Introduction: Dynamic assessment has demonstrated effectiveness in enhancing writing skills among ESL learners and may be especially useful in the improvement of writing mechanics by enabling individualized mediation and adaptive instruction. The major objectives of the current study were to examine the effectiveness of dynamic assessment in reducing writing mechanics errors among Pakistani learners in their essay drafts. The study also explored how experimental group students perceive the mediational intervention and dynamic assessment as an alternative approach to static assessment in improving writing mechanics. Methodology:  To perform the study, a sequential explanatory design was used to explore the effect of dynamic assessment instruction on Pakistani ESL learners’ writing mechanics. The sequential explanatory design allowed us to understand the phenomenon under study more comprehensively by collecting both quantitative and qualitative data in sequence. The quantitative part of the study used an interventionist model, with a pretest-treatment-posttest design, while the qualitative part used semi-structured interviews. Following a quantitative test of the efficacy of treatment, the researchers interviewed the participants of the experimental group to investigate their perceptions of the mediation approach. The interviews were recorded, transcribed, and analyzed for recurring themes and sub-themes. Results: The quantitative findings of this study confirmed the significant impact of dynamic assessment and were consistent with previous research reporting it as an effective approach to improving writing skills. Regarding the qualitative findings, dynamic assessment positively affected students’ writing mechanics. Students reported that dynamic assessment could reduce writing anxiety, enhance self-efficacy, and provide ample opportunities to learn from their errors. Conclusion: The findings of the current study showed that the interaction between teachers and students during mediation significantly contributed to their writing development and helped them work toward self-regulation.

This autoethnographic account narrates my transition as a first-year Ph.D. student at Texas A&M University, USA. Employing Kurt Lewin’s Change Model, I have structured my narrative around three phases: (a) unfreeze, (b) change, and (c) refreeze. The unfreeze phase details the process of unlearning, adjusting to American academic practices, and the initial cultural shock intensified by homesickness. The change phase describes embracing a new identity, integrating into campus and cultural life, and overcoming academic challenges. Lastly, the refreezing phase involves consolidating new beliefs, perspectives, and skills, solidifying the transition to becoming a more confident and competent scholar. This autoethnographic account narrates the dilemmas and breakthroughs I encountered, with the aim of providing insights for future Asian students aspiring to pursue doctoral programs in the USA.

The authors present a qualitative comparative analysis of AI policies from five major academic publishers: Taylor & Francis, Elsevier, Sage, Wiley, and Springer Nature. They employed position statements of the Committee on Publication Ethics (COPE) as their analytical framework. Six key themes emerged: permitted AI use, prohibited AI use, disclosure requirements, AI as author and co-author, AI in peer review, and policy adaptability. They found substantial differences among publishers in defining acceptable AI use and disclosure requirements. While all publishers explicitly state that AI cannot claim authorship, their policies differ in permitted AI roles, particularly regarding peer review and manuscript preparation. These inconsistencies create ethical challenges for authors and reviewers. The study concludes by recommending clearer, discipline-specific guidelines and enhanced reviewer training to ensure responsible AI use for upholding scholarly integrity.

The authors present a qualitative comparative analysis of AI policies from five major academic publishers: Taylor & Francis, Elsevier, Sage, Wiley, and Springer Nature. They employed position statements of the Committee on Publication Ethics (COPE) as their analytical framework. Six key themes emerged: permitted AI use, prohibited AI use, disclosure requirements, AI as author and co-author, AI in peer review, and policy adaptability. They found substantial differences among publishers in defining acceptable AI use and disclosure requirements. While all publishers explicitly state that AI cannot claim authorship, their policies differ in permitted AI roles, particularly regarding peer review and manuscript preparation. These inconsistencies create ethical challenges for authors and reviewers. The study concludes by recommending clearer, discipline-specific guidelines and enhanced reviewer training to ensure responsible AI use for upholding scholarly integrity.