This research aims to systematically review the integration of artificial intelligence (AI) in English language teaching and learning. It specifically seeks to analyze the current literature to identify how AI could be utilized in English language classrooms, the specific tools and pedagogical approaches employed, and the challenges faced by educators. Using the PRISMA-guided Systematic Literature Review (SLR) methodology, articles were selected from Scopus, Science Direct, and ERIC, and then analyzed thematically with NVivo software. Findings reveal that AI enhances English teaching through tools like grammar checkers, chatbots, and language learning apps, with writing assistance being the most common application (54.55% of studies). Despite its benefits, challenges such as academic dishonesty, over-reliance on AI (27.27% of studies), linguistic issues, and technical problems remain significant. The study emphasizes the need for ethical considerations and teacher training to maximize AI’s potential. It also highlights societal concerns, including the digital divide, underscoring the importance of equitable access to AI-powered education for learners of all socioeconomic backgrounds.

The proliferating field of writing education increasingly intersects with technological innovations, particularly generative artificial intelligence (GenAI) resources. Despite extensive research on automated writing evaluation systems, no empirical investigation has been reported so far on GenAI’s potential in cultivating intermedial writing skills within first language contexts. The present study explored the impact of ChatGPT as a writing assistant on university literature students’ intermedial writing proficiency. Employing a quasi-experimental design with a non-equivalent control group, researchers examined 52 undergraduate students’ essay writings over a 12-week intervention. Participants in the treatment group harnessed the conversational agent for iterative essay refinement, while the reference group followed traditional writing processes. Utilizing a comprehensive four-dimensional assessment rubric, researchers analyzed essays in terms of relevance, integration, specificity, and balance of intermedial references. Quantitative analyses revealed significant improvements in the AI-assisted group, particularly in relevance and insight facets. The findings add to the research on technology-empowered writing learning.

In recent years, particularly over the last 10–15 years, the scientific value of oral history in relation to historical and social knowledge has been increasingly recognized. Since the 1980s, oral history researchers have pioneered new approaches to interpreting human experience, highlighting oral biographical narratives and recounted experiences as valuable material for social research. According to Tsiolis, the biographical narrative approach has become an established scientific methodology for studying how social actors interact with their environment and respond to social changes, as these are reflected through their subjectivity. Based on the above, this study involved four academic lecturers who narrated their academic and professional journeys, the factors that influenced them, the challenges they faced, and the positive impact of their engagement with teaching in the context of Greek higher education. The research employed the methodology of narrative biography, allowing the participants to recount their academic trajectories spontaneously, recalling personal experiences and memories. Through these narratives, qualitative data emerged, which were analyzed and coded into common themes, leading to conclusions about the conditions, aspirations, and disappointments experienced by academics in higher education institutions. The paper concludes some limitations of the current study and offers suggestions for future research.