2026· ACCOUNTING AND CONTROL· Vol 5-5, pp. 75-94· 0 citations
TL;DR
The paper substantiates the need to shift the focus of education from mechanical coding to prompt engineering, refactoring, and auditing of AI- generated solutions, as well as to the development of ethical reflection.
Abstract
The rapid development of generative artificial intelligence (GenAI) technologies is reshaping the IT industry landscape. Large language models and automated code generation systems take over routine programming and design operations. Against this background, a contradiction emerges between traditional IT training models, centered on mastering syntax and basic algorithms, and current labor market demands, where AI orchestration skills, architectural thinking, and critical verification of machine solutions acquire greater weight. The aim of this study is to identify key areas and develop a conceptual model for transforming the professional training of future IT specialists in the context of the widespread adoption of generative AI. This study utilizes methods of systemic analysis of employer requirements, comparative pedagogical analysis of domestic and international practices, and pedagogical modeling. The paper substantiates the need to shift the focus of education from mechanical coding to prompt engineering, refactoring, and auditing of AI- generated solutions, as well as to the development of ethical reflection. An updated model of IT specialist competencies is proposed, including a new block on "Human- AI Collaboration." Methodological approaches for integrating GenAI tools into the educational process have been developed, including a transition to authentic assessment formats that focus on the decision- making process, not just the final software product.
The development of generative artificial intelligence (GenAI) and its integration into the industrial sector is influencing the range of skills in demand in the labor market. To prepare competitive professionals, higher education systems need to develop students’ skills in interacting with large language models (LLMs) as well as soft skills, such as critical thinking, which enable them to adapt to changing requirements. Prompt engineering, as the process of creating and modifying queries to LLMs, is becoming an important tool in education. However, existing research on the potential of prompt engineering for critical thinking development is primarily theoretical. The aim of this empirical study was to identify opportunities for developing specific aspects of critical thinking through prompt engineering training. The target sample included 93 engineering students who collaboratively completed tasks in the discipline “Legal regulation in the field of communications” using generative AI tools. Thirty-eight student dialogues with LLMs were analyzed using qualitative content analysis. Eight interaction patterns were identified, some of which were associated with the use of prompt engineering techniques. The most common pattern was the addition of information from lectures or other sources, indicating students’ efforts to refine and improve LLM responses. The data analysis revealed the manifestation of critical thinking aspects, such as analysis, comparison, and synthesis of information, in student prompts. A comparison of the results from two coding stages demonstrated a connection between three of the eight patterns and the aforementioned critical thinking aspects. The study suggests that prompt engineering training can become a promising tool for developing critical thinking in students, provided certain educational conditions are met. Additionally, the results indicate the potential of using LLM dialogue analysis to assess student skills.
V. G. Kiselyova (Lavrovskaia)· Informatics and Education· 0 citations
It is concluded that academic institutions must use clear ethical practices and AI-aware assessment designs to ensure that technology is used as an assisting tool that improves users' learning while ensuring the fundamental values of education.
Sugandha Nandedkar, Prachi Waghmare, Ashwini Swami et al.· International Scientific Jou...· 0 citations
Due to great advancements in technology, the 21st century has been turned into an
era of digital revolution where the Artificial Intelligence emerged in more and more
fields of activity, including education and the teaching and studying of foreign
languages. The present paper adopts an exploratory approach based on the analysis
of current AI tools which may be used in the ESP instruction by teachers and students
to mark a transformative shift towards a successful and meaningful process of
language acquisition. It relies on both personal teaching experience and the
perspective of students majoring in Electrical Engineering at the University of
Craiova, Romania when it comes to the use of AI platforms to improve their knowledge
of the language. The AI-driven tools which provide context-specific language
instruction offer instant feedback, domain-specific interactions, the prospect of
autonomous practice, premises for an efficient teaching and learning process. Yet, a
successful integration of AI depends on pedagogical, ethical and practical factors.
Diana Marcu· ANALELE UNIVERSITĂȚII DIN CR...· 0 citations
The article substantiates the theoretical and practical aspects of integrating generative artificial intelligence (AI) and large language models (LLMs) into the educational process of professional pre-higher education institutions to shape the professionally oriented digital competence of future professional junior bachelors of law, alongside analyzing the associated socio-legal and pedagogical risks. Based on the synergy of systemic, competence-based, and activity-based approaches, as well as methods of pedagogical modeling and case studies (specifically evaluating US and Chinese judicial precedents), the study proves the necessity of transitioning from a knowledge-based to an activity-based learning model. The paper reveals the potential of generative AI as a tool for optimizing students' routine processes (searching regulatory frameworks, analyzing big data) and simulating professional scenarios. Particular attention is paid to the foreign language preparation of future lawyers (ESP); AI is identified as an adaptive contextual tutor that deconstructs Anglo-American legal concepts and transforms passive lexical acquisition into active communication skills through role-play simulations and instant feedback. The author proposes a dualistic modular framework of AI competence, consisting of invariant (universal prompt engineering, academic autonomy) and variable (specialized legal software) modules. Key risks are identified and systematized: neural network "hallucinations," AI plagiarism, the devaluation of fundamental education, and clip-based thinking. The student's role is defined as a critical supervisor of digital assistants, which requires advanced data verification skills through official legislative registries. Finally, the study justifies recommendations for the institutional regulation of AI boundaries and the transformation of State Final Examination (SFE) formats through the introduction of oral examinations and practice-oriented case studies. The research materials can be used to update the educational programs of the "Law" specialty (081) and professional development programs for teachers of professional pre-higher education institutions.
The construction industry continues to face high levels of accidents despite the use of various safety training approaches, highlighting the need for more effective and responsive methods. This study examines the role of Generative Artificial Intelligence (GenAI) in potentially improving construction safety training by exploring the development of training practices and identifying the shortcomings of existing approaches. A systematic literature review (SLR) was conducted to analyse safety training methods and emerging GenAI applications, followed by validation interviews with industry experts in South Australia to ensure practical relevance. Emergent findings show that safety training has progressed through three main stages: instructor-led, digital and GenAI-enabled. However, instructor-led and digital approaches remain limited by non-interactive learning, limited flexibility to different learner needs, lack of real-time feedback and weak alignment with actual site conditions. In contrast, GenAI offers opportunities to support more interactive, personalised and context-aware training through technologies such as large language models (LLMs), adaptive learning systems, computer vision and scenario generation. Despite these benefits, significant challenges related to data quality, system reliability, ethical concerns and organisational readiness continue to affect implementation. Based on these findings, the study develops an integrated framework that links training evolution, key challenges and GenAI capabilities, providing practical guidance to improve safety training in construction.
Thamali Sarathchandra, Giphy George, Udara Ranasinghe et al.· Buildings· 0 citations
The rapid development of generative artificial intelligence (AI) risks widening gaps in digital literacy, critical thinking skills, and cognitive problem-solving, particularly for undergraduate students who will encounter AI tools in academic and professional contexts. Critical thinking is also identified as a key competency in engineering practice, with recent studies raising concerns about how AI might affect students’ problem-solving skills. The AI Client for Engineering (ACE) was designed to support critical thinking and discussion in engineering design courses. This paper outlines the development process and customizable alignment with pedagogical outcomes. In a pilot implementation, students used ACE as a tool for asking questions, seeking guidance, and simulating real-world interactions within an engineering organization. Through this integration, ACE aims to provide students with knowledge and practical experience, preparing them for future challenges and opportunities in academic, professional, and industry contexts.
Elias Poitras-Whitecalf, Emily Marasco, Keeryn Johnson· Proceedings of the Canadian...· 0 citations