Navigating the integration of generative artificial intelligence in higher education: Opportunities, challenges, and strategies for fostering ethical learning

Deleted Journal, Journal Year: 2025, Volume and Issue: 4(1), P. 1 - 2

Published: Jan. 1, 2025

Language: Английский

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Artificial intelligence in higher education institutions: review of innovations, opportunities and challenges

Frontiers in Education, Journal Year: 2025, Volume and Issue: 10

Published: March 3, 2025

Artificial intelligence is revolutionizing industries including institutions of higher learning as it enhances teaching and processes, streamline administrative tasks drive innovations. Despite the unprecedented opportunities, AI tools if not used correctly, can be challenging in education institutions. The purpose this study was to comprehensively review innovations, opportunities challenges associated with use Education learning. A systematic literature methodology adopted locate select existing studies, analyze synthesize evidence arrive at clear conclusion about current debate area study. Following PRISMA, analyzed a total 54 documents that met inclusion exclusion criteria set for selection documents. unveiled many enhanced research capabilities, automation among others. Intelligence are found refine different units include ethical concerns, integrity issues data fabrication issues. With notwithstanding, benefits cannot over emphasized. remains powerful tool research, tasked, personalized learning, inclusivity accessibility educational content all. Emphasis should put regulatory frameworks detailing how such while maintaining level standards required.

Language: Английский

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Examining predictors of generative-AI acceptance and usage in academic research: a sequential mixed-methods approach

Benchmarking An International Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

Purpose This research uses a mixed-methods approach to identify predictors of Generative artificial intelligence (Gen-AI) adoption and usage among academics educational researchers. It examines drivers barriers based on the diffusion innovation theory (DIT) planned behaviour (TPB). Design/methodology/approach A qualitative investigation was carried out by conducting interviews academic researchers who used Gen-AI tools such as ChatGPT. Based DIT, TPB analysis results, an integrated model proposed tested using survey data collected from analysed partial least squares-structural equation modelling (PLS-SEM). Findings The study demonstrated that relative advantages observability influence attitude subjective norms, these in turn impact behavioural intentions. Researchers' perception advantage their intentions use were found lead positive behaviours. However, technical limitations ethical concerns acted key moderators between intention norms intention, respectively. Mediation effects also observed. Research limitations/implications utilised DIT its base models, future could incorporate additional constructs other technology theories. concentrated had subsequently reported significant factors affecting usage. Future studies should consider perspective non-users tools. Further, geographical focus India, broaden scope. Practical implications community must unite develop guidelines for plagiarism research. be emphasising importance highlights need establishing standards, comprehensive transparently within framework. Originality/value results can greatly enhance understanding researchers, particularly light about integrity potential negative consequences

Language: Английский

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Digitale Lernmethoden in der Pharmazie

Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

With the outbreak of SARS-CoV‑2 pandemic in March 2020 and associated restrictions on teaching, digital learning methods were increasingly used at many universities. Digital generally include fully or partially digitized elements such as lecture recordings, open materials, e‑portfolios. Fully formats game-based learning, inverted classroom, mobile use social media, online peer collaborative adaptive learning. Digitized realities are created context simulation-based augmented virtual reality. Online-based event degree programs characterized by an almost exclusive proportion internet-based phases.The extent to which pharmacy courses Germany is explained this article using selected practical examples. The examples creation audio podcast assess performance a clinical chemistry internship form element, analysis tool carry out medication analyses example blended concept teach basics pharmacy, bedside game-like simulation for dispensing medicines. inclusion artificial intelligence can be helpful development implementation offerings. However, sufficiently high quality critical approach must guaranteed.

Language: Английский

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Artificial Intelligence-Aided Next Generation Cloud Computing Networks

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 285 - 306

Published: Jan. 17, 2025

Next-generation wireless networks (NGWNs) are extremely dynamic due to the integration of communications at different scales. (NGNs) high-speed communication network that enables many services such as packet based seamless transmission data and information. The emergence artificial intelligence (AI) helped NGNs overcome their existing issues by enabling automated management real-time optimization. AI can address next-generation challenges enhancing security through intelligent threat detection, improving scalability via resource management, reducing latency with predictive analytics. paper presents various aspects discusses most potential techniques. Further, this highlights next generation how solve problems in NGNs. Finally, some recent advancement regards techniques being used specifically machine learning, deep fuzzy logic, rule modelling natural language processing.

Language: Английский

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TEIA colaborativa Brasil-Inglaterra: promovendo intercâmbio virtual, internacionalização e aprendizado em IA Generativa em cursos de computação

Published: April 7, 2025

Neste trabalho é apresentada uma experiência piloto de colaboração internacional promovendo o intercâmbio virtual entre alunos graduação e pós-graduação em computação, envolvendo tema transversal grande importância, arcabouço IA Generativa, para atrair múltiplos interesses áreas da computação propiciar forma rica, barata acessível internacionalização, celebrando um acordo cooperação universidades do Brasil Inglaterra: a Universidade Federal Amazonas Manchester. Os exercitaram habilidades equipe, atividades colaborativas coleta recursos, entendimento conteúdos, manipulação ferramentas desenvolvimento projeto, se comunicando inglês. Ao mesmo tempo, Generativa foi explorada cenários aplicação diversos, culminando pequenos projetos conjuntos. resultados, tanto interação quanto dos artefatos gerados durante após matéria, mostraram valiosos validar proposição disciplina maior escala na compreensão das ricas possibilidades, baixo custo necessidade poucos que proposta (virtual) internacionalização como esta pode promover.

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The Effectiveness of Local Fine-Tuned LLMs: Assessment of the Japanese National Examination for Pharmacists

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 15, 2025

Large Language Models (LLMs) offer great potential for applications in healthcare and pharmaceutical fields. While cloud-based implementations are commonly used, they present challenges related to privacy cost. This study examined the performance of locally executable LLMs on Japanese National Examination Pharmacists (JNEP). Additionally, we explore feasibility creating specialized pharmacy models through fine-tuning with Low-Rank Adaptation (LoRA). Text-based questions from 97th 109th JNEP were utilized, comprising 2,421 training 165 testing. Four distinct evaluated, including Microsoft phi-4 DeepSeek R1 Distill Qwen series. Baseline was initially assessed, followed by using LoRA dataset. Model evaluated based accuracy scores achieved test In baseline evaluation against JNEP, ranged 55.15–76.36%. Notably, CyberAgent 32B passing threshold (approximately 61%). Following fine-tuning, exhibited a increase 60.61–66.06%. showed that capable handling knowledge tasks comparable those national pharmacist examination. Moreover, found techniques like can significantly enhance model performance, demonstrating robust AI specifically designed pharmacological applications. These findings contribute understanding implementing secure high-performing solutions tailored use.

Language: Английский

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Evaluation of False, Reductionist Part-Whole Relationships in Biochemistry and Its Effect on Health Science Students’ Chemistry-Based Health Literacy

Science & Education, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Language: Английский

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Exploring Generative Artificial Intelligence to Enhance Reflective Writing in Pharmacy Education

American Journal of Pharmaceutical Education, Journal Year: 2025, Volume and Issue: unknown, P. 101416 - 101416

Published: April 1, 2025

The integration of generative artificial intelligence (AI) holds potential to impact teaching and learning. In this commentary, we explore the opportunity for AI enhance RW among pharmacy students. AI-guided has strengthen students' reflective capacity, deepen their autobiographical memory, develop self-confidence. This commentary presents examples how can be utilized enrich includes a sample prompt aimed at facilitating student self-reflection. We integrating AI-facilitated assignments into curriculum help students detailed self-reflection gain exposure uses in professional development career advancement.

Language: Английский

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Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination

BMC Medical Education, Journal Year: 2025, Volume and Issue: 25(1)

Published: May 1, 2025

Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements artificial intelligence (AI) offer opportunities complement human evaluations. This study aims explore the consistency between AI evaluators assessing skills during OSCE. cross-sectional was conducted at a state university Turkey, focusing on pre-clinical students (Years 1, 2, 3). Four skills-intramuscular injection, square knot tying, basic life support, urinary catheterization-were evaluated OSCE end of 2023-2024 academic year. Video recordings performances were assessed by five evaluators: real-time assessor, two video-based expert assessors, AI-based systems (ChatGPT-4o Gemini Flash 1.5). The evaluations based standardized checklists validated university. Data collected from 196 students, with sample sizes ranging 43 58 for each skill. Consistency among analyzed using statistical methods. models consistently assigned higher scores than across all For intramuscular mean total score given 28.23, while averaged 25.25. 16.07 versus 10.44 humans. In 17.05 16.48 catheterization, similar (AI: 26.68; humans: 27.02), but showed considerable variance individual criteria. Inter-rater visually observable steps, auditory tasks led greater discrepancies evaluators. shows promise as supplemental tool evaluation, especially However, its reliability varies depending perceptual demands skill being assessed. more uniform suggest potential standardization, yet refinement is needed accurate assessment requiring verbal communication or cues.

Language: Английский

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