as a creative endeavor. Overall, these tools are well-received and positively influence participants\u0026rsquo; writing quality and efficiency. More particularly, utilizing adaptive and interactive AI chatbots facilitate effective written corrective feedback (WCF), and lead to measurable improvements in students\u0026rsquo; writing skills, including fluency, coherence, lexical diversity, style, and grammatical accuracy. Moreover, these platforms significantly boost learners\u0026rsquo; motivation to engage in writing tasks, helping bridge the gap between technical skill acquisition and emotional involvement.\u003c/p\u003e\u003cp\u003eFurthermore, the current research makes a significant contribution to the field of teaching English as a foreign language (EFL) by illustrating how artificial intelligence (AI) can improve linguistic skills and foster learner autonomy. The results emphasize the necessity of incorporating such technologies into language education, encouraging educators to adopt innovative strategies for more interactive and effective writing programs. AI platforms succeeded in creating a shift in L2 education by promoting learners\u0026rsquo; intrinsic motivation, offering customized learning opportunities, and empowering students to take an active role in their learning rather than simply absorbing information. Additionally, the research points to the need to further explore the changing dynamics of AI that could enhance the learning experience in different ways. Future research should aim to optimize these platforms for diverse educational settings and assess their long-term effects on writing skills and learner motivation. Ultimately, AI-powered writing tools not only enhance language abilities but also serve as catalysts for nurturing a more engaged, autonomous, and confident generation of EFL learners.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthical Approval\u003c/h2\u003e\u003cp\u003e This research was carried out in consonance with the ethical principles outlined in the Declaration of Helsinki. The Ethics Committee for Research in Social and Human Sciences at Umm Al-Qura University granted approval for the study [reference approval # 2024-16] on October 11, 2024. Following a comprehensive evaluation of the research methods and data collection tools, the committee ensured that the rights and welfare of participants were prioritized. This included confirming voluntary participation, obtaining informed consent, maintaining anonymity and confidentiality, and assessing any potential risks to participants.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003cp\u003eAccording to the university calendar, the second semester started on Sunday 24 October 2024 and ended on Thursday 20 February 2025. In the first week of the semester, the researcher provided the participants with detailed information regarding the objectives of the study, the voluntary aspect of their involvement, measures taken to safeguard their privacy and personal information, and the use of collected data solely for research purposes. Additionally, the researcher informed the participants about the publication of the findings. Written consent reflecting this information was acquired from every participant involved in the research.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMy paper is relevant to the scope of this collection, Large language models in psychological science, as it investigates cognitive and behavioral aspects related to utilizing AI in learning writing in English as a foreign language. It also explores the significance of understanding how AI-powered tools help L2 learners develop their writing skills. The study was conducted in Saudi Arabia, which is an under-researched learning context. Getting this paper published in Humanities and social sciences communications will have a positive effect on the academic atmosphere and encourage other researchers to plan and do more research on different topics related to learning English as a foreign language. Many thanks for considering my paper for publication.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study would be made available upon reasonable request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eAlam A, Mohanty A (2023) Educational technology: Exploring the convergence of technology and pedagogy through mobility, interactivity, AI, and learning tools. Cogent Eng 10(2):2283282. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/23311916.2023.2283282\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eAlGhamdi R (2024) Exploring the impact of ChatGPT-generated feedback on technical writing skills of computing students: A blinded study. Educ Inform Technol 29(14):18901\u0026ndash;18926. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10639-024-12594-2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eAljuaid H (2024) The Impact of Artificial Intelligence Tools on Academic Writing Instruction in Higher Education: A Systematic \u003cem\u003eReview. Arab World English Journal (AWEJ) Special Issue on ChatGPT, April 2024\u003c/em\u003e. 26\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dx.doi.org/10.24093/awej/ChatGPT.2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eAlsadoon R (2021) Chatting with AI Bot: Vocabulary learning assistant for Saudi EFL learners. Engl Lang Teach 14(6):135\u0026ndash;157. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5539/elt.v14n6p135\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBarber JD (2021) Using course journals to encourage reflective practice in second language teacher education. Reflective Pract 22(1):128\u0026ndash;141. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/14623943.2020.1851670\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBitchener J, Knoch U (2010) The contribution of written corrective feedback to language development: A ten month investigation. Appl Linguist 31(2):193\u0026ndash;214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/applin/amp016\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eChen M, Lv MC (2024) College English writing instruction in a ChatGPT context. Contemporary Foreign Language Studies, 2(1), 161\u0026ndash;168. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.qk.sjtu.edu.cn/cfls/EN/10.3969/j.issn.1674-8921.2024.01.013\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eCreswell JW (2020) Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson Education, London\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eDale R, Viethen J (2021) The automated writing assistance landscape in 2021. \u003cem\u003eNatural Language Engineering\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(4), 511\u0026ndash;518. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S1351324921000164\u003c/span\u003e\u003c/span\u003e Ferris, D. R. (2004). The grammar correction debate in L2 writing: Where are we, and where do we go from here? (and what do we do in the meantime\u0026hellip; \u003cem\u003eJournal of Second Language Writing, 13\u003c/em\u003e(1), 49\u0026ndash;62. https://doi.org/10.1016/j.jslw.2004.04.005\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eGodwin-Jones R (2024) Generative AI, Pragmatics, and Authenticity in Second Language Learning. \u003cem\u003eComputation and Language\u003c/em\u003e. 1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://arxiv.org/abs/2410.14395\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHayes JR (2012) Modeling and remodeling writing. Writ Communication 29(3):369\u0026ndash;388. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0741088312451260\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJarrah am, Wardat Y, Fidalgo P (2023) Using ChatGPt in academic writing is (not) a form of plagiarism: What does the literature say. Online J Communication Media Technol 13(4):e202346. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.30935/ojcmt/13572\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJomaa NJ (2025) Corrective Feedback of AI Tools in Writing and Translation. In: Jomaa N (ed) Using AI Tools in Text Analysis, Simplification, Classification, and Synthesis. IGI Global Scientific Publishing, New York, pp 295\u0026ndash;320. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4018/979-8-3693-9511-0\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJeon J (2021) Chatbot- assisted dynamic assessment (CA- DA) for L2 vocabulary learning and diagnosis. Comput Assist Lang Learn 30:1\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09588221.2021.1987272\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKano N (2021) The Efficiency of the Academic Writing System: Can Prewriting Discussion be Eliminated? LET Kanto J 5:39\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.24781/letkj.5.0_39\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKaratsareas P (2022) Semi-Structured Interviews. In: Kircher R, Zipp L (eds) \u003cem\u003eResearch Methods in Language\u003c/em\u003e Attitudes. Cambridge University Press, Cambridge, UK, pp 99\u0026ndash;113. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/9781108867788.010\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKundu A, Bej T (2025) Transforming EFL Teaching with AI: A Systematic Review of Empirical Studies. Int J Artif Intell Educ 1\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40593-025-00470-0\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLee I, Yuan RE (2021) Understanding L2 writing teacher expertise. J Second Lang Writ 52:100755. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jslw.2020.100755\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePessoa L (2008) On the relationship between emotion and cognition. Nat Rev Neurosci 9:148\u0026ndash;158. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nrn2317\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePeters E (2007) Manipulating L2 learners\u0026rsquo; online dictionary use and its effect on L2 word retention. Lang Learn Technol 11(2):36\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://llt.msu.edu/vol11num2/peters/\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRaims A (1983) Techniques in teaching writing. Oxford University Press, New York, NY\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRanalli J (2018) Automated written corrective feedback: How well can students make use of it? Comput Assist Lang Learn 31(7):653\u0026ndash;674. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09588221.2018.1428994\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRichards JC (2022) Exploring emotions in language teaching. RELC J 53(1):225\u0026ndash;239. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0033688220927531\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTsufim F, Pomerleau L (2024) More is less? Using generative AI for idea generation and diversification in early writing processes. In B. Buyserie \u0026amp; T.N. Thurston (Eds.), \u003cem\u003eTeaching and generative AI: Pedagogical possibilities and productive tensions\u003c/em\u003e (pp. 99\u0026ndash;112). Utah State University. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://uen.pressbooks.pub/teachingandgenerativeai/chapter/more-isless-using-generative-ai-for-idea-generation-and-diversification-in-early-writing-processe s/\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eWang C (2024) Exploring Students\u0026rsquo; Generative AI-Assisted Writing Processes: Perceptions and Experiences from Native and Nonnative English Speakers. \u003cem\u003eTechnology, Knowledge and Learning\u003c/em\u003e, 1\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10758-024-09744-3\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eYang Y (2025) AI-supported L2 vocabulary acquisition\u0026ndash;a systematic review from 2015 to 2023. Educ Inform Technol, 1\u0026ndash;35\u0026nbsp;\u003c/span\u003e\u003cspan\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10639-025-13417-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eZhao D (2025) The impact of AI-enhanced natural language processing tools on writing proficiency: An analysis of language precision, content summarization, and creative writing facilitation. Educ Inform Technol 30(6):8055\u0026ndash;8086. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10639-024-13145-5\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"artificial intelligence, L2 writing, learner cognition, behavioral patterns","lastPublishedDoi":"10.21203/rs.3.rs-6804457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6804457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdvancements in technology and artificial intelligence (AI) are increasingly influencing second and foreign language (L2) learning. The integration of AI in L2 education highlights the importance of understanding and investigating its pedagogical and psychological roles and effects. Unlike conventional methods, AI-driven models offer L2 writing students personalized corrective feedback, real-time adjustments, and adaptive scaffolding that empower them to tackle unique challenges at their own pace. In addition, these platforms boost learners' motivation, bridge the gap between technical skill acquisition and emotional engagement. Utilizing qualitative mixed methods (classroom observations, student reflective journals, and semi-structured interviews), the current research assesses the perspectives of 54 Saudi undergraduate students on AI tools in L2 writing classrooms. The findings accentuate the dual impact of AI: technical enhancing writing skills and improving writing outcomes while promoting learners' motivation and fostering a positive attitude towards the writing process. Ultimately, such atmospheres have the potential for nurturing a more engaged, autonomous, and confident generation of EFL learners. The findings also underscore the necessity of integrating such technologies into language education and encouraging innovative teaching strategies. Future research should optimize these platforms for various educational contexts and evaluate their long-term effects on writing skills, feedback literacy, and learner motivation,\u003c/p\u003e","manuscriptTitle":"L2 learners’ behavioral and cognitive engagement in AI-supported English writing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 07:14:16","doi":"10.21203/rs.3.rs-6804457/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1cc01fbb-3b93-4e9d-8635-9117f79aba45","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54147462,"name":"Humanities/Language and linguistics"},{"id":54147463,"name":"Social science/Education"}],"tags":[],"updatedAt":"2025-10-31T09:24:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-04 07:14:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6804457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6804457","identity":"rs-6804457","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}