Digital tools and their role in optimizing the detection of academic plagiarism

Objective. This paper aims to delineate how digital tools have transformed the process of plagiarism detection within the academic context. Design/Methodology/Approach. This study was conducted through a systematic review of the liter-ature. The PRISMA methodology was employed for the search and selection of articles. The research was conducted using the Scopus and Web of Science databases, from which 20 articles addressed the subject matter between 2014 and 2024 were selected. Results/Discussion. The findings demonstrated a notable advancement in the precision and effec-tiveness of these technologies. Ethical concerns about privacy and data utilization were also identified, necessitating their monitoring in subsequent investigations. Conclusions. Considering the outcomes mentioned above, digital instruments have experienced a notable evolution in the domain of academic plagiarism detection. Tools based on artificial intelligence and developed algorithms offer high accuracy and the potential to identify complex plagiarism structures, such as paraphrasing and translations. Nevertheless, the implementation and efficacy of these tools exhibit considerable variability across institutions, contingent upon factors such as the availability of accessible resources and the extent of personal training. Originality/value. The research offered a revised perspective on the capacity of diverse technologies, including machine learning algorithms and artificial intelligence, to identify deceptive behaviors. The study considered the ethical and pedagogical implications of their use, thereby providing a solid basis for future developments in educational policy and the continuous improvement of these tools.