Exploring the Role of Artificial Intelligence in Second Language Acquisition

Today, when digital transformation affects the field of social work, the integration of artificial intelligence technologies into professional practices gains importance. This study examines social work students' views on artificial intelligence with a phenomenological approach. The aim of the study is to determine students' perceptions of artificial intelligence, its potential role in professional practices and their concerns about ethics. The study included 14 third and fourth year social work students living in Bandırma. A semi-structured interview form was used as a data collection tool, and in-depth interviews lasted between 30-45 minutes. The analyses were carried out by thematic analysis method using MAXQDA software. In the findings, 8 sub-themes and 27 codes were identified under 3 main themes: 'Perceptions of Artificial Intelligence', 'Intersection of Social Work and Artificial Intelligence' and 'Artificial Intelligence Education and Access'. While students emphasise the benefits of artificial intelligence such as making life easier (f=10) and fast access (f=8), they have concerns about lack of empathy (f=8), privacy and data security (f=8). In addition, the integration of artificial intelligence into the curriculum (f=9) emerged as an important need. The results show that artificial intelligence in social work education should be positioned in line with professional values.

Introduction: The integration of artificial intelligence (AI) into higher education is swiftly revolutionizing pedagogical methodologies, in conjunction with learning processes and research paradigms. The interdisciplinary potential of AI within academic settings was examined in this study, employing a case study conducted at the University of Tirana. Through the utilization of bibliometric analysis and survey-based research, this study comprehensively investigates the swiftly emerging trends in AI applications, students' significant familiarity with AI technologies, as well as the substantial challenges impeding broader adoption. The bibliometric analysis highlights significant exponential growth in AI research, particularly within pivotal domains such as finance and accounting, thereby emphasizing the swiftly increasing relevance of blockchain and automation. The survey indicates a robust enthusiasm among students for AI in educational settings. More than 90 percent of students actively incorporate AI tools in their project work. Nonetheless, resource limitations and ethical considerations, including privacy, data security, and algorithmic bias, pose considerable challenges to the widespread adoption of AI, despite the prevailing enthusiasm. Objective: The aim of this research is to examine the incorporation of Artificial Intelligence (AI) within the realm of higher education. This analysis concentrates on the applications, advantages, and challenges associated with AI, with the intent of advancing interdisciplinary research and educational methodologies at the University of Tirana. Theoretical Framework: This research expands upon the principles of AI adoption within the educational sector, alongside an examination of ethical considerations and multidisciplinary collaboration. Theories pertaining to technological integration and adaptive learning systems serve as the foundational framework for comprehending the implications of AI in the realm of education. Method: The methodology employs bibliometric analysis to examine AI-related research trends utilizing data from SCOPUS and conducts a survey to assess students' familiarity with and perceptions of AI. Data collection was facilitated through bibliometric instruments and an online survey incorporating Likert-scale and open-ended questions. Results and Discussion: The results underscore an increased focus on artificial intelligence (AI) and blockchain within scholarly research, wherein students exhibit considerable engagement and interest in AI applications. Nevertheless, limitations in resources and ethical issues, including privacy and bias, persist as primary challenges. The discourse underscores the imperative for investment in infrastructure and the incorporation of ethical education. Research Implications: This research highlights the imperative for higher education institutions to integrate artificial intelligence tools, cultivate adaptive curricula, and address ethical considerations in order to adequately prepare students for a future shaped by AI. The implications of these findings also pertain to educational policy and the formulation of interdisciplinary research strategies. Originality/Value: The study contributes by delivering a comprehensive bibliometric analysis and gives insights into student engagement with artificial intelligence. Its significance resides in presenting actionable recommendations to enhance the integration of artificial intelligence in higher education.

IntroductionRadiographer reporting is accepted practice in the UK. With a national shortage of radiographers and radiologists, artificial intelligence (AI) support in reporting may help minimise the backlog of unreported images. Modern AI is not well understood by human end-users. This may have ethical implications and impact human trust in these systems, due to over- and under-reliance. This study investigates the perceptions of reporting radiographers about AI, gathers information to explain how they may interact with AI in future and identifies features perceived as necessary for appropriate trust in these systems. MethodsA Qualtrics® survey was designed and piloted by a team of UK AI expert radiographers. This paper reports the third part of the survey, open to reporting radiographers only. Results86 responses were received. Respondents were confident in how an AI reached its decision (n = 53, 62%). Less than a third of respondents would be confident communicating the AI decision to stakeholders. Affirmation from AI would improve confidence (n = 49, 57%) and disagreement would make respondents seek a second opinion (n = 60, 70%). There is a moderate trust level in AI for image interpretation. System performance data and AI visual explanations would increase trust. ConclusionsResponses indicate that AI will have a strong impact on reporting radiographers’ decision making in the future. Respondents are confident in how an AI makes decisions but less confident explaining this to others. Trust levels could be improved with explainable AI solutions. Implications for practiceThis survey clarifies UK reporting radiographers’ perceptions of AI, used for image interpretation, highlighting key issues with AI integration.

The study aimed to assess teachers' perceptions of artificial intelligence (AI), their understanding of its potential advantages and disadvantages, and the specific training needs necessary for successful AI integration. The study aimed to assess teachers' perceptions of artificial intelligence (AI), their understanding of its potential advantages and disadvantages, and the specific training needs necessary for successful AI integration. A mixed-method research design was used in collecting and analyzing quantitative and qualitative data. Descriptive statistics was utilized to delineate teachers' perspectives on AI in education. Open-ended questions were employed to gather insights into the challenges teachers encounter when using AI in the classroom. The findings revealed that teachers' experiences with AI present opportunities and challenges in integrating technology into the classroom. While teachers expressed optimism about AI's potential to enhance education, citing benefits such as personalized learning, educator support, and administrative efficiency, they also voiced concerns about increased workload, excessive student reliance on technology, algorithmic bias within AI systems, and data privacy. A balanced approach to AI integration is recommended not only that complements traditional teaching methods and addresses privacy and algorithmic bias. Schools are encouraged to offer comprehensive professional development programs for teachers to introduce AI technologies, address the ethical and practical challenges associated with their use in education, ensure equitable access to AI tools, and improve technological infrastructure. Keywords: Artificial Intelligence, Capacity building ,Educators, Education, private schools,

This study examines EFL teachers' perceptions of artificial intelligence (AI) integration in a public secondary school in Santa Elena, Ecuador, employing a sequential explanatory mixed-methods design. Phase 1 consists of a systematic scoping review (PRISMA-ScR) synthesizing 21 peer-reviewed studies published between 2020 and 2025 on AI-enhanced EFL teaching, with emphasis on resource-constrained and Latin American contexts. Phase 2 reports descriptive findings from the EFL Teachers' Perceptions of AI Integration Survey (ETPAIS), a researcher-designed 24-item Likert instrument administered to all eight EFL teachers at the Unidad Educativa Otto Arosemena Gómez (N = 8; census sampling). Results reveal that teachers hold positive attitudes toward AI as a complementary pedagogical tool (D2: M = 4.13) but perceive institutional infrastructure as substantially inadequate for implementation (D3: M = 2.31). Professional development emerged as the most urgently demanded facilitating condition (Item 22: M = 4.63). These findings converge with international evidence regarding positive teacher conceptualizations of AI while diverging significantly regarding infrastructure sufficiency, confirming that adoption strategies derived from well-resourced contexts are not directly transferable to Ecuadorian public secondary education. Implications for educational policy and teacher training are discussed.

Artificial Intelligence (AI) in education sector is leading to a transformation in education. Whereas AI has a number of advantages like individualized learning and efficiency, it also poses some challenges involving ethics and human interaction. This paper will explore the potentials of AI applied to education, discuss its drawbacks, and review future trends that will shape the learning landscape. The article evaluated the pros and cons of AI in education, based on the views of fifty academics from different universities using a mixed method approach. The conclusions brought out of the analysis are in line with similar studies existing in the literature. For academics, the integration of AI has many positives aspects on the learning–teaching process including improvement in skills and competences of students. The findings reveal a strong correlation between participants' awareness of AI-related risks in education and their perceptions of AI's impact on the college education system, emphasizing the intricate link between awareness and attitudes towards AI in education. While the negative aspects brought out from the research are linked to generalizability. The contribution to be drawn from the results of this research is mainly empirical and practical. These opinions should be used as resources for managers, policy makers and researchers suggesting avenues for future research to broaden the scope and include diverse educational contexts

Artificial intelligence (AI) is widely considered to be the new technical advancement capable of a large-scale modernization of health care. Considering AI's potential impact on the clinician-patient relationship, health care provision, and health care systems more widely, patients and the wider public should be a part of the development, implementation, and embedding of AI applications in health care. Failing to establish patient and public engagement and involvement (PPIE) can limit AI's impact. This study aims to (1) understand patients' and the public's perceived benefits and challenges for AI and (2) clarify how to best conduct PPIE in projects on translating AI into clinical practice, given public perceptions of AI. We conducted this qualitative PPIE focus-group consultation in the United Kingdom. A total of 17 public collaborators representing 7 National Institute of Health and Care Research Applied Research Collaborations across England participated in 1 of 3 web-based semistructured focus group discussions. We explored public collaborators' understandings, experiences, and perceptions of AI applications in health care. Transcripts were coanalyzed iteratively with 2 public coauthors using thematic analysis. We identified 3 primary deductive themes with 7 corresponding inductive subthemes. Primary theme 1, advantages of implementing AI in health care, had 2 subthemes: system improvements and improve quality of patient care and shared decision-making. Primary theme 2, challenges of implementing AI in health care, had 3 subthemes: challenges with security, bias, and access; public misunderstanding of AI; and lack of human touch in care and decision-making. Primary theme 3, recommendations on PPIE for AI in health care, had 2 subthemes: experience, empowerment, and raising awareness; and acknowledging and supporting diversity in PPIE. Patients and the public can bring unique perspectives on the development, implementation, and embedding of AI in health care. Early PPIE is therefore crucial not only to safeguard patients but also to increase the chances of acceptance of AI by the public and the impact AI can make in terms of outcomes.

The integration of Artificial Intelligence (AI) into English as a Foreign Language (EFL) education marks a significant transformation in pedagogical practices, particularly in higher education. In many European countries, such as Germany, Estonia, Finland, and Ukraine, this transformation is accelerating as education systems increasingly adopt AI technologies that replicate human cognitive processes like problem-solving and decision-making. They provide unprecedented opportunities for personalizing language learning based on individual student needs. This study explores current trends, pedagogical models, and empirical findings related to the implementation of AI in EFL classrooms, with particular attention to its impact on the development of language skills, learner autonomy, and affective factors such as motivation and engagement. Within the European context, these issues are especially relevant due to the widespread status of English as a foreign language and the strategic emphasis on digital innovation in national education systems. Drawing on both international and Ukrainian research, the study examines the application of widely used AI tools, such as chatbots, writing assistants, translation platforms, and intelligent tutoring systems, in language teaching. Empirical evidence, including findings from European-based studies, indicates significant improvements in students’ receptive (reading, listening) and productive (speaking, writing) language skills, lexical acquisition, and intercultural competence. Furthermore, AI enhances the affective dimension of learning by boosting motivation, promoting engagement, and alleviating foreign language anxiety through personalized, adaptive feedback and autonomous learning pathways. Despite these benefits, the integration of AI into EFL education is characterized by some challenges, including students’ over-reliance on technology, insufficient digital literacy among users, ethical concerns regarding data privacy, and a lack of comprehensive pedagogical frameworks. The study emphasizes the need for pre-service teacher training programs that effectively incorporate AI competencies. Overall, the study results indicate a positive impact of integrating AI into the teaching of English as a foreign language in European counties (including Ukraine), demonstrating how technological innovations can complement traditional pedagogical approaches to support accessible, effective, and learner-centered foreign language education in the digital era.

This study examines teachers’ perceptions of Artificial Intelligence (AI) integration in education, with a particular focus on its impact on cultural literacy and its contributions to the Sustainable Development Goals (SDGs). The study employs a quantitative descriptive design, involving 25 teachers from SD Islam Prihaswari in East Lombok, Indonesia, who were selected through purposive sampling. Data were collected between July and August 2025 using a Likert-scale questionnaire consisting of 20 items distributed across four dimensions: AI utilization, cultural awareness, contribution to SDGs, and readiness and challenges. Data analysis employed descriptive statistics, including mean scores, standard deviations, percentage indices, 95% confidence intervals, and categorical interpretations. The results indicate an overall positive perception of AI integration in education. The highest mean score was observed in the SDGs dimension (M = 4.90, SD = 0.30, CI95% = 4.78–5.02), while the utilization dimension received the lowest score (M = 4.20, SD = 0.65, CI95% = 4.03–4.37). These findings suggest that teachers recognize AI’s potential to strengthen cultural literacy and support sustainable education, although practical implementation remains constrained by infrastructural and pedagogical limitations. The study highlights the need for improved digital infrastructure, systematic teacher training, and culturally responsive AI-based learning models to ensure meaningful and sustainable integration of AI in education

The rise of artificial intelligence (AI), particularly ChatGPT, has transformed educational landscapes globally. Moreover, the Beijing Consensus on Artificial Intelligence and Education and the ‘Pact for the Future’ propose that AI can support UNESCO in achieving development goals, especially focusing on SDG 4, which emphasizes quality education. Thus, this study investigates undergraduate students’ familiarity with and attitudes toward AI tools, as well as their perceived risks and benefits of using AI tools at a private university in China. An explanatory sequential mixed-method design was employed with an online survey of 167 students, followed by a qualitative analysis of open-ended responses. Data were analyzed using the one-sample Wilcoxon signed-rank test and thematic analysis, supported by SPSS and ATLAS.ti 25. The findings revealed that students demonstrated moderate familiarity with AI tools, particularly ChatGPT and willingness to use them in coursework. Positive attitudes toward AI’s value in education were evident, although concerns such as dependence and reduced independent thinking, algorithmic bias and ethical concerns, accuracy and information quality, data security, and privacy concerns were observed among students. Moreover, students generally viewed AI positively and perceived AI integration as inevitable and becoming common in academic settings. Students were concerned that the misuse of AI by their teachers was minimal and trusted their teachers to use AI effectively in teaching. Students also perceived AI’s benefits, such as personalized learning, efficiency and convenience, career and skill development, and support for independent learning. This study contributes to the discourse on AI integration in higher education by highlighting students’ nuanced perceptions and balancing their benefits with potential risks. The findings of this study were limited by the small sample size and institution. Future research should explore diverse contexts to develop comprehensive AI implementation frameworks for higher education.

Introduction: The integration of Artificial Intelligence (AI) into radiology has shown promise in enhancing diagnostic accuracy and efficiency, yet the confidence of doctors in AI-assisted diagnosis remains uncertain. AI's potential to streamline workflows and detect complex abnormalities is widely acknowledged, but skepticism persists regarding its reliability and the potential disruption of traditional radiological practices. This study aims to assess global doctors' confidence in AI-assisted radiology and explore factors influencing their acceptance of AI technologies. Methods: This descriptive cross-sectional survey involved 384 doctors from diverse clinical settings worldwide. A self-administered questionnaire captured demographic data, confidence in AI versus conventional radiology, and perceptions of AI in clinical practice. Data were analyzed using descriptive statistics. Results: The majority of participants (66.7%) expressed higher confidence in conventional radiologist-led diagnoses compared to AI-assisted interpretations. Confidence in AI tools averaged 5.35/10, with limited AI training (16.9%) and lack of trust (13%) as the primary challenges. Participants with more experience reported greater confidence in interpreting radiographs independently and relied less on radiologists. Common challenges in conventional radiology included delays (35%) and limited access to radiologists (26%). AI was seen as beneficial for routine cases but not yet trusted for complex diagnoses, with only 36.7% believing it will eventually surpass human expertise. Conclusion: Doctors continue to favor conventional radiologist-led diagnostics over AI-assisted tools due to concerns about trust, reliability, and insufficient training. While AI holds potential for improving diagnostic accuracy and reducing time constraints, widespread adoption requires overcoming significant barriers. Radiologists remain crucial in clinical decision-making, and AI will likely serve as a supplementary tool until confidence in its capabilities improves.

This study explores the impact of Artificial Intelligence (AI) in English as a Foreign Language (EFL) learning, aiming to understand how AI influences teacher-student dynamics, the ethical challenges involved, and students' perceptions of AI in the classroom. The research adopts a qualitative ethnographic approach, engaging with 220 students and 58 lecturers from universities in the Jabodetabek region. Data were collected through participant observation, in-depth interviews, and document analysis, focusing on the integration of AI tools such as ChatGPT and Gamma. Thematic analysis was employed to identify key patterns in teacher-student interactions, ethical concerns, and student engagement. Findings indicate that AI enhances student autonomy and learning personalization while reducing the direct communication between teachers and students. Ethical challenges identified include data privacy concerns, the risk of over-dependency on AI, and the potential dehumanization of the learning process. From the student perspective, AI reduces language anxiety and increases engagement through flexible, personalized learning experiences, but some students miss the emotional connection traditionally provided by human teachers. The study concludes that while AI offers significant educational benefits, careful consideration must be given to maintaining ethical standards and human-centered teaching practices. Future research should focus on integrating AI tools that support not only cognitive learning but also emotional and ethical aspects to ensure balanced educational outcomes.

On the relationship between EFL students' attitudes toward artificial intelligence, teachers' immediacy and teacher-student rapport, and their willingness to communicate

As artificial intelligence (AI) integration becomes more prominent in society, the infosphere becomes increasingly complex. A better understanding of the human-AI relationship is crucial during these rapid technological and social changes. Emotions are complex responses of the human mind – a highly advanced information processing system. Thus, examining how humans perceive AI’s emotional capability may provide helpful insights. Human physiological properties such as humanoid appearance and gender are suggested to be potential influencing factors. Following the information processing approach, we employed Bayesian Mindsponge Framework (BMF) analytics on a dataset of 266 residents of the United States. Results show that interacting with an AI agent with human-like physical features is positively associated with the belief in that AI agent’s capability of experiencing emotional pain and pleasure. This effect is stronger in males than females. A possible explanation for these patterns is reliance on cognitive strategies used in interpersonal interactions, including gender-specific physiological properties. This study also demonstrates the effectiveness of using a compatible information processing analytical method such as BMF for studying humans’ perceptions of AI.

The study addresses the impact of artificial intelligence (AI) on the academic performance of students at private universities in Chiclayo, 2025. The research focuses on how AI influences academic decision-making, autonomous learning, and time management. Using a quantitative and descriptive approach, various variables related to students’ perceptions of AI, its ethical use, the integration of AI into learning, and its relationship to academic performance were analysed. The results show that knowledge about AI and its responsible use has a positive correlation with academic performance, highlighting the importance of training students and educators in the use of these technologies. Students who were more willing to learn about AI and its ethics better integrated these tools into their learning process, which improved their performance on exams and projects. In addition, the ability to manage time and meet deadlines is directly related to academic performance.