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Background: Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large language models, particularly ChatGPT, in improving the English academic writing skills of these students. Methods: A cohort of 25 third-year medical students from China was recruited. The study consisted of two stages. Firstly, the students were asked to write a mini paper. Secondly, the students were asked to revise the mini paper using ChatGPT within two weeks. The evaluation of the mini papers focused on three key dimensions, including structure, logic, and language. The evaluation method incorporated both manual scoring and AI scoring utilizing the ChatGPT-3.5 and ChatGPT-4 models. Additionally, we employed a questionnaire to gather feedback on students' experience in using ChatGPT. Results: After implementing ChatGPT for writing assistance, there was a notable increase in manual scoring by 4.23 points. Similarly, AI scoring based on the ChatGPT-3.5 model showed an increase of 4.82 points, while the ChatGPT-4 model showed an increase of 3.84 points. These results highlight the potential of large language models in supporting academic writing. Statistical analysis revealed no significant difference between manual scoring and ChatGPT-4 scoring, indicating the potential of ChatGPT-4 to assist teachers in the grading process. Feedback from the questionnaire indicated a generally positive response from students, with 92% acknowledging an improvement in the quality of their writing, 84% noting advancements in their language skills, and 76% recognizing the contribution of ChatGPT in supporting academic research. Conclusion: The study highlighted the efficacy of large language models like ChatGPT in augmenting the English academic writing proficiency of non-native speakers in medical education. Furthermore, it illustrated the potential of these models to make a contribution to the educational evaluation process, particularly in environments where English is not the primary language. [ABSTRACT FROM AUTHOR]

This paper investigates the complex interplay between generative artificial intelligence (AI) and human intellect in academic writing and publishing. It examines the 'organic versus synthetic' paradox, emphasizing the implications of using generative AI tools in educational and academic integrity contexts. The paper critiques the prevalent 'publish or perish' culture in academia, highlighting the need for systemic reevaluation due to generative AI's emerging role in academic writing and reporting. It delves into the legal and ethical challenges of authorship and ownership, especially in relation to copyright laws and AI-generated content. The paper discusses generative AI's diverse roles and advocates for transparent reporting to uphold academic integrity. Additionally, it calls for a broader examination of generative AI tools and stresses the need for new mechanisms to identify generative AI use and ensure adherence to academic integrity and ethics. The implications of generative AI are also explored, suggesting the need for innovative AI-inclusive strategies in academia. The paper concludes by emphasizing the significance of generative AI in various information-processing domains, highlighting the urgency to adapt and transform academic practices in an era of rapid generative AI-driven change. [ABSTRACT FROM AUTHOR]

This paper offers a multi-dimensional comparative analysis of the linguistic characteristics found in the introduction sections of dissertations produced by ChatGPT and those written by Saudi authors. This research paper aims to analyze the linguistic variation in the introduction part of the dissertations written by Saudi writers compared with the introduction produced by ChatGPT. An extensive analysis of more than 150 linguistic features, including lexico-grammatical structures and semantic nuances, is performed using Multidimensional Analysis Tagger (MAT) tagger. A corpus of dissertation introductions written by Saudi students is compiled and analyzed. Furthermore, a corpus is created that comprises introductions produced by ChatGPT. The study investigates the relationship between language produced by AI and human-written content, revealing unique linguistic preferences. The results indicate ChatGPT is more informational, explicit and less non-narrative and non-argumentative than human-written introductions. There is a significant difference in discourse production on dimension five, as human-written introductions produce abstract and ChatGPT produces non-abstract discourse. The study is significant as it highlights the linguistic differences between the writing styles of ChatGPT and Saudi writers, indicating potential areas of improvement for AI-generated texts. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has increasingly influenced higher education, notably in academic writing where AI-powered assisting tools offer both opportunities and challenges. Recently, the rapid growth of generative AI (GAI) has brought its impacts into sharper focus, yet the dynamics of its utilisation in academic writing remain largely unexplored. This paper focuses on examining the nature of human-AI interactions in academic writing, specifically investigating the strategies doctoral students employ when collaborating with a GAI-powered assisting tool. This study involves 626 recorded activities on how ten doctoral students interact with GAI-powered assisting tool during academic writing. AI-driven learning analytics approach was adopted for three layered analyses: (1) data pre-processing and analysis with quantitative content analysis, (2) sequence analysis with Hidden Markov Model (HMM) and hierarchical sequence clustering, and (3) pattern analysis with process mining. Findings indicate that doctoral students engaging in iterative, highly interactive processes with the GAI-powered assisting tool generally achieve better performance in the writing task. In contrast, those who use GAI merely as a supplementary information source, maintaining a linear writing approach, tend to get lower writing performance. This study points to the need for further investigations into human-AI collaboration in learning in higher education, with implications for tailored educational strategies and solutions. [ABSTRACT FROM AUTHOR]

The new wave of buzzword technology has launched the Chat Generative Pre-Trained Transformer (ChatGPT). The ChatGPT application, besides its benefits, has created a worldwide heated debate about its impact on quality and the future of education. Artificial intelligence and other computing technology advancements have dominated the academic scene The main aim of this paper is to map out the impact of the use of ChatGPT on academic writing at Moroccan universities. The researchers have designed a questionnaire for the purpose of this study. The research targets university students and educators for their possible expertise in academic writing. The distribution intends to ensure representation across levels of education, age, and gender. One hundred and eighty volunteers participated by providing insightful data about the investigation. The results of the study revealed that participants confirm the value and efficacy of ChatGPT as a tool; Moroccan respondents admit that ChatGPT can be both beneficial and harmful to students. Students at different educational levels venture into the use of ChatGPT without guidance and training. They are at a crossroads without direction signs in implementing ChatGPT appropriately, so they are astray about whether to use ChatGPT academically, how, and where. The educators, though they are provided with accounts in iThenticate plagiarism detector, stay aloof and claim training in their turn, but the educational authorities, ministry, and universities continue to keep taciturn. [ABSTRACT FROM AUTHOR]

This study was aimed at understanding graduate students' preferences in applying AI when dealing with their class papers and projects in Indonesia. It also sought to understand how students who have used AI in previous writing feel about such experience. This study adopted a phenomenological research method in order to elicit in-depth insights into the concerns of the students. The participants included graduate students from four universities in Indonesia. These data were gathered using semi-structured interviews of 30 students who had experience using AI for their academic writing. Guided by understanding the decision-making process, perceived benefits, and drawbacks of AI, and overall experiences, interview questions were prepared. One-way thematic analysis was conducted with the interview data. Students seemed to view AI applications as only helping with formatting and editing tasks, as most of them would like to have the opportunity to do the major work by themselves for better learning. Another underlying strong theme emerging here is related to AI overdependency and unequal access to it. The results offer insights into the respective areas that can be used by educators and institutions to provide a balance between the rising AI in use and support for independent learning within academics.

As artificial intelligence (AI) increasingly permeates educational landscapes, its impact on academic writing has become a subject of intense scrutiny. This research delved into the nuanced dimensions of authorship and voice in academic writing, specifically focusing on the application of OpenAI's ChatGPT. In this study, the research team compared and contrasted an essay written by one second-year English student for a course on English literature with a similar essay produced by ChatGPT. The current research also, tried to clarify whether artificial intelligence can satisfy the formal requirements of academic writing and maintain the distinctive voice inherent in human-authored content. The examination hinges on parameters such as assertiveness, self-identification, and authorial presence. Additionally, the researchers shed light on the challenges inherent in producing AI-generated academic text. While ChatGPT presented an ability to generate contextually relevant content, the results highlighted its need for support in guaranteeing factual accuracy and capturing the complex aspects of authorship that are common in human writing. Notably, when compared to human-generated text, the AI-generated text was deficient in terms of specificity, depth, and accurate source referencing. While AI has potential as an additional tool for academic writing, this study's findings indicated that its current capabilities--particularly in producing academic text are limited, and remain constrained. This study emphasizes upon the imperative for continued refinement and augmentation of AI models to bridge the existing gaps in achieving a more seamless integration into the academic writing landscape. [ABSTRACT FROM AUTHOR]

Copyright of Praxis Pedagogica is the property of Corporacion Universitaria Minuto de Dios and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Generative AI applications are believed to have disruptive potential, not only for academic writing. However, little is known about which AI tools are used to what extent for writing. This is especially true for student teachers who are expected both to learn writing and teach it in the future. Therefore, 505 student teachers were surveyed about their usage of and beliefs regarding writing with AI. The results show that ChatGPT is the most frequently used application, although knowledge of AI does not automatically translate into regular use. Nevertheless, most participants believe that AI applications play a crucial role for writing in school. Considering the extent of AI usage and beliefs about AI in a regression model, AI literacy, the subject studied, self-assessed digital skills, and writing-related self-concept can explain a medium amount of the variance. Based on these findings, the article draws conclusions for further research and teacher training. [ABSTRACT FROM AUTHOR]

Copyright of Firat University Journal of Social Sciences / Firat Üniversitesi Sosyal Bilimler Dergisi is the property of Firat University, Social Sciences Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)