THE APPROPRIATE USE OF ARTIFICIAL INTELLIGENCE IN STUDENT LEARNING

Purpose: This analysis aims to propose guidelines for artificial intelligence (AI) research ethics in scientific publications, intending to inform publishers and academic institutional policies in order to guide them toward a coherent and consistent approach to AI research ethics.Methods: A literature-based thematic analysis was conducted. The study reviewed the publication policies of the top 10 journal publishers addressing the use of AI in scholarly publications as of October 2024. Thematic analysis using Atlas.ti identified themes and subthemes across the documents, which were consolidated into proposed research ethics guidelines for using generative AI and AI-assisted tools in scholarly publications.Results: The analysis revealed inconsistencies among publishers’ policies on AI use in research and publications. AI-assisted tools for grammar and formatting are generally accepted, but positions vary regarding generative AI tools used in pre-writing and research methods. Key themes identified include author accountability, human oversight, recognized and unrecognized uses of AI tools, and the necessity for transparency in disclosing AI usage. All publishers agree that AI tools cannot be listed as authors. Concerns involve biases, quality and reliability issues, compliance with intellectual property rights, and limitations of AI detection tools.Conclusion: The article highlights the significant knowledge gap and inconsistencies in guidelines for AI use in scientific research. There is an urgent need for unified ethical standards, and guidelines are proposed for distinguishing between the accepted use of AI-assisted tools and the cautious use of generative AI tools.

Objective: To explore the perception of university students on the use of Artificial Intelligence (AI) tools for the development of autonomous learning. Theoretical Framework: The research is based on Technological Acceptance Theory and Constructivism, focusing on the perception of AI in autonomous learning of university students. Method: Quantitative approach with a descriptive scope, the sample consisted of 665 students enrolled in the Faculty of Education Sciences and Languages (FCEI) of the Peninsula de Santa Elena State University (UPSE)-Ecuador; in the collection of information, the Questionnaire of Perception on the Use of Artificial Intelligence for Autonomous Learning was designed based on 4 dimensions of both variables, and the statistical program SPSS version 29 was used for data processing. Results and Discussion: The results indicate that students show a favorable perception towards the use of AI tools for the autonomous learning process, however, although AI is recognized as a potential tool in university environments, there are still challenges to be overcome. Research Implications: The study has practical implications for strengthening in students the digital competencies needed to effectively use AI tools in their autonomous learning. Originality/Value: The research provides data on the perception of AI tools among university students, offering a starting point for future technology integration strategies in universities.

This paper presents the results of a survey on the use of artificial intelligence (AI) among teachers in Poland ( N = 289). The survey, conducted in December 2024 and January 2025, used the extended educational technology acceptance model (EETAM) to capture factors supporting and blocking the integration of AI in education (primary and secondary schools). The aim of the study is to identify factors influencing the acceptance and use of AI tools by teachers in their professional work. Based on the EETAM, the relationships between perceived usefulness, ease of use, digital competence, AI‐related concerns, attitudes, intention to use and actual use of AI are analysed. This study is unique in that it fills a local empirical gap (based on EETAM assumptions) on AI usage patterns among teachers. Cluster analysis revealed three groups of teachers: (1) intensive users of AI (13.5%), (2) occasional users (30%) and (3) nonusers (43.5%). The results indicate that the most frequently used functions of AI are information retrieval and text translation, while more advanced applications remain marginally used in educational contexts. In turn, structural modelling confirmed the key role of perceived usefulness and digital competence in shaping intentions to use AI, which in turn have a strong influence on actual use. Perceived ease of use had a moderate impact on usability, while anxiety relating to AI appeared to be of minimal importance. The overall model explained 72% of the variance in intention to use AI and 30% of actual use, highlighting the high effectiveness of the research approach adopted. The results highlight the need to further improve teacher education programmes in the context of AI use, especially with regard to the development of teachers’ digital competences, as well as to strengthen positive attitudes towards AI, also by emphasising the praxeological nature of the solutions analysed.

Will ChatGPT undermine ethical values in nursing education, research, and practice?

This paper considers the combination of Artificial Intelligence (AI) and the IT project management field of project management risk in the context of Management Information Systems (MIS). In IT projects, risks are identified, analyzed, and responded to with varying degrees of efficiency. This study explores the use of AI tools (including machine learning regression and neural networks) to improve the processes of AI-enhanced tools integrated into established risk management processes. Improved decision-making capabilities are the result. Performance evaluation tools such as Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) as well as measures of precision, recall and the F1 score were the metrics of the study to measure the efficiency and effectiveness of AI as contrasted with the AI tools and the implementation of traditional risk systems management. AI, with respect to risk management, traditional, and non-AI systems, risk systems management design, measures, time, project success, and overall outcome, significantly AI MIS and risk management project are realized. AI systems, project management tools, and human cooperation, in project deliverables, management timely project streamline outcomes management is more project completion are combined with MIS. This paper considers project risk management and the use of project management AI tools in an organizational context

This study empirically investigates the use of artificial intelligence (AI) tools within Hungarian religious communities, with a focus on Catholic respondents, to assess their awareness, application, and acceptance of AI in religious contexts. By religious communities, we do not mean monastic or priestly communities, but rather communities of lay religious people. Conducted between 10 February and 11 March 2025, the questionnaire-based research (N = 133) employs Campbell’s Religious Social Shaping of Technology (RSST) framework to analyze attitudes toward AI across 15 religious functions. Six hypotheses explore gender differences, religiosity types (church-based vs. self-defined), and the acceptability, authenticity, and ethicality of AI applications. Findings reveal high acceptance for administrative tasks (e.g., email list updates: 64.7%) and technical functions (e.g., live translation: 65.4%), but low acceptance for spiritual roles (e.g., spiritual leadership: 12.8%). Self-defined religious individuals are significantly more accepting, perceiving AI as more authentic and ethical compared to those adhering to church teachings. No significant gender differences were found. The study contributes to digital religion studies, highlighting the influence of religiosity on AI adoption, though its non-representative sample limits generalizability.

Technical English (TE) proficiency is crucial for the future careers of polytechnic students. While Artificial Intelligence (AI) tools offer significant potential to enhance language learning, their effectiveness relies on student acceptance and use. There is limited understanding of what drives polytechnic students to adopt these tools specifically for TE. This study aims to identify the key factors influencing polytechnic students' acceptance and use of AI tools in this context and employ a quantitative approach based on the Technology Acceptance Model (TAM) and Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from 100 Polytechnic Kota Bharu (PKB) students enrolled in TE courses. The research investigates core antecedents, primarily perceived usefulness (PU) and perceived ease of use (PEOU), and their impact on students' behavioral intention (BI) to use AI tools. The potential influence of external factors such as social influence and lecturer support are examined. The study found PEOU was identified as a critical antecedent, which significantly positively affected PU and BI. The study reaffirmed the significant predictive power of BI on AU, indicating that students' stated intentions reliably translate into their subsequent usage behaviour. This research will offer practical recommendations for educators seeking to integrate AI tools effectively into TE instruction. Theoretically, this study contributes to understanding technology adoption within the specific domain of technical and vocational language education, providing valuable insights for leveraging AI to improve essential communication skills for aspiring technical professionals.

This study examines pre-service English language teachers’ grounds and connections between the use of generative Artificial Intelligence (AI) tools in EFL writing skills and future prospects to integrate them into their teaching practices. Employing a qualitative research paradigm, a researcher-developed survey was used to elicit the perspectives of 28 pre-service English language teachers and 10 teacher trainers. The stages of qualitative data analysis were followed, emergent ideas embedded in the responses were labeled and the codes were clustered into broader themes to obtain a description of their reflections. This study documented reflections on the transformative impact of generative AI in EFL writing. Benefits were reported considering the use of AI tools to overcome writer’s block and get language support, and instantaneous and personalized feedback to the texts. Foregrounding concerns regarding academic misconduct, a need was highlighted for ethical guidelines and enhancement to AI literacy to ensure the validity of AI-generated content. Further, they suggested reformulating assessment and evaluation in EFL writing skills and moving away from result-oriented exams suggesting the adoption of performance-based and process-oriented assessments. Accordingly, ethical and pedagogical implications were offered to adopt a critical stance to improve AI literacy skills in EFL writing development.

Die folgenden Auszüge zu KI und Ethik stammen aus einem UNESCO-Dokument, das im Rahmen einer internationalen Konferenz in Peking 2019 entstand. Sie sollen auf die weltweite Bedeutung der Debatte um KI und Ethik aufmerksam machen. BEIJING CONSENSUS ON ARTIFICIAL INTELLIGENCE AND EDUCATION Preamble 1. We, the participants of the International Conference on Artificial Intelligence (AI) and Education, including 50 government ministers and vice ministers, as well as around 500 international representatives from more than 100 Member States, United Nations agencies, academic institutions, civil society and the private sector, met in Beijing, People’s Republic of China, from 16 to 18 May 2019. [...] 2. We reaffirmed the commitment made in the 2030 Agenda for Sustainable Development, particularly Sustainable Development Goal (SDG) 4 and its targets, and discussed the challenges faced by education and training systems in achieving SDG 4. [...] 6. We also recognize the distinctive features of human intelligence. Recalling the principles set forth in the Universal Declaration of Human Rights, we reaffirm UNESCO’s humanistic approach to the use of AI with a view towards protecting human rights and preparing all people with the appropriate values and skills needed for effective human-machine collaboration in life, learning and work, and for sustainable development. 7. We also affirm that the development of AI should be human-controlled and centred on people; that the deployment of AI should be in the service of people to enhance human capacities; [...] and that the impact of AI on people and society should be monitored and evaluated throughout the value chains. [...] AI to Empower Teaching and Teachers 12. Be mindful that while AI provides opportunities to support teachers in their educational and pedagogical responsibilities, human interaction and collaboration between teachers and learners must remain at the core of education. Be aware that teachers cannot be displaced by machines, and ensure that their rights and working conditions are protected. [...] Ensuring ethical, transparent and auditable use of education data and algorithms 28. Be cognizant that AI applications can impose different kinds of bias that are inherent in the data the technology is trained on and uses as input [...]. Be cognizant of the dilemmas of balancing between open access to data and data privacy protection. Be mindful of the legal issues and ethical risks related to data ownership, data privacy and data availability for public goods. [...] 29. Test and adopt emerging AI technologies and tools for ensuring teachers‘ and learners’ data privacy protection and data security. Support robust and long-term study of deeper issues of ethics in AI, ensuring AI is used for good and preventing its harmful applications. Develop comprehensive data protection laws and regulatory frameworks to guarantee the ethical, non-discriminatory, equitable, transparent and auditable use and reuse of learners’ data. 30. Adjust existing regulatory frameworks or adopt new ones to ensure responsible development and use of AI tools for education and learning. Facilitate research on issues related to AI ethics, data privacy and security, and on concerns about AI’s negative impact on human rights and gender equality. https://unesdoc.unesco.org/ark:/48223/pf0000368303 [Zugriff: 21.09.2020]

The purpose of this research is to understand the challenges, opportunities, and implications associated with the design and use of Artificial Intelligence (AI) tools to preserve the native Quechua language in Peru. To do so, we conducted a theoretical analysis regarding how AI could be applied to protecting Quechua. We also interviewed two Quechua speakers, an expert in the Quechua language, and two experts in language localization and translation. The purpose of the interviews was for the interviewees to express their opinions on the potential design and use of AI tools in the conservation of Quechua; considering the challenges, opportunities, and implications that this would have. The conclusion is that Quechua is one of the vital languages in Peru that helps maintain the social and cultural traditions of the country; it is necessary to maintain this state of vitality through various means. And, although technological projects for its preservation have been undertaken at the state level, these have not had a great impact on the population because the technologies created have not been attractive or dynamic for the dissemination and learning of the Quechua language.

Integrating artificial intelligence (AI) technologies into academic writing presents opportunities and challenges, as use of AI promotes efficiency in knowledge production but also exacerbates existing disparities between developed and developing nations, with developing nations lagging behind in terms of access and the expertise for using them productively. Moreover, while AI tools provide support for innovative research, writing assistance, and data analysis, there are growing concerns about the quality of postgraduate student theses and publications, written using AI tools, as they contain false statements and violate research ethics. Based on survey data and secondary literature, this study investigated the current application of AI tools in academic writing by Humanities and Social Science postgraduate students in a Kenyan university. The study aimed to: establish the uptake and use of AI tools in academic writing, assess student attitudes on using AI tools in academic writing; and explore challenges influencing the use of AI tools in academic writing. The study revealed that students often use AI tools that generate content, provide analysis and paraphrase texts, such as chatGPT, Gemini Grammarly and Quillbot. Students had positive attitudes to adopting AI tools for academic writing, however, they reported limitations in proficient use of AI tools, poor writing and research skills, along with lack of ICT resources and AI tools. It is recommended that for effective integration of AI tools in academic writings, higher education institutions should provide ICT resources, AI tools and offer training in research skills, writing skills and use of AI tools for writing.

Introduction: The availability and use of artificial intelligence (AI) tools is accelerating significantly. As these technologies proliferate, many post-secondary institutions have responded by banning students from using AI tools such as ChatGPT and framing the conversation as breaches of academic integrity. Background: Despite these institutional responses, many students adopt these tools as part of their learning journey. In health care settings, the adoption of such tools in the context of patient care provision is a reality. Consequently, there is a relevant pedagogical opportunity to examine how such tools inform the experiential learning of nursing students and their future practice. Methods: To address the dearth of information regarding nursing students’ perceptions of using AI tools, a Canadian university teaching team incorporated ChatGPT into an undergraduate nursing course assignment. A pilot quasi-experimental pre-post-test survey design was employed to examine student perceptions of using ChatGPT. After obtaining institutional ethics approval, a neutral third party collected the anonymous data. Findings: Pilot study results highlighted significant student concerns regarding the ethics of using AI tools. Additionally, students described such tools as meaningful avenues to support learning access and equity. Finally, students identified a high probability of use of AI tools in their future practice, suggesting that exposure and support during learning can positively influence responses to these tools in practice settings. Conclusion: The students surveyed are now practising nurses; thus, findings may provide insight into perceptions of new nurses regarding the integration of AI to support competencies required by the nurses of tomorrow.

Despite constant increase in the use of Artificial Intelligence tools in educational settings, nothing is known about students’ personality traits associated with the use of these resources. Thus, the objective of this study was to explore possible links between Artificial Intelligence use and personality traits among university students. A cross-sectional ex-post facto quantitative study was conducted with 1761 undergraduate students (Mage = 20.30; SD = 2.76). Validated questionnaires were administered for data collection, always under the supervision of members of the research team. According to multinomial regression analysis, neuroticism and extraversion were related to sporadic use and frequent use, respectively. Agreeableness increased the odds of using Artificial Intelligence to solve every day doubts and neuroticism to do academic work. Conscientiousness was negatively related to the use of Artificial Intelligence to do academic work and to create fake content. Higher scores in openness increased the likelihood of creating fake content using Artificial Intelligence. These results provide novel information about personal characteristics associated with the use of Artificial Intelligence tools among university students. Educators should consider this information when implementing Artificial Intelligence into their educational strategies.

This study explores the role of artificial intelligence (AI) in K–12 student assessment practices, focusing on educators’ use of AI tools. Through content analysis of active Facebook groups dedicated to AI in education, the authors examined how educators integrate AI into assessment across various grade levels and subjects. Using the Technology Integration Model, they analysed posts to evaluate the use of AI across subjects and grade levels. The findings revealed a progression from initial interest and experimentation with AI to more advanced, adaptive uses in assessment creation and grading. Educators reported positive experiences with AI-driven tools, especially in automating tasks and gamifying assessments. However, challenges such as ensuring reliable, context-specific feedback persist. Overall, the research highlights AI’s potential to enhance student-centred assessment practices and provides insights for educators, administrators and policymakers on AI’s evolving role in education.

Our presentation focuses on the topic and relationship between religion, ecclesiastical journalism and media technology, artificial intelligence. In the first part of our presentation, we will review how artificial intelligence is changing the media industry on a global scale. As a result, what new inequalities are created in the media industry. After that, we will present which processes related to new AI applications can be automated in the field of media content production. And we also cover the transformation of the role of a journalist and the perception of a journalist’s role. In our presentation, we will demonstrate what artificial intelligence applications Hungarian religious and ecclesiastical media content creators use in their work, what attitudes they have regarding artificial intelligence, and what journalistic ethical issues concern them. We also present whether religious institutional or editorial regulations regarding the applicability of artificial intelligence are implemented or not. In our presentation, we show the results of qualitative research conducted in the fall of 2023 and quantitative research conducted in the spring of 2024. In the fall of 2023, we conducted in-depth interviews with 40 journalists regarding artificial intelligence. The gender and generational differences are clearly visible from the results. Building on this, we prepared a questionnaire in the spring of 2024, in which we also asked about the attitudes of religious and nonreligious content producers regarding artificial intelligence. In our lecture, we present the results of this research. What differences can be shown between religious and non-religious content creators in the use of artificial intelligence tools during their journalistic work.