Harnessing AI for sustainable higher education: ethical considerations, operational efficiency, and future directions

Discover Sustainability, Journal Year: 2025, Volume and Issue: 6(1)

Published: Jan. 13, 2025

As higher education faces technological advancement and environmental imperatives, AI becomes a key instrument for revolutionizing instructional methods institutional operations. can improve educational outcomes, resource management, long-term sustainability in education, according to this study. The research uses case studies best practices show how AI-driven innovations minimize impact, enhance energy efficiency, customize learning, creating more sustainable inclusive academic environment. document discusses ethics, including data privacy, algorithmic prejudice, the digital divide. It emphasizes need strong ethical frameworks use ethically make decisions with transparency fairness. study also robust rules infrastructure promote integration, protecting student privacy supporting fair access technologies. shows curriculum-building tools educate students future concerns stimulate innovation. prospects difficulties of are critically examined, its potential change traditional roles, performance, maintain profitability. Actionable recommendations educators, politicians, leaders contribute conversation. Focusing on creates framework where technology stewardship intimately connected, ensuring that institutions prosper fast-changing world.

Language: Английский

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A deep learning-based hybrid PLS-SEM-ANN approach for predicting factors improving AI-driven decision-making proficiency for future leaders

Journal of International Education in Business, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

Purpose This study explores the factors influencing artificial intelligence (AI)-driven decision-making proficiency (AIDP) among management students, focusing on foundational AI knowledge, data literacy, problem-solving, ethical considerations and collaboration skills. The research examines how these competencies enhance self-efficacy engagement, with curriculum design, industry exposure faculty support as moderating factors. aims to provide actionable insights for educational strategies that prepare students AI-driven business environments. Design/methodology/approach adopts a hybrid methodology, integrating partial least squares structural equation modeling (PLS-SEM) neural networks (ANNs), using quantitative collected from 526 across five Indian universities. PLS-SEM model validates linear relationships, while ANN captures nonlinear complexities, complemented by sensitivity analyses deeper insights. Findings results highlight pivotal roles of literacy problem-solving in fostering self-efficacy. Behavioral, cognitive, emotional social engagement significantly influence AIDP. Moderation analysis underscores importance design enhancing efficacy constructs. identifies most critical predictors AIDP, respectively. Research limitations/implications is limited central universities may require contextual adaptation global applications. Future could explore longitudinal impacts AIDP development diverse cultural settings. Practical implications findings designers, policymakers educators integrate into education. Emphasis experiential learning, frameworks interdisciplinary preparing AI-centric landscapes. Social By equipping future leaders proficiency, this contributes societal readiness technological disruptions, promoting sustainable contexts. Originality/value To author’s best uniquely integrates analyze interplay shaping It advances theoretical models linking learning theories practical education strategies, offering comprehensive framework developing students.

Language: Английский

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Advancing SDG 4: Harnessing Generative AI to Transform Learning, Teaching, and Educational Equity in Higher Education

Journal of Lifestyle and SDGs Review, Journal Year: 2025, Volume and Issue: 5(2), P. e03774 - e03774

Published: Jan. 7, 2025

Objective: The objective of this study is to investigate the transformative potential generative AI in advancing Sustainable Development Goal 4 (SDG 4), with aim enhancing equity, accessibility, and quality higher education through integration AI-driven systems practices. Theoretical Framework: This research underpinned by Academic Convergence (AIAC) Framework, which aligns theories such as constructivism, Vygotsky’s cultural-historical theory, Bloom’s Taxonomy. These frameworks provide a solid basis for understanding interplay between personalized learning, cognitive engagement, stakeholder collaboration, ethical governance educational ecosystems. Method: methodology adopted comprises Literature-Driven Conceptual Framework approach, synthesizing peer-reviewed studies across key themes: operational efficiency, collaborative governance. Data collection involved systematic literature reviews scholarly articles, books, conference proceedings within past decade. Results Discussion: results reveal that AIAC promotes tailored, adaptive learning pathways, enhances faculty roles AI-enabled mentors, optimizes administrative workflows predictive analytics. discussion contextualizes these findings existing theories, emphasizing framework's ability mitigate challenges algorithmic bias, equity gaps, data privacy concerns. Limitations include need empirical validation addressing resource disparities underprivileged contexts. Research Implications: practical theoretical implications are significant institutions, policymakers, practitioners. fostering innovative teaching practices, equitable access AI-enhanced tools, aligning strategies labor market demands analytics Originality/Value: contributes introducing an scalable model integrating into education. Its value lies bridging digital divide, lifelong positioning institutions leaders sustainable integration, ultimately mission SDG 4.

Language: Английский

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Artificial Intelligence in Higher Education: Early Perspectives from Lebanese STEM Faculty

TechTrends, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Language: Английский

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Yükseköğretimde Yapay Zekâ: Öğrenci Tutumları ve Akademisyen Görüşleri

İktisadi İdari ve Siyasal Araştırmalar Dergisi, Journal Year: 2025, Volume and Issue: 10(26), P. 132 - 153

Published: Feb. 25, 2025

Bu araştırma, yükseköğretimde yapay zekâ kullanımına ilişkin öğrenci tutumlarını ve akademisyen görüşlerini karma yöntem yaklaşımıyla incelemeyi amaçlamaktadır. Veriler, 400 lisans öğrencisinden anket yoluyla 10 akademisyenle gerçekleştirilen yarı yapılandırılmış görüşmelerle toplanmıştır. Nicel bulgular, öğrencilerin zekâya yönelik olumlu tutum sergilediğini göstermiş, öğrenciler araçlarını kullanmada orta düzeyde yetkinlik bildirmiş bunları öncelikle yaratıcı yazım, görsel oluşturma dil öğrenme amacıyla kullandıklarını belirtmişlerdir. Öğrenciler, kişiselleştirilmiş fırsatları karmaşık konuları daha kolay anlama gibi avantajları vurgularken, eğitimde eşitsizlikler yanlış bilgi riskleri konusunda endişelerini dile getirmişlerdir. Nitel akademisyenlerin teknolojilerine karşı hem de temkinli bir duruş göstermiştir. Akademisyenler, zekânın veri analizi eğitim desteğindeki potansiyelini kabul ederken, temel becerilerin zayıflaması güvenliği konularında endişe duymaktadır. Yükseköğretimde kapsamlı dönüşüm öngören akademisyenler, etkili etik kullanımı için detaylı yaklaşımın gerekliliğini vurgulamaktadır. Araştırma, entegrasyonunun kaçınılmaz olduğu, ancak uygulama kurumsal politika düzenlemelerin gerekli olduğu sonucuna varmaktadır.

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Examining the interaction between artificial intelligence literacy and individual entrepreneurial orientation in teacher candidates: The mediating role of sustainable development

The International Journal of Management Education, Journal Year: 2025, Volume and Issue: 23(2), P. 101156 - 101156

Published: March 4, 2025

Language: Английский

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Perspectives of academic staff on artificial intelligence in higher education: exploring areas of relevance

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

Published: March 26, 2025

Despite the recent increase in research on artificial intelligence education (AIED), studies investigating perspectives of academic staff and implications for future-oriented teaching at higher institutions remain scarce. This exploratory study provides initial insight into 112 by focusing three aspects considered relevant sustainable, age AI: instructional design, domain specificity, ethics. The results indicate that participants placed greatest importance AIED Furthermore, indicated a strong interest (mandatory) professional development AI more comprehensive institutional support. Faculty who perceived design as important were likely to use AI-based tools their practice. However, relevance specificity ethics did not predict tool integration, which suggests an intention–behavior gap warrants further investigation factors such literacy structural conditions education. findings may serve basis discussion adequate support services learning AI.

Language: Английский

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Analysis of influencing factors on teachers' AI literacy under the SOR framework: An empirical study based on PLS-SEM and fsQCA

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: March 31, 2025

Language: Английский

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Modeling the influence of AI dependence to research productivity among STEM undergraduate students: case of a state university in the Philippines

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

Published: April 16, 2025

STEM fields—Science, Technology, Engineering, and Mathematics—play crucial roles in advancing knowledge, driving innovation, addressing challenges by means of several mechanisms including research. Consequently, curricula higher education institutions prepare undergraduate students taking these fields to engage produce quality research outputs preparation for their future careers or roles. The advent educational resources help perform research-related tasks artificial intelligence. Although AI use is viewed as inappropriate doing scholarly works due concerns about academic integrity the fear losing essential cognitive skills, growing dependence among inevitable. In this regard, present study seeks empirically investigate influence toward students’ productivity, mediating disposition, self-efficacy. Through literature review, a structural model was proposed validated. Initially, instrument developed reflective constructs where items were also generated using review. Eventually, an online survey conducted recorded 834 valid responses from students. Results revealed that seven hypotheses model, six are supported except causal path between productivity. paths dispositions, self-efficacy well three This indicates mediation linking findings imply strategic integration may foster not only skills development but motivation confidence, which together could enhance overall productivity fields.

Language: Английский

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Exploring faculty perceptions and concerns regarding artificial intelligence Chatbots in nursing education: potential benefits and limitations

BMC Nursing, Journal Year: 2025, Volume and Issue: 24(1)

Published: April 18, 2025

To examine faculty perceptions of artificial intelligence (AI) chatbots in nursing education, focusing on their usage patterns, perceived benefits, and limitations. A cross-sectional study. The study surveyed from Jordan the United States using a self-reported questionnaire. Data were analyzed descriptive statistics Multivariate Analysis Covariance to assess variations based AI chatbot frequency characteristics. Among 474 members, 82.5% familiar with at least one chatbot. Faculty generally acknowledged benefits chatbots, including enhanced teaching experiences, improved student engagement, support for independent learning, quick access medical knowledge. However, concerns about misinformation, reduced faculty-student interaction, inadequacies addressing complex clinical scenarios prevalent. Legal ethical issues, particularly risk misuse AI-generated information, also highlighted. Frequent users demonstrated significantly greater awareness both advantages limitations compared infrequent users. challenges highlighting role hands-on experience shaping adoption. adoption is primarily driven by rather than limitations, emphasizing need showcase practical while concerns. enhance institutions should focus demonstrating through targeted training guidelines. Providing structured exposure can increase confidence, reinforcing usefulness strategies mitigate Future research may effectiveness programs behaviors, providing valuable insights enhancing integration education.

Language: Английский

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