Improving Academic Writing Skills through Artificial Intelligence-Based Training

Teaching academic writing skills requires careful attention to the individual and assessing, and providing conducive feedback to all the students within the specific allocated time. However, there remains a gap in research regarding how different types of Teachers' feedback influence students' academic writing development in the particular context of Sanghar. Therefore, the study intends to explore the most effective feedback provided by teachers to foster the academic writing skills of the university Sanghar at Shaheed Benazir Bhutto University, Sanghar Campus. To achieve this, the qualitative research method was employed in which semi-structured interviews were conducted with five teachers of the English language to know their perceptions and experiences. The results revealed that personalized and constructive feedback, which includes detailed suggestions and corrections, significantly enhances students' ability to write academically. Moreover, the research highlights the importance of timely feedback in improving writing skills among students. Additionally, encouraging a feedback culture in the classroom could further support the development of academic writing proficiency at the university level in Sanghar.

In higher education, where written assignments often serve as the cornerstone of the learning experience and assessment, academic writing skills emerge as a critical aspect of student success.This study explores the progress of freshman students at an Englishmedium university in Armenia, examining how their academic writing develops during their first year of study.This research employs a corpus-based analysis of 590 pre-and post-year essays to track trends in the use of academic vocabulary, discourse markers, and reporting verbs.The findings reveal a statistically significant increase in the use of academic vocabulary, indicating students' growing familiarity with academic lexis.No significant changes were observed in the use of discourse markers.However, reporting verbs in the argue and show categories have increased in frequency, while think verbs have declined, suggesting a shift from subjective toward more objective and evidencebased writing.These trends provide insights into the developmental potential of academic writing among first-year students in English-medium universities in non-English speaking countries and highlight areas that could be further examined to understand the specific challenges students face in academic writing.

This study explores the impact of the Artificial Intelligence (AI) tools on academic writing among the university students and lecturers at the educational establishments in Malaysia and China. Employing the mixed-methods approach, the research involved the quasi-experiment and the interviews to assess the tools’ effectiveness in improving the writing quality, their limitations, and the ethical challenges they present. Quantitative results revealed the significant improvements in grammar, coherence, and overall writing performance, particularly among the students with lower baseline proficiency. Qualitative findings highlighted the disparities in AI understanding between the students and the lecturers, their concerns about overreliance, and the absence of institutional guidelines for the responsible AI use. The study integrates the Hyperpersonal Communication Theory to analyze how AI mediates and enhances the academic writing while exposing its limitations in fostering critical thinking and originality. Its findings emphasize the need for the balanced, ethical AI integration into education, offering practical recommendations for Xiamen University Malaysia and similar institutions to develop the comprehensive policies. Despite the limitations, including not big enough sample size, and the focus on the third-year undergraduate students, this research provides the valuable insights into the opportunities and challenges of AI in academic the contexts, paving the way for future studies on its long-term implications and interdisciplinary applications.

This study aims to develop a model to examine the influence of excessive mobile application (app) texting on technostress and academic writing skills in the Arabic language among undergraduates in higher education. In this study, the person-technology (P-T) fit model was used as a means of exploring the effect of excessive mobile app texting on students' levels of technostress and the influence of these factors on their academic writing skills. The sample was comprised of 235 undergraduate students who were selected by random sampling. The study proposed a model comprised of several factors that assist in answering the study questions. These factors are the following: `excessive mobile apps texting', `techno-overload', `techno-invasion', `techno-complexity', `accuracy', `clarity', `cohesiveness', and `vocabulary'. A developed questionnaire was employed as the main data collection method to obtain relevant information regarding excessive mobile app texting, mobile technostress, and students' academic writing skills. A quantitative research method via structural equation modeling (SEM) was used to analyze the data. The results showed that excessive mobile app texting and mobile technostress, including techno-overload, techno-invasion, and techno-complexity, have negative influences (through both direct and indirect effects) on students' academic writing skills, including accuracy, clarity, cohesiveness, and vocabulary. Several pedagogical and technical implications are suggested at the end of this study.

The higher education landscape in South Africa is characterised by alarming levels of student attrition and the prolongation of academic programmes. The lack of proficient academic writing skills hinders their achievement and impacts their success rates. This study examined the transformative effects of postgraduate writing camps on students’ academic writing skills and self-efficacy. This article drew its data from the larger project, ‘Postgraduate Research Support for Enhanced Throughput’, conducted by the Centre for Teaching and Learning at the North-West University (NWU), South Africa. Based on Halpern’s four-part model of critical thinking, the research investigated the acquisition of skills, development of disposition, transfer of skills, and metacognitive processes in a sample of 50 postgraduate students. The findings revealed that writing camps effectively enhance language skills, encourage individual voices in academic discourse, and improve professional competence. A well-structured writing environment and effective feedback mechanisms play a crucial role in increasing productivity and satisfaction. Additionally, the study highlighted the acquisition of functional and self-management skills, including effective time management and collaborative interaction. The recommendation to target newly admitted postgraduate students emphasised the potential to address writing difficulties from the outset. The implications for supervisors and institutions include utilising the insights for mentoring practices, investing in conducive and structured settings, and integrating effective feedback mechanisms. Keywords: Academic Writing Camp, Writing Skills Development, Self-Efficacy, Halpern’s Four-Part Model, Postgraduate Research.

The rapid advancements in Artificial Intelligence (AI) have transformed language education, especially in higher education.Many studies have been done related to AI integration in education, but none on the use of language AI tools among Diploma TESL students at Poly-Tech institutions in Malaysia.This study investigates the use of AI writing tools such as Grammarly, QuillBot and ChatGPT in enhancing the academic writing skills of Diploma in Teaching English as a Second Language (DTESL) students at Kolej Poly-Tech Mara (KPTM) Kota Bharu, Malaysia.The study is grounded in Sociocultural Theory (SCT) and the Technology Acceptance Model (TAM) to investigate the relationship between AI writing tool use which is the independent variable and academic writing skills as the dependent variable including grammar accuracy, vocabulary usage, coherence and organization and self-editing skills.Students' perceptions of AI writing tools that are operationalized through perceived usefulness and perceived ease of use will serve as the moderating variable.A mixed-method explanatory sequential design under the pragmatic paradigm will be employed with Phase 1 comprising a quantitative survey that will be administered to 150 students followed by Phase 2 involving qualitative semi-structured interviews with 15 purposively selected students to explore their experiences, challenges and suggestions for improving the integration of AI writing tools.Quantitative data will be analysed using SPSS Statistics Version 29 through descriptive statistics, Pearson correlation and multiple regression analysis.Qualitative data will be analysed thematically through a manual process.This study will provide empirical insights into how AI writing tools support ESL academic writing performance and offer practical recommendations elicited from students' suggestions for incorporating these tools into writing instruction.By focusing on the Malaysian higher education ESL context, this study addresses critical gaps in the literature on AI-assisted academic writing.

هدفت الدراسة إلى فاعلية برنامج قائم على نظرية ما بعد البنائية باستخدام تطبيقاتWizIQلتطوير مهارتي القراءة الناقدة والكتابة الأكاديمية لدى طلاب جامعة القدسالمفتوحة. تبدأ الدراسة بمراجعة الأدبيات والدراسات المرتبطة بنظرية ما بعد البنائية,تطبيقات WizIQبالإضافة إلى مهارتي القراءة الناقدة والكتابة الأكاديمية المناسبةلطلاب المرحلة الجامعية. لقد قامت الباحثة بتصميم اختبار تواصل شفهي, مقياسمتدرج لتقييم مهارات التواصل الشفهي والبرنامج المقترح . ثم قامت الباحثة باختيارمجموعة عشوائية من طلاب اللغة الانجليزية بجامعة القدس المفتوحة للمشاركة فيالدراسة والانخراط في أنشطتها . ثم تقديم المشاركين للاختبار القبلي والبعدي. ثم تمتحليل النتائج من الناحيتين الكمية والكيفية . لقد أظهرت النتائج آن برنامج WizIQكانفعالا للغاية لتطوير القراءة الناقدة والكتابة الأكاديمية لدى طلاب جامعة القدس المفتوحة.

The integration of Artificial Intelligence (AI) in academic writing has revolutionized the way scholars approach writing, editing, and ensuring academic integrity. This chapter explores the multifaceted role of AI in enhancing the academic writing process, focusing on AI-powered writing assistants, plagiarism detection, and grammar enhancement systems. With the advent of machine learning algorithms, AI has evolved from basic grammar checkers to sophisticated tools that provide real-time, context-aware suggestions, ensuring the clarity, coherence, and logical consistency of academic texts. Furthermore, AI tools for plagiarism detection have become critical in maintaining academic integrity by identifying not only direct plagiarism but also subtle forms such as paraphrasing and translation-based content theft. The chapter delves into how AI-driven plagiarism detection systems are increasingly becoming multilingual, offering effective support for non-native English speakers and researchers across different linguistic backgrounds. Additionally, the role of AI in customizing writing assistance for specific academic genres, ensuring adherence to discipline-specific conventions, and maintaining logical consistency from thesis to conclusion is examined. The future of AI in academic writing lies in its ability to provide personalized, adaptive feedback that enhances writing quality while promoting ethical standards across global academic platforms. The potential of AI tools to transform academic writing is immense, with far-reaching implications for scholarly productivity, writing efficiency, and the preservation of academic integrity.

The current study investigated the pedagogical implication of Clause Expansion (CE) mastery to improve academic English writing skills. Fifteen students participated in the study. A two-cycle action research design was used to justify how the mastery of clause expansion contributed to the development of academic writing skills. Prior to intervention, they were assigned to write academic texts based on IELTS writing test. Then, they were given a three-week task-based e-learning instruction on CE., based on Systemic Functional Linguistic Framework of Clause Expansion.In the process of Explicit Instruction (EI) of CE, they were exposed in academic writing exercises to apply their knowledge on CE in various grammatical contexts in which it is required as Input Flood (IF). Another test was administered to see how it progressed from the pre-test. Then, another three-week task-based e-learning module, was given for their second online learning activities. A post-test was administered to see how it contributed to their overall writing skills. It turned out that CE mastery under e-learning special instruction did significantly improve their writing skills. They become more confident in writing academic texts. It is highly recommended that CE be taught as an integral part of a writing course.

The transition from high school to university for first-year students is challenging in academia, globally, and locally. Students must continually provide quality content at university and possess organisational and coherent language skills in writing essays and assignments. They should meet expectations such as demonstrating their academic writing skills, showing meaningful writing, which includes reasoning, and drawing readers’ attention to the pertinent facts. For a few decades, academic support programmes, including writing centres, have been introduced in South African universities to assist first-year students in academic writing. Despite establishing these programmes, poor academic writing persists in many South African universities among first-year students. Therefore, this study explored how the Academic Writing Centre, as a collaborative scaffolded approach, could improve the academic writing skills of first-year English Second Language (ESL) students at a South African university. The study adopted a quantitative method through a descriptive research design. A questionnaire was used as an instrument for data collection. Fifty first-year students who were registered for the Senior and Further Education and Training phases at the faculty of education of a South African university were chosen (N=50; males=14, females=36). Descriptive results revealed that the Academic Writing Centre could be considered a collaborative scaffolded model to improve the academic writing skills of first-year ESL students. The study recommends exploring writing support centres and lecturers further as essential tools that can assist students in socialising the link between entry and the discourse of university subjects’ academic requirements.

This study aimed to assess the academic writing skills of graduate students in educational departments at a leading state university in Saudi Arabia and investigate the correlation between these skills and their attitudes towards the classical Arabic language. Employing a descriptive analytical approach, the research utilized an academic writing test and the Attitude towards Classical Arabic Scale. A random sample of 105 male and female students, representing 45% of the study population, participated. Drawing from a compendium of essential Academic Arabic writing skills, encompassing 74 sub-skills distributed across 8 core competencies, the results of the writing test unveiled that the participants had achieved a satisfactory level of mastery in these skills. Key findings reveal that graduate students excel in style and linguistic accuracy while showing a need for improvement in formatting skills. The study also highlights positive attitudes towards Classical Arabic, with a strong preference for writing, followed by listening, reading, and speaking. Notably, a significant positive correlation was observed at a 0.05 significance level between students' possession of academic writing skills and their attitudes towards Classical Arabic. Furthermore, gender-based analysis indicated higher academic writing skill scores among female students in educational departments. Based on these insightful findings, pedagogical recommendations and suggestions for future research were also deliberated.

The integration of ChatGPT and artificial intelligence (AI) has led to innovative ideas in academic writing. This shift has improved the efficiency and quality of academic content, yet it also raises ethical concerns regarding authorship, originality, and maintaining academic rigor. This study aims to explore the interplay between AI and academic writing practices, contributing to the role of technology in language studies and its impact on scholarly endeavors. The study uses a qualitative research approach, employing document analysis and queries directed at ChatGPT to assess its effectives in generating academic content. The research queries serve to evaluate ChatGPT's performance in tasks such as generating introductions, literature reviews, findings, discussions, conclusions, and abstracts related to the use of AI in academic writing. The experimentation with ChatGPT highlights the capabilities and limitations of AI in academic writing. It emphasizes the importance of human oversight and critical thinking in the research process. Despite ChatGPT's rapid response rate, the study reveals limitations such as deficiencies in academic rigor and referencing accuracy, which necessitate human oversight. This study underlines the importance of combining human intellect together with AI and focuses on the ethical considerations crucial for preserving the integrity of academic research and writing.

The integration of artificial intelligence (AI) in education has the potential to revolutionize teaching and learning, particularly in the development of students’ critical thinking skills. This study explores science instructors' familiarity, perceptions, and experiences with using AI to enhance students' critical thinking skills, as well as the level of institutional support for AI integration in teaching. A quantitative survey was conducted among 20 science instructors from higher education institutions in Isabela, Philippines. The findings reveal that while instructors acknowledge AI's potential to improve educational outcomes, there is a significant gap in formal AI training and literacy among educators. Positive correlations were found between AI literacy, AI integration, and critical thinking development, suggesting that as AI literacy increases, AI integration and enhancement of critical thinking skills also increase. Regression analysis identified AI integration as a significant predictor of critical thinking development. Challenges remain in the effective implementation of AI, including concerns about overreliance on AI-generated responses and the need for clear assessment guidelines. Interestingly, years of teaching experience did not significantly influence participants’ AI literacy, perceptions, or integration. This study highlights the importance of developing comprehensive AI literacy programs for educators and integrating AI into curriculum structures to balance AI-enhanced learning with human-centered pedagogy. These findings emphasize the need for thoughtful implementation and ongoing research to effectively leverage AI in promoting critical thinking skills in science education.

This study investigates the influence of artificial intelligence (AI) integration on teachers’ professional identity and job satisfaction using a quantitative research design involving 251 respondents. Descriptive statistics showed relatively high levels of AI integration (M = 3.98, SD = 0.62) and professional identity (M = 4.12, SD = 0.58), indicating strong engagement with AI tools and a well-defined sense of professional role among teachers. Pearson correlation analysis revealed a moderately strong, statistically significant positive relationship between AI integration and professional identity (r = 0.612, p = 0.000), demonstrating that increased use of AI is associated with a strengthened professional identity. Mediation analysis further indicated that institutional factors significantly influence the relationship between AI integration and job satisfaction, with AI integration positively predicting institutional support (β = 0.54, p = 0.000) and institutional factors strongly predicting job satisfaction (β = 0.47, p = 0.000). Both a significant direct effect (β = 0.29, p = 0.001) and a strong indirect effect (β = 0.25, p = 0.000) were found, confirming partial mediation. These findings highlight that AI not only enhances teachers’ identity and satisfaction but that successful implementation relies heavily on institutional readiness and support. Overall, the results underscore the importance of adopting teacher-centered AI strategies that reinforce professional identity, reduce workload, and enhance well-being.

With the growing integration of generative artificial intelligence (GAI) tools such as ChatGPT into higher education, understanding the factors influencing students’ use of GAI for academic writing tasks has become increasingly urgent. This study investigates the key factors influencing students’ behavior in using GAI tools to complete academic writing tasks. In addition to core constructs of Unified Theory of Acceptance and Use of Technology (performance expectancy, effort expectancy, social influence, and facilitating conditions), the study incorporates three new constructs relevant to ethical aspects of academic writing (trust in GAI, ethical AI literacy, and academic integrity assurance). Data were collected from 1400 undergraduate students at three Beijing universities using a structured questionnaire. Structural equation modeling revealed that all eight hy-pothesized paths were supported. Among these predictors, academic integrity assurance (β = 0.194, p < 0.001) and ethical artificial intelligence literacy (β = 0.177, p < 0.001) emerged as the strongest predictors of behavioral intention, while behavioral intention (β = 0.429, p < 0.001) had a strong effect on actual use behavior. These findings highlight the role of ethical and cognitive factors in shaping students’ adoption of GAI for academic writing and offer valuable implications for valuable insights for AI-informed teaching and governance.