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Exploring Students’ Generative AI-Assisted Writing Processes: Perceptions and Experiences from Native and Nonnative English Speakers
Open accessAbstract
Abstract Generative artificial intelligence (AI) can create sophisticated textual and multimodal content readily available to students. Writing intensive courses and disciplines that use writing as a major form of assessment are significantly impacted by advancements in generative AI, as the technology has the potential to revolutionize how students write and how they perceive writing as a fundamental literacy skill. However, educators are still at the beginning stage of understanding students’ integration of generative AI in their actual writing process. This study addresses the urgent need to uncover how students engage with ChatGPT throughout different components of their writing processes and their perceptions of the opportunities and challenges of generative AI. Adopting a phenomenological research design, the study explored the writing practices of six students, including both native and nonnative English speakers, in a first-year writing class at a higher education institution in the US. Thematic analysis of students’ written products, self-reflections, and interviews suggests that students utilized ChatGPT for brainstorming and organizing ideas as well as assisting with both global (e.g., argument, structure, coherence) and local issues of writing (e.g., syntax, diction, grammar), while they also had various ethical and practical concerns about the use of ChatGPT. The study brought to front two dilemmas encountered by students in their generative AI-assisted writing: (1) the challenging balance between incorporating AI to enhance writing and maintaining their authentic voice, and (2) the dilemma of weighing the potential loss of learning experiences against the emergence of new learning opportunities accompanying AI integration. These dilemmas highlight the need to rethink learning in an increasingly AI-mediated educational context, emphasizing the importance of fostering students’ critical AI literacy to promote their authorial voice and learning in AI-human collaboration.
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“Emerging frameworks emphasize process-oriented assessment that documents iterative revision, reflective decision-making, and AI integration strategies rather than solely evaluating final products (Engeness and Gamlem, 2025; Tseng and Lin, 2024; Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Students, particularly those facing language barriers or socioeconomic pressures, conceptualize AI as an equalizing tool that democratizes access to high-quality writing support (Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“LLMs dominate the planning phase for idea generation and outlining, continue supporting the drafting phase for content expansion, while AWE tools are reserved primarily for revision and editing (Wang, 2024; Zhao and Dang, 2026).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“Explicit instruction in prompt engineering and critical AI literacy positions AI as legitimate skill development object rather than taboo (Talandis and Muller, 2025; Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“For example, studies examining AI-assisted writing tasks report that students often produce more fluent and well-structured text, while improvements in argument quality or conceptual reasoning remain limited [10][11][12].”
From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [11]
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“Studies consistently report that students perceive AI-generated text as helpful for brainstorming, drafting, paraphrasing, and improving linguistic accuracy [11].”
From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [11]
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“Appropriate usage is motivated by efficiency enhancement, cognitive load reduction, and access to personalized scaffolding (Kumar et al., 2025; Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“EFL and L2 students view AI as voice-augmenting and barrier-removing, whereas native speakers report concerns about authenticity when AI suggestions diverge from personal style (Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“Students use AI as a “walking tutor” providing instant feedback on linguistic accuracy and structural coherence, particularly during brainstorming and drafting (Talandis and Muller, 2025; Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“This motivation is especially pronounced among non-native speakers who leverage AI to augment authorial voice and overcome communication barriers (Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“Mitigates “full delegation” by rewarding the cognitive journey over the final output (Hanh and Duyen, 2025; Wang, 2024).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024
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“Students may rely on AI for organization without strengthening reasoning [11,36]”
From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [11]
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Citations
Cites
Lincoln, Y. S., Guba, E. G., & Pilotta, J. J. (1985) · International Journal of Intercultural Relations · doi:10.1016/0147-1767(85)90062-8 · Cited by 45,787 · cited 1×
“To ensure the trustworthiness of the qualitative analysis, I also conducted a peer debriefing (Lincoln & Guba, 1985) on the codebook with an experienced qualitative researcher.”
(1998) · Cited by 18,576
Interpretative Phenomenological Analysis: Theory, Method and Research
(2010) · QMiP Bulletin · doi:10.53841/bpsqmip.2010.1.10.44 · Cited by 8,189 · cited 1×
“Phenomenology seeks to form a close and clear account of people’s perceptions and lived experiences as opposed to delivering a positivist conclusion of human encounters, as “pure experience is never accessible” (Smith et al., 2009, p. 33).”
Organizing and the process of sensemaking
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005) · Organization Science · doi:10.1287/orsc.1050.0133 · Cited by 6,943
Students' voices on generative ai: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · arXiv · doi:10.48550/arxiv.2305.00290 · Cited by 2,504 · cited 1×
“Furthermore, the study shows that rather than passively indulging themselves in the convenience of AI tools, a common concern among educators (Chan & Hu, 2023; Graham, 2023), the student writers attempted to seize new learning opportunities that emerged from AI technologies to promote their…”
Smith, J. A. (1996) · Psychology & Health · doi:10.1080/08870449608400256 · Cited by 2,380 · cited 1×
“This qualitative study adopted a phenomenological research design, which focuses on understanding and interpreting a particular aspect of shared human experience (Moran, 2002; Smith, 1996).”
Students’ voices on generative AI: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00411-8 · Cited by 2,301 · cited 1×
“Furthermore, the study shows that rather than passively indulging themselves in the convenience of AI tools, a common concern among educators (Chan & Hu, 2023; Graham, 2023), the student writers attempted to seize new learning opportunities that emerged from AI technologies to promote their…”
Language Learning with Technology
Castillo, D. G. (2021) · Springer eBooks · doi:10.1007/978-981-16-2697-5 · Cited by 2,211
Conceptualizing AI literacy: An exploratory review
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100041 · Cited by 2,205 · cited 1×
“The present study shows that such decision making process can play a pivotal role in cultivating students’ “AI literacy” (Ng et al., 2021) and promoting their responsible use of AI.”
Interpretative phenomenological analysis.
Smith, J. A., & Shinebourne, P. (2012) · American Psychological Association eBooks · doi:10.1037/13620-005 · Cited by 1,755
Encyclopedia of case study research
Mills, A. J., Durepos, G., Wiebe, E., & Aaltio, I. (2010) · Choice Reviews Online · doi:10.5860/choice.48-0043 · Cited by 1,471
Vision, challenges, roles and research issues of Artificial Intelligence in Education
Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100001 · Cited by 1,435 · cited 1×
“Hwang et al. (2020) and Southworth et al. (2023) argued that AI is likely to transform not only the learning environment, but also the learning process, and even what it means to learn.”
Publication Manual of the American Psychological Association (4th ed.).
Gullickson, T. (1996) · Contemporary Psychology · doi:10.1037/004700 · Cited by 1,241
A cognitive process theory of writing
Flower, L., & Hayes, J. R. (1981) · College Composition & Communication · doi:10.58680/ccc198115885 · Cited by 1,025 · cited 1×
“Since the early 1980s until now, scholars have proposed various writing process models (e.g., Abdel Latif, 2021; Flower & Hayes, 1981; Hayes, 2012; Kellogg, 1996), yet they are still trying to form a complete understanding of composing processes.”
(2019) · Open Research Online (The Open University) · Cited by 1,004
Artificial Intelligence in Education: The Three Paradigms
Ouyang, F., & Jiao, P. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100020 · Cited by 991 · cited 1×
“After all, the participants in this study have already developed some proficiency and skills in academic writing, but holding learner agency (Ouyang & Jiao, 2021) can be more complex and challenging for younger learners.”
ChatGPT User Experience: Implications for Education
Zhai, X. (2023) · doi:10.2139/ssrn.4312418 · Cited by 935 · cited 1×
“Thus, pedagogical innovations, policy adjustments, new forms of writing assessments, and teacher education (Zhai, 2022) are needed to adapt to the potential impact of AI on desired student learning outcomes within specific writing curriculums.”
Modeling and remodeling writing
Hayes, J. R. (2012) · Written Communication · doi:10.1177/0741088312451260 · Cited by 893 · cited 1×
“Since the early 1980s until now, scholars have proposed various writing process models (e.g., Abdel Latif, 2021; Flower & Hayes, 1981; Hayes, 2012; Kellogg, 1996), yet they are still trying to form a complete understanding of composing processes.”
Huang, W., Hew, K. F., & Fryer, L. K. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12610 · Cited by 830 · cited 1×
“Research suggests that adopting AI in literacy and language education has advantages such as supporting personalized learning experiences, providing differentiated and immediate feedback (Huang et al., 2022; Bahari, 2021), and reducing students’ cognitive barriers (Gayed et al., 2022).”
Using ChatGPT for second language writing: pitfalls and potentials
Barrot, J. S. (2023) · Assessing Writing · doi:10.1016/j.asw.2023.100745 · Cited by 770 · cited 6×
“This facilitates greater student ownership of their learning, enhancing their learner competence through self-direction, self-assessment, and self-reflection when interacting with AI tools (Barrot, 2023c; Fariani et al., 2023).”
InfluentialCollaborating with ChatGPT in argumentative writing classrooms
Su, Y., Lin, Y., & Lai, C. (2023) · Assessing Writing · doi:10.1016/j.asw.2023.100752 · Cited by 760 · cited 3×
“Barrot (2023a) and Su et al. (2023) both review ChatGPT’s benefits and challenges for writing, pointing out that ChatGPT can offer a wide range of context-specific writing assistance such as idea generation, outlining, content improvement, organization, editing, proofreading, and post-writing…”
Impact of ChatGPT on learners in a L2 writing practicum: an exploratory investigation
Yan, D. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11742-4 · Cited by 713 · cited 4×
“Specifically with regard to classroom-based research in L2 writing, Yan (2023) examined the use of ChatGPT through the design of a one-week L2 writing practicum at a Chinese university.”
InfluentialSouthworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100127 · Cited by 647 · cited 1×
“Hwang et al. (2020) and Southworth et al. (2023) argued that AI is likely to transform not only the learning environment, but also the learning process, and even what it means to learn.”
Moran, D. (2002) · Routledge eBooks · doi:10.4324/9780203196632 · Cited by 615
Making Sense of Sensemaking 2: A Macrocognitive Model
Klein, Moon, & Hoffman (2006) · IEEE Intelligent Systems · doi:10.1109/mis.2006.100 · Cited by 606 · cited 1×
“This perspective focuses on the cognitive strategies employed in connecting and utilizing information to achieve the purpose of explaining the world (Klein et al., 2006).”
A model of working memory in writing.
Kellogg, R. T. (1996) · Cited by 524
Comparing the quality of human and ChatGPT feedback of students’ writing
Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J., Moon, Y., Tseng, W., Warschauer, M., & Olson, C. B. (2024) · Learning and Instruction · doi:10.1016/j.learninstruc.2024.101894 · Cited by 509 · cited 1×
“Steiss et al. (2024) analyzed 400 feedback instances—half generated by human raters and half by ChatGPT—on the same essays.”
Koltovskaia, S. (2020) · Assessing Writing · doi:10.1016/j.asw.2020.100450 · Cited by 447 · cited 3×
“One prominent application is automatic written evaluation (AWE), which comprises two main elements: a scoring engine producing automatic scores and a feedback engine delivering automated written corrective feedback (AWCF) (Koltovskaia, 2020).”
Memarian, B., & Doleck, T. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100152 · Cited by 416 · cited 1×
“Researchers also note challenges such as the varied level of technological readiness among teachers and students as well as concerns regarding accuracy, biases, accountability, transparency, and ethics (e.g., Kohnke et al., 2023; Memarian & Doleck, 2023; Ranalli, 2021).”
Human-centered Artificial Intelligence in education: Seeing the invisible through the visible
Yang, S. J. H., Ogata, H., Matsui, T., & Chen, N.-S. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100008 · Cited by 379 · cited 1×
“The students’ beliefs align with a connectivism paradigm of AI in Education (AIEd) outlined by Ouy-ang and Jiao (2021), in which AI serves as a tool to augment human intelligence and capability (Yang et al., 2021) and learner agency is placed at the core.”
Exploring an AI-based writing Assistant's impact on English language learners
Gayed, J. M., Carlon, M. K. J., Oriola, A. M., & Cross, J. S. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100055 · Cited by 340 · cited 1×
“Research suggests that adopting AI in literacy and language education has advantages such as supporting personalized learning experiences, providing differentiated and immediate feedback (Huang et al., 2022; Bahari, 2021), and reducing students’ cognitive barriers (Gayed et al., 2022).”
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100156 · Cited by 309 · cited 1×
“Researchers also note challenges such as the varied level of technological readiness among teachers and students as well as concerns regarding accuracy, biases, accountability, transparency, and ethics (e.g., Kohnke et al., 2023; Memarian & Doleck, 2023; Ranalli, 2021).”
Link, S., Mehrzad, M., & Rahimi, M. (2022) · Computer Assisted Language Learning · doi:10.1080/09588221.2020.1743323 · Cited by 275 · cited 1×
“Adopting NLP to analyze language features, diagnose errors, and evaluate essays, AWE was first implemented in high-stakes testing and later adopted in writing classrooms (Link et al., 2022).”
Johnson, M. D. (2017) · Journal of Second Language Writing · doi:10.1016/j.jslw.2017.06.001 · Cited by 266 · cited 1×
“For L2 students, writing can be very complex and cognitively daunting (Mohsen, 2021) due to reasons including but not limited to linguistic barriers (Johnson, 2017).”
Using google translate in EFL drafts: a preliminary investigation
Tsai, S.-C. (2019) · Computer Assisted Language Learning · doi:10.1080/09588221.2018.1527361 · Cited by 255 · cited 1×
“Scholars also investigate chatbots as writing partners for scaffolding students’ argumentative writing (Guo et al., 2022; Lin & Chang, 2020) and incorporating Google’s neural machine translation system in second language (L2) writing (Cancino & Panes, 2021; Tsai, 2019).”
Ebadi, S., & Amini, A. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2022.2096638 · Cited by 252 · cited 1×
“Although the students acknowledged the cognitive and affective benefits (e.g., Ebadi & Amini, 2022; Fryer & Carpenter, 2006) of using ChatGPT in writing, they were very cautious about adopting its ideas and suggestions at different discourse levels (i.e., essay, paragraph, and sentence levels) due…”
Barrot, J. S. (2023) · Computer Assisted Language Learning · doi:10.1080/09588221.2021.1936071 · Cited by 248
Bots as language learning tools
Fryer, L. K., & Carpenter, R. (2006) · Language learning & technology · doi:10.64152/10125/44068 · Cited by 243 · cited 1×
“Although the students acknowledged the cognitive and affective benefits (e.g., Ebadi & Amini, 2022; Fryer & Carpenter, 2006) of using ChatGPT in writing, they were very cautious about adopting its ideas and suggestions at different discourse levels (i.e., essay, paragraph, and sentence levels) due…”
The International Encyclopedia of Strategic Communication
Heath, R. L., & Johansen, W. (2018) · Wiley eBooks · doi:10.1002/9781119010722 · Cited by 220
Chatbot-assisted dynamic assessment (CA-DA) for L2 vocabulary learning and diagnosis
Jeon, J. (2023) · Computer Assisted Language Learning · doi:10.1080/09588221.2021.1987272 · Cited by 202 · cited 1×
“Research shows that ITS could enhance students’ vocabulary and grammar development, offer immediate sentence-and paragraph-level suggestions, and provide insights into students’ writing behaviors (Jeon, 2021; Pandarova et al., 2019).”
Using chatbots to scaffold EFL students’ argumentative writing
Guo, K., Wang, J., & Chu, S. K. W. (2022) · Assessing Writing · doi:10.1016/j.asw.2022.100666 · Cited by 201 · cited 2×
“Confirming previous research (e.g., Guo et al., 2022; Holmes et al., 2019; Su et al., 2023), this study found that the students overall had positive experiences with generative AI-assisted writing, for it could accelerate their writing process, reduce their cognitive load and anxiety, and provide…”
L2 writing in the post-process era: Introduction
Atkinson, D. (2003) · Journal of Second Language Writing · doi:10.1016/s1060-3743(02)00123-6 · Cited by 192 · cited 1×
“Thus, writing should be investigated in consideration of its dynamic interplay with institutional, cultural, and technological factors (Atkinson, 2003).”
L2 student engagement with automated feedback on writing: Potential for learning and issues of trust
Ranalli, J. (2021) · Journal of Second Language Writing · doi:10.1016/j.jslw.2021.100816 · Cited by 184 · cited 1×
“Researchers also note challenges such as the varied level of technological readiness among teachers and students as well as concerns regarding accuracy, biases, accountability, transparency, and ethics (e.g., Kohnke et al., 2023; Memarian & Doleck, 2023; Ranalli, 2021).”
Vetter, M. A., Lucia, B., Jiang, J., & Othman, M. (2024) · Computers & composition/Computers and composition · doi:10.1016/j.compcom.2024.102831 · Cited by 177 · cited 1×
“…writing instruction (Tan et al., 2024), L1 student writers’ perceptions of ChatGPT as writing partner and AI ethics in college composition classes (Vetter et al., 2024), and the collaborative experience of writing instructors and students in integrating generative AI into writing (Bedington et…”
A systematic literature review on personalised learning in the higher education context
Fariani, R. I., Junus, K., & Santoso, H. B. (2023) · Technology, Knowledge and Learning · doi:10.1007/s10758-022-09628-4 · Cited by 141 · cited 1×
“This facilitates greater student ownership of their learning, enhancing their learner competence through self-direction, self-assessment, and self-reflection when interacting with AI tools (Barrot, 2023c; Fariani et al., 2023).”
ChatGPT as a Language Learning Tool: An Emerging Technology Report
Barrot, J. S. (2023) · Technology Knowledge and Learning · doi:10.1007/s10758-023-09711-4 · Cited by 130 · cited 6×
“This facilitates greater student ownership of their learning, enhancing their learner competence through self-direction, self-assessment, and self-reflection when interacting with AI tools (Barrot, 2023c; Fariani et al., 2023).”
InfluentialAI-writing tools in education: If you can’t beat them, join them
Tseng, W., & Warschauer, M. (2023) · Journal of China Computer-Assisted Language Learning · doi:10.1515/jccall-2023-0008 · Cited by 119 · cited 3×
“Similar to Tseng and Warschauer (2023), Barrot (2023a) is also concerned about students’ learning loss due to their use of generative AI in writing and their over-reliance on AI.”
A systematic review of automated writing evaluation systems
Shi, H., & Aryadoust, V. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11200-7 · Cited by 111 · cited 1×
“However, scholars have also raised concerns regarding its accuracy and its potential misrepresentation of the social nature of writing (Shi & Aryadoust, 2023).”
The racializing forces of/in AI educational technologies
Dixon‐Román, E. J., Nichols, T. P., & Nyame-Mensah, A. (2019) · Learning Media and Technology · doi:10.1080/17439884.2020.1667825 · Cited by 106
Cancino, M., & Panes, J. (2021) · System · doi:10.1016/j.system.2021.102464 · Cited by 98 · cited 1×
“Scholars also investigate chatbots as writing partners for scaffolding students’ argumentative writing (Guo et al., 2022; Lin & Chang, 2020) and incorporating Google’s neural machine translation system in second language (L2) writing (Cancino & Panes, 2021; Tsai, 2019).”
Bedington, A., Halcomb, E. F., McKee, H. A., Sargent, T., & Smith, A. (2024) · Computers & composition/Computers and composition · doi:10.1016/j.compcom.2024.102833 · Cited by 89 · cited 1×
“…instruction (Tan et al., 2024), L1 student writers’ perceptions of ChatGPT as writing partner and AI ethics in college composition classes (Vetter et al., 2024), and the collaborative experience of writing instructors and students in integrating generative AI into writing (Bedington et al., 2024).”
An error-analysis study from an EFL writing context: Human and Automated Essay Scoring Approaches
Almusharraf, N., & Alotaibi, H. M. (2022) · Technology Knowledge and Learning · doi:10.1007/s10758-022-09592-z · Cited by 86 · cited 1×
“Thus the system can contribute to classroom instruction by reducing the burden on teachers and aiding students in writing, revision, and self-learning (Almusharraf & Alotaibi, 2023).”
Exploring the Potential of ChatGPT as an Educational Technology: An Emerging Technology Report
Glaser, N. J. (2023) · Technology Knowledge and Learning · doi:10.1007/s10758-023-09684-4 · Cited by 82 · cited 1×
“While some are optimistic about the opportunities that generative AI brings to classrooms, various concerns arise especially in terms of academic dishonesty and the biases inherent in these AI tools (Glaser, 2023).”
RECIPE: How to Integrate ChatGPT into EFL Writing Education
Han, J., Yoo, H., Kim, Y., Myung, J., Kim, M., Lim, H., Kim, J., Lee, T. Y., Hong, H., Ahn, S.-Y., et al. (2023) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3573051.3596200 · Cited by 67 · cited 1×
“In another study by Han et al. (2023), the authors designed a platform that integrated ChatGPT to support L2 writers in improving writing quality in South Korea.”
Computer‐mediated feedback for L2 learners: Challenges versus affordances
Bahari, A. (2020) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12481 · Cited by 64
Beyond ChatGPT: Multimodal generative AI for L2 writers
Kang, J., & Yi, Y. (2023) · Journal of Second Language Writing · doi:10.1016/j.jslw.2023.101070 · Cited by 62 · cited 1×
“…assistance; the multimodal functionalities of generative AI can also allow writers to explore creative expressions and multimodal writing, enriching literacy practices by integrating more visual, auditory, and interactive elements into the composition process (Kang & Yi, 2023; Li et al., 2024).”
Pandarova, I., Schmidt, T. D., Hartig, J., Boubekki, A., Jones, R. D., & Brefeld, U. (2019) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-019-00180-4 · Cited by 60 · cited 1×
“Research shows that ITS could enhance students’ vocabulary and grammar development, offer immediate sentence-and paragraph-level suggestions, and provide insights into students’ writing behaviors (Jeon, 2021; Pandarova et al., 2019).”
Digital Writing Technologies in Higher Education
Kruse, O., Rapp, C., Anson, C. M., Benetos, K., Cotos, E., Devitt, A., & Shibani, A. (2023) · Springer eBooks · doi:10.1007/978-3-031-36033-6 · Cited by 59
Enhancing Post-secondary Writers’ Writing Skills with a Chatbot: A Mixed-Method Classroom Study
Lin, M. P.-C., & Chang, D. (2020) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 54
AI in CALL—Artificially Inflated or Almost Imminent?
Schulze, M. (2008) · CALICO Journal · doi:10.1558/cj.v25i3.510-527 · Cited by 44 · cited 1×
“Researchers have long been studying the utilization of AI technologies to support writing and language learning (Schulze, 2008).”
Ferrara, A. (2002) · Routledge eBooks · doi:10.4324/9780203005422 · Cited by 44
Co-authoring with an AI? Ethical Dilemmas and Artificial IntelligencePreprint
Jabotinsky, H. Y., & Sarel, R. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4303959 · Cited by 40 · cited 1×
“…further pursue what it means by authenticity and academic integrity in an increasingly AI-mediated educational context, ways to promote students’ authorial voice and agency, as well as the complicated authorship issues (Jabotinsky & Sarel, 2022) involved in AI-human collaboratively generated texts.”
Writing in Test and Non-test Situations: Process and Product
Khuder, B., & Harwood, N. (2015) · Journal of Writing Research · doi:10.17239/jowr-2015.06.03.2 · Cited by 39 · cited 1×
“For instance, skilled writers refine and revise their ideas during writing, whereas novice writers mostly engage in sentence level changes such as fixing grammatical and lexical issues (e.g., Khuder & Harwood, 2015).”
Remodeling writers’ composing processes: Implications for writing assessment
Abdel Latif, M. M. M. (2021) · Assessing Writing · doi:10.1016/j.asw.2021.100547 · Cited by 31 · cited 3×
“Since the early 1980s until now, scholars have proposed various writing process models (e.g., Abdel Latif, 2021; Flower & Hayes, 1981; Hayes, 2012; Kellogg, 1996), yet they are still trying to form a complete understanding of composing processes.”
Li, B., Wang, C., Bonk, C. J., & Kou, X. (2024) · TechTrends · doi:10.1007/s11528-024-00960-3 · Cited by 29 · cited 1×
“…assistance; the multimodal functionalities of generative AI can also allow writers to explore creative expressions and multimodal writing, enriching literacy practices by integrating more visual, auditory, and interactive elements into the composition process (Kang & Yi, 2023; Li et al., 2024).”
Pedagogies of Digital Composing through a Translingual Approach
Martín, C. S., Hirsu, L., Gonzales, L., & Alvarez, S. P. (2019) · Computers & composition/Computers and composition · doi:10.1016/j.compcom.2019.02.007 · Cited by 28
L1 versus L2 writing processes: What insight can we obtain from a keystroke logging program?
Mohsen, M. A. (2021) · Language Teaching Research · doi:10.1177/13621688211041292 · Cited by 28 · cited 1×
“For L2 students, writing can be very complex and cognitively daunting (Mohsen, 2021) due to reasons including but not limited to linguistic barriers (Johnson, 2017).”
Poquet, O. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13435 · Cited by 25 · cited 6×
“Poquet (2024) integrates these two theoretical orientations, proposing that sensemaking encompasses both the individual and the collective, drawing attention to how learners explain the cognitive aspects of their learning as well as the social and cultural factors shape their learning experiences.”
InfluentialExploring Academic Voice in Multimodal Quantitative Texts
Prince, R. N., & Archer, A. H. (1970) · Literacy and Numeracy Studies · doi:10.5130/lns.v22i1.4178 · Cited by 18
Authenticity, Self-fulfillment, and Self-acknowledgment
Rings, M. (2017) · The Journal of Value Inquiry · doi:10.1007/s10790-017-9589-6 · Cited by 17 · cited 1×
“As Rings (2017) acknowledged, authenticity extends beyond adherent to personally endorsed commitments; it requires a comprehensive consideration of one’s self-awareness and the changing social context.”
Research works printed but not linked: 7
- Cao, L., & Dede, C. (2023). Navigating a world of generative AI: Suggestions for educators. The next level lab at harvard graduate school of education. President and Fellows of Harvard College: Cambridge, MA.
- Eaton, S. (2023). Six tenets of postplagiarism: Writing in the age of artificial intelligence. University of Calgary. http://hdl.handle.net/1880/115882.
- Graham, S. S. (2023). Post-process but not post-writing: large language models and a future for composition pedagogy. Composition Studies, 51(1), 162–218.
- Johnson, G. P. (2023). Don’t act like you forgot: Approaching another literacy “crisis” by (re)considering what we know about teaching writing with and through technologies. Composition Studies, 51(1), 169–175.
- Saldaña, J. (2016). The coding manual for qualitative researchers (3rd ed.). Sage.
- Tan, X., Xu, W., & Wang, C. (2024). Purposeful remixing with generative AI: Constructing designer voice in multimodal composing. arXiv preprint arXiv:2403.19095. · DOI
- Wang, C., Samuelson, B., & Silvester, K. (2020). Zhai nan, mai meng and filial piety: The translingual creativity of Chinese university students in an academic writing course. Journal of Global Literacies, Technologies, and Emerging Pedagogies, 6(2), 1120–1143.
Cited by
Sorted by citations
Investigating L2 writers' critical AI literacy in AI-assisted writing: An APSE model
Wang, C., & Wang, Z. (2025) · Journal of Second Language Writing · doi:10.1016/j.jslw.2025.101187 · Cited by 140
Generative AI (GenAI) in the language classroom: A systematic review
Lee, S., Choe, H., Zou, D., & Jeon, J. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2025.2498537 · Cited by 158
“As a resource provider, GenAI assisted language learners in enriching writing topics (Mahapatra, 2024), seeking additional information (Punar Özçelik & Ekşi, 2024), learning technical terms (Abdelhalim, 2024), and improving grammar or vocabulary (C. Wang 2024).”
InfluentialLiteracy in the Time of Artificial Intelligence
Kalantzis, M., & Cope, B. (2024) · Reading Research Quarterly · doi:10.1002/rrq.591 · Cited by 197
“But they also noted differences between human and machine feedback and that the two were different in useful ways (Tzirides, Zapata, et al., 2023, 2024; Zapata et al., 2024).”
Kohnke, L. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100279 · Cited by 132
A systematic literature review of generative artificial intelligence (GenAI) literacy in schools
Park, J. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100487 · Cited by 114
Metadata
- Authors
- Wang, C.
- Affiliations
- Colby College (US)
- Corresponding author
- Wang, Chaoran
- ORCID
- Wang, Chaoran
- Venue
- Technology Knowledge and Learning
- Published
- 2024-05-30
- Volume
- 30
- Issue
- 3
- Pages
- 1825-1846
- ISSN
- 2211-1662 (ISSN-L)
- 2211-1670
- OpenAlex
- W4399182459
- Cited by
- 212
- References
- 72
- Citations by year
- 2026: 119 · 2025: 81 · 2024: 12
- FWCI
- 79.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Technology Knowledge and Learning (publishedVersion, cc-by)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI in writing, ChatGPT, writing process, student perceptions, first-year composition, authorial voice, critical AI literacy, human-AI collaboration, ethics of writing
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