The rapid integration of generative artificial intelligence tools in higher education has raised significant questions regarding their influence on academic writing practices. This study examines the mediating effects of a text-generating system, particularly ChatGPT developed by OpenAI, on the written productions of first-year university students in Algeria. Rather than assuming a direct causal impact on the development of autonomous writing skills, the research adopts a cautious methodological stance by explicitly distinguishing between improvement of AI- assisted textual output and genuine enhancement of writing competence. The study is based on a comparative analysis of initial drafts and revised versions produced after interaction with an AI tool. Lexical, syntactic, and discursive transformations were examined using a structured evaluation grid. The findings indicate a noticeable improvement in the formal quality of texts following algorithmic mediation, particularly in terms of grammatical accuracy, lexical diversification, and argumentative coherence. However, the results do not provide sufficient evidence to conclude that students’ independent writing skills have sustainably developed. The observed improvements primarily reflect immediate technical assistance rather than long-term competence acquisition. In order to assess the statistical significance of the observed differences between pre- and post-intervention texts, the non- parametric Wilcoxon signed-rank test was employed. The findings indicate a statistically significant improvement in the formal quality of texts following algorithmic mediation, particularly in terms of grammatical accuracy, lexical diversification, and argumentative coherence. However, the results do not provide sufficient evidence to conclude that students’ independent writing skills have sustainably developed. The observed improvements primarily reflect immediate technical assistance rather than long-term competence acquisition. This study contributes to ongoing debates by offering a nuanced perspective on the pedagogical role of generative AI in Algerian higher education.
In a world where technology is rapidly gaining popularity and is increasingly fulfilling various functions, the issue of machine translation is also becoming a matter of importance. Artificial Intelligence (AI) is quickly turning into a necessity as far as speed and accuracy are concerned. And if AI translation tools come in handy in almost all spheres of rendition from a source (SL) to a target language (TL), there are some challenges when transferring certain types of phrases, sentences and texts. With the assistance of AI tools, translation is becoming a quicker way to handle general phrases, language chunks and texts, yet a personal knowledge of culture and culture-specific competence is needed when phraseological units are concerned. They are culturally-bound units, whereby linguistic knowledge, lexical fluency and ready-made grammatical constructions are not enough to accurately convey the message of the unit. A knowledge of the culture, background and ideology of a social group or people is necessary so as to achieve adequate rendition of ideas and thoughts. Researchers (Mercan, 2024; Shalevska, 2025) have placed the importance of MT, yet they have focused on the significance of the human factor as well. The current study is thus an attempt to delve into the matter of translating phraseological units from Bulgarian into English with the assistance of AI translation tools, thus unveiling the degree to which they can be serviceably and relevantly transferred from one language into another and seeing as to what extent the meaning behind the units has been preserved.
The paper examines the contemporary figure of the reader at the intersection of literary style and algorithmic text production in the context of artificial intelligence and digital culture. Building on the historical shifts in literary theory – from the proclaimed “death of the author” to the growing emphasis on the reader’s role – the study argues that the reader has become a particularly vulnerable and contested figure in the present-day textual ecosystem. Special attention is paid to the unprecedented abundance of AI-generated texts and the ways in which this “textual excess” affects readers’ cognitive, aesthetic, and critical capacities. The article conceptualizes style not only as a textual or authorial category but also as a reader-oriented phenomenon shaped through reading practices, taste formation, and cultural experience. Reading is approached as both an individual and a social act that contributes to cultural identity and collective memory. In this framework, the paper introduces and discusses the notion of a “narcissistic reader”, a type emerging under the conditions of digital acceleration, utilitarian reading practices, and the dominance of algorithmically generated content. Rather than offering definitive solutions, the study outlines key risks and tendencies affecting the act of reading today, emphasizing the decisive role of the reader’s intentionality, critical thinking, and stylistic sensitivity in preserving meaningful literary reception in an algorithm-driven environment.
The adoption of GenAI in research is reshaping the epistemic conditions of knowledge production. While LLMs are often perceived as neutral agents, this paper argues that the humanities and social sciences (HSS) serve as critical infrastructures for governing AI-mediated inquiry. Drawing on sociotechnical pragmatism, the article introduces epistemic archaeology: an interpretive orientation that treats AI outputs as stratified artifacts shaped by cultural and statistical histories. Rather than seeking validation in convergence, this approach interprets model divergence as signals of training data and epistemic constraints. By foregrounding interpretation, contextualization, and epistemic literacy, the work establishes the foundational coordinates for AI integration. This conceptual positioning preserves human responsibility and judgment as the primary locus of meaning in human–AI interaction. While serving as the theoretical base for future applications, the paper defines the ethical landscape for responsible academic research.
The object of this article is the role of artificial intelligence (AI) in the academic field. The objective of this article is to discuss different ways in which AI can be used in academic education and scientific research work. Specific policies in an international aspect, which try to regulate and balance this ratio, have been presented. The article outlines three specific aspects of AI in the academic educational and scientific research field. Artificial intelligence should not be ignored, but rather integrated through well-structured policies or approaches in academic practices. Only in this way is there a possibility of preserving integrity and apply critical measures against fraud. What makes the second specific of AI is that it can perceive simultaneously as a tool and as an object of influence. This article describes its function as a research and methodological tool, but what is more interesting is its presence as an active factor, which alters academic practices and predefines criteria of validity. The third aspect the article examines is the possibilities for an ethical and transparent AI and it elaborates on the fact that responsible use of AI is directly connected with creating policies that should regulate the extent of its use that guarantee transparency, methodological criticality, copyright management, declaration of content, etc. One of the conclusions is that the new reality enforces a change of perspective concerning the essence of tools which shape the competencies of modern individuals.
