Using Artificial Intelligence Tools for Providing Feedback as A Strategic Response to Addressing Challenges in Students’ Academic Writing

This study investigates the effectiveness of Artificial Intelligence (AI) and Deep Learning (DL) tools in enhancing academic journal writing skills among students in the Arabic Language Education program at UIN Maulana Malik Ibrahim Malang. Utilizing a mixed-methods approach within a quasi-experimental design, the research involved 90 final-year students divided into experimental and control groups. The intervention group employed AI-based tools such as ChatGPT, Grammarly, and Quilbolt throughout the writing process, while the control group relied on conventional methods. Data were collected through pre-test and post-test assessments, reflective journals, and structured questionnaires. Quantitative results showed a statistically significant improvement in writing performance among students who used AI tools, with large effect sizes (Cohen’s d > 1.0). Qualitative findings revealed that students engaged critically with AI outputs, valued teacher feedback, and developed ethical awareness regarding authorship and originality. The integration of AI tools also increased student confidence, enhanced writing fluency, and promoted autonomous learning. However, limitations in semantic precision and rhetorical fit especially in theology-specific content necessitated human revision. These findings affirm the role of AI as a cognitive scaffold in academic writing and highlight the need for culturally responsive, ethically guided AI integration in language teacher education.Keywords: Artificial Intelligence, Academic Writing, Deep Learning, Arabic Education, Cognitive Scaffold

This study aims to explore English Language Education Study Program (ELESP) students' perceptions of the use of artificial intelligence (AI) tools in supporting their academic writing processes and identify the benefits and limitations they encounter when using these tools in their writing process. Six sixth-semester students from the ELESP were purposively selected based on their prior engagement with AI tools such as ChatGPT, Grammarly, or QuillBot in academic writing tasks. Data were collected through semi-structured, in-depth interviews that allowed participants to express their experiences openly while giving the researcher flexibility to probe further when necessary. Thematic analysis was used to analyze the findings. The findings indicate that the majority of students perceive AI paraphrasing tools as highly useful in the writing process, both in the linguistic and affective dimensions. The majority of EFL students also perceive AI tools as providing substantial benefits in supporting academic writing. Given these insights, it is suggested that educators and institutions integrate AI tools into writing pedagogy while providing explicit guidance on ethical and critical use.

The rapid integration of Artificial Intelligence (AI) tools, such as ChatGPT, DeepSeek, etc., into academic and professional settings has raised important questions about their influence on human cognition. This study examines the relationship between reliance on AI tools and critical thinking skills, with a particular focus on cognitive load. A quantitative survey design was employed, using structured questionnaires to collect data from 350 university students across diverse disciplines. Measures assessed the extent of AI usage, perceived cognitive load, and levels of critical thinking. AI tool use and critical thinking while controlling for demographic and educational factors. Findings indicate that frequent use of AI tools is associated with significantly lower reported cognitive load during complex tasks (β = –0.37, p < .01) but also with slightly lower self-assessed critical thinking skills (β = –0.21, p < .05). Results suggest that while AI support can reduce mental effort, it may inadvertently discourage deeper engagement with information. Implications for education and workplace training include encouraging deliberate reflection and structured critical analysis when integrating AI tools.

This paper discusses the integration of artificial intelligence (AI) tools in education, delineating their potential to transform pedagogical practices alongside the challenges they present. Generative AI models like ChatGPT, had a disruptive impact on teaching and learning, due to their ability to create text, images, and sound, revolutionizing educational content creation and modification. However, nowadays the educational community is polarized, with some embracing AI for its accessibility and efficiency thus advocating it as an indispensable tool, while others cautioning against risks to academic integrity and intellectual development. This document is designed to raise awareness about AI tools and provide some examples of how they can be used to improve education and learning. From an educator’s perspective, AI is an asset for curriculum development, course material preparation, instructional design and student assessment, while reducing bias and workload. For students, AI tools offer personalized learning experiences, timely feedback, and support in various academic activities. The Turkish Biochemical Society (TBS) Academy recommends educators to embrace and utilize AI tools to enhance educational processes, and engage in peer learning for better adaptation while maintaining a critical perspective on their utility and limitations. The transfer of AI knowledge and methods to the teaching experiences should complement and not replace the educator’s creativity and critical thinking. The paper advocates for an informed embrace of AI, AI fluency among educators and students, ethical application of AI in academic settings, and continuous engagement with the evolving AI technologies, ensuring that AI tools are used to augment critical thinking and contribute positively to education and society.

The rapid integration of Artificial Intelligence (AI) tools like ChatGPT, Quillbot, Grammarly, and Cici is actively transforming education in the Philippines, a nation with a tech-savvy, youthful population. This surge provides new avenues for personalized learning and enhanced student engagement, directly impacting how students approach reading and writing. This research specifically sought to determine the influence of AI tools on the academic writing performance of Grade 11 students at Taft National High School during the first semester of the 2024-2025 academic year. The study utilized a descriptive-correlational quantitative design to examine the relationship between AI application tool usage and student academic performance. The data analysis yielded several significant findings: A remarkable 66% of Grade 11 students reported using AI application tools daily for academic writing, indicating a high level of usage. The specific tool Cici was the most commonly used, consulted by 52% of the students. The average academic rating for students exposed to AI tools in their Reading and Writing subjects was 89.08%, placing their performance solidly in the Proficiency Level. Students generally held very favourable perceptions regarding the usage (Grand Mean: 4.532) and benefits (Grand Mean: 4.486) of AI tools, both showing a high level of agreement. Perceptions regarding challenges were also high (Grand Mean: 3.642). A statistical correlation was established between AI usage and academic performance. The frequency of AI tool usage showed a moderate positive correlation (r = 0.543, p < .001) with Reading and Writing performance, meaning increased usage positively influences academic outcomes. Student perceptions of the usage and benefits of AI tools had a significant influence on their performance. Conversely, student perceptions of the challenges associated with AI tools (r = -0.031, p = 0.830) did not have a significant influence on their learning. Keywords: Artificial Intelligence (AI), Academic Writing, Student Academic Performance

Integrating artificial intelligence (AI) technologies into academic writing presents opportunities and challenges, as use of AI promotes efficiency in knowledge production but also exacerbates existing disparities between developed and developing nations, with developing nations lagging behind in terms of access and the expertise for using them productively. Moreover, while AI tools provide support for innovative research, writing assistance, and data analysis, there are growing concerns about the quality of postgraduate student theses and publications, written using AI tools, as they contain false statements and violate research ethics. Based on survey data and secondary literature, this study investigated the current application of AI tools in academic writing by Humanities and Social Science postgraduate students in a Kenyan university. The study aimed to: establish the uptake and use of AI tools in academic writing, assess student attitudes on using AI tools in academic writing; and explore challenges influencing the use of AI tools in academic writing. The study revealed that students often use AI tools that generate content, provide analysis and paraphrase texts, such as chatGPT, Gemini Grammarly and Quillbot. Students had positive attitudes to adopting AI tools for academic writing, however, they reported limitations in proficient use of AI tools, poor writing and research skills, along with lack of ICT resources and AI tools. It is recommended that for effective integration of AI tools in academic writings, higher education institutions should provide ICT resources, AI tools and offer training in research skills, writing skills and use of AI tools for writing.

Background Histological remission is an important target for Ulcerative Colitis (UC) treatment; however, scoring of histological images is time-consuming and prone to inter and intra-observer variability. Thus, a need exists for an accurate, reproducible, and reliable automated method. Previously, we demonstrated an Artificial Intelligence (AI) Tool using image processing and machine learning algorithms to measure histological disease activity using the Nancy index consistently and accurately.1 Here, we aim to enhance the capabilities of the AI Tool, by adding substantially more population-diversified training data while maintaining accuracy and robustness of results. Methods Eight global sites submitted 600 UC histological images. These were added to the 200 images previously used to train and validate the AI Tool. The 800-image dataset was divided into 2 groups: 90% used for training, 10% for testing. The novel AI algorithms were trained using state-of-the-art image processing and machine learning techniques based on deep learning and feature extraction. Cell and tissue regions of each training image were manually annotated, measured, and assigned a Nancy Index independently by 3 histopathologists, and used to further train the AI using over 43,000 characterisations. The AI Tool fully characterises histological images, identifying tissue types, cell types, cell numbers and locations, and automatically measures the Nancy Index for each image. Intra Class Correlation (ICC) and Confusion Matrix analyses were performed to evaluate the AI Tool and assess accuracy. Results The average ICC was 92.1% among the histopathologists and 91.1% between histopathologists and AI Tool, compared with 88.3% and 87.2% in the previous study.1 Confusion matrix analysis (Table 1) demonstrated the strongest correlation at the extremes of the Nancy Index, with 80% correlation between predicted and true labels for Nancy Scores of 0 or 4. When 2 adjacent scores were combined, correlations were stronger: 96% for a true Nancy score of 0 being predicted as 0 or 1, and 100% for a true Nancy score of 2 being predicted as 2 or 3. Conclusion By adding a larger number of images to the AI Tool training data, the robustness of the AI Tool was substantially improved while maintaining accuracy. The continued high correlation of AI Tool performance with the histopathologists reinforces the potential role for the AI Tool for IBD clinical applications. Fully characterising whole slides could standardise and validate an AI-driven scoring system for histology slides in IBD, eliminating the subjectivity of the human pathologist in assessment of disease activity.

The paper presents the results of the research study conducted on students at the Faculty of Humanities and Social Sciences in Zagreb (FHSS), Croatia, at the end of 2024, focusing on their experiences with artificial intelligence (AI) tools, and its use in academic activities, students' trust in AI, and the future use of AI by students. While over 81 % of respondents reported using AI tools for study purposes, more than 89% did not receive any education about AI and expressed a need for such education. Generative AI tools for text creation are the most frequently used type of AI tools, but students still require additional knowledge to use them effectively. AI tools are also utilized for seeking advice, finding information, being available 24/7, and assisting in writing student papers, though not yet on a massive scale. Teachers remain the most trusted source for information and for recommending AI tools. Despite known shortcomings of AI tools such as content errors, potential costs and ethical or privacy concerns, students expressed their intention to continue using AI tools in the future.

The rapid adoption of Artificial Intelligence (AI) tools in higher education has transformed learning practices, prompting concerns about their influence on students’ critical thinking, originality, and independent engagement with academic materials. This study explores the perceived impact of AI on academic literacy among Indonesian university students, with particular attention to critical thinking, originality, and independent learning. Employing a qualitative approach, the study captures students' experiences and perspectives, revealing that while AI tools such as ChatGPT and Grammarly are perceived to enhance learning efficiency, they may also diminish deeper engagement with academic content and critical thinking processes. Many participants reported a tendency to rely on AI-generated summaries, which they associated with reduced independent analysis and creativity. Nevertheless, the findings suggest that when AI tools are integrated with thoughtful pedagogical strategies, they can support the development of academic literacy within ethical boundaries. The study underscores the importance of implementing AI literacy programs and ethical guidelines to foster responsible and reflective use of AI in academic contexts.

Background: Artificial intelligence (AI) tools have demonstrated success in US medical licensing examinations; however, their utility in infection prevention and control (IPC) remains unknown. Methods: The program of hospital epidemiology handles consultation calls and records each question and answer. Using 2022 data, we selected 31 frequently asked questions. We utilized four AI tools, including Chat GPT-3.5 and 4.0, Bing AI, and OpenEvidence, to generate answers. We predefined scales (Table 1) to capture responses by three reviewers, including two hospital epidemiologists and one infection preventionist. The mean score of ≥ 3 and ≥ 4 was considered acceptable in accuracy and completeness, respectively. We reported the percentage of responses with acceptable accuracy and completeness out of assessed questions for each category. Results: Among 31 questions, 16 were associated with isolation duration, 9 with healthcare personnel (HCP) exposure, 4 with cleaning contaminated rooms, and 2 with patient exposure. Regarding accuracy, most AI tools performed worse in questions about isolation duration, ranging between 75% and 93.8%. All AI tools, except OpenEvidence, had a 100% accuracy rate for HCP and patient exposure. All AI tools had a 100% accuracy rate for contaminated room handling. The highest overall acceptable accuracy rate was observed in Chat GPT-3.5. Regarding completeness, most AI tools performed worse in questions about isolation duration, ranging between 44% and 75%. All AI tools, except OpenEvidence, had a 100% completeness rate for contaminated rooms and patient exposure. The highest overall acceptable completeness rate was observed in Bing AI (Table 2). Conclusions: All AI tools provided reasonable answers to commonly asked IPC-related questions, although, there were variations among different tools used. AI could be used to supplement the infection control program, especially if resources are limited.

Purpose: This analysis aims to propose guidelines for artificial intelligence (AI) research ethics in scientific publications, intending to inform publishers and academic institutional policies in order to guide them toward a coherent and consistent approach to AI research ethics.Methods: A literature-based thematic analysis was conducted. The study reviewed the publication policies of the top 10 journal publishers addressing the use of AI in scholarly publications as of October 2024. Thematic analysis using Atlas.ti identified themes and subthemes across the documents, which were consolidated into proposed research ethics guidelines for using generative AI and AI-assisted tools in scholarly publications.Results: The analysis revealed inconsistencies among publishers’ policies on AI use in research and publications. AI-assisted tools for grammar and formatting are generally accepted, but positions vary regarding generative AI tools used in pre-writing and research methods. Key themes identified include author accountability, human oversight, recognized and unrecognized uses of AI tools, and the necessity for transparency in disclosing AI usage. All publishers agree that AI tools cannot be listed as authors. Concerns involve biases, quality and reliability issues, compliance with intellectual property rights, and limitations of AI detection tools.Conclusion: The article highlights the significant knowledge gap and inconsistencies in guidelines for AI use in scientific research. There is an urgent need for unified ethical standards, and guidelines are proposed for distinguishing between the accepted use of AI-assisted tools and the cautious use of generative AI tools.

The integration of artificial intelligence (AI) tools in the workflow of scholarly writing, including scientific and medical writing, offers transformative advantages while raising critical ethical and practical concerns. Among the pros, AI substantially enhances efficiency by automating several time-consuming tasks such as literature review, data synthesis and text editing. In particular, tools such as ChatGPT, Grammarly, and SciSpace Copilot remarkably empower researchers when they draft, refine, and format manuscripts, increasing precision and speed. In addition, AI tools may foster inclusivity by assisting non-native English speakers with seamless translations and also enabling interdisciplinary collaboration, thereby hopefully democratizing access and boosting scientific communication and cooperation. However, the rapid adoption of novel AI tools brings significant challenges. First, there is a distinct risk of perpetuating biases in training datasets, and other key issues include ambiguity in authorship accountability and the potential erosion of critical thinking skills. In addition, AI tools could be purposefully misused to generate mock datasets and fraudulent papers (e.g. by paper mills), and this clearly poses a threat to academic integrity. This challenge is all too pressing given that traditional plagiarism detection tools often fall short against sophisticated AI-generated content. We hereby explore the pros and cons of AI on medical writing, poignantly leveraging Sergio Leone’s The Good, The Bad, and The Ugly movie as a metaphor. By providing general concepts as well as focusing on several key AI tools, we are hopeful this overview may prove useful to anyone wishing to conscientiously adopt AI tools for scientific writing. In addition, we make a compelling case for transparent guidelines, robust and freely available detection mechanisms, and ongoing critical oversight to ensure AI will be able to serve as a catalyst for innovation and dissemination without compromising the credibility of scholarly endeavors.

Introduction: Artificial intelligence (AI) is revolutionizing medical education by enhancing learning experiences, improving knowledge retention, and providing personalized guidance. Through interactive simulations, virtual tutors, and adaptive learning platforms, AI-powered solutions help students in preclinical education grasp difficult ideas. Thus this study aims to examine the impact of AI on preclinical medical education students' academic performance, engagement, and readiness for clinical training among preclinical medical students, examining its applicability, efficacy, potential, and limitations. Which is done by outlining the objectives and evaluating the effectiveness, opportunities, and challenges of integrating artificial intelligence (AI) tools in medical education among Year 1 and Year 2 MBBS students in a private medical university, Malaysia. Methodology: The study involved 300 sample population, including 152 Year 1 and 148 Year 2 students. A cross-sectional questionnaire-based study was conducted, with a sample size of 184 with a 95% confidence level. Data were collected through online surveys and analysis using Microsoft Excel and IBM SPSS version 23.0.Result: All 184 preclinical students used AI tools in their medical education, mainly relying on ChatGPT. About 84.2% are familiar with AI in this context. The effectiveness of AI in improving learning was rated from 1 to 3, with most students scoring AI as 4 or 5 in problem-solving, decision-making, critical thinking, and inspiring new ideas, indicating a high perception of its effectiveness. Many believe AI supports traditional teaching. However, concerns exist about over-reliance on technology (83.2%) and loss of critical thinking skills (77.7%). Also, 42.9% rated their worries about AI's impact on clinical decision-making skills as a 3. Conclusion: Most preclinical students know about AI in medical education and believe it helps improve learning. AI assists students in solving problems, making decisions, encouraging critical thinking, and generating new ideas. However, concerns felt about much dependence on technology and weaken critical thinking skills in medical education. Students believe that AI will not entirely harm clinical decision-making skills. In summary, AI offers both advantages and disadvantages in medical education.

Instructional writing has long been at the forefront of research, with the advent of artificial intelligence (AI) tools such as ChatGPT. Understanding teachers’ perceptions of ChatGPT's use for teaching English writing skills has become increasingly significant. The present study explores Pakistani English teachers’ perceptions of using ChatGPT to teach writing skills to college-level students. Using a qualitative research design, the study involved 15 faculty members from a government college in Pakistan who participated in semi-structured interviews. The study found that teachers perceived ChatGPT as a valuable tool for developing vocabulary, syntactic structure, paragraph writing, and emotional intelligence. The results also showed a potential increase in the students’ involvement while reducing writing anxiety. However, concerns were rising about the overreliance on AI tools, less academic creativity, diminished critical thinking, and a lack of AI-assisted writing classrooms. Further, the findings suggest a balanced approach towards implementing ChatGPT favors creative writing skills, organization, and accuracy. This study recommends practical strategies and provides clear instructions for using AI tools. Moreover, the Technology Acceptance Model (TAM) highlights perceived usefulness, influence, and challenges as key determinants of TAM acceptance. The participants emphasized the need to prompt teachers’ training programs, provide scaffolding, and integrate ChatGPT and other AI tools for effective writing instruction, focusing on structured guidelines to minimize risks and maximize outcomes. This research contributes to contemporary debates on the use of AI tools to support digital transformation in education and provides an actionable plan for integrating AI tools into the English writing classroom.

Will ChatGPT undermine ethical values in nursing education, research, and practice?