Influence Of Artificial Intelligence Research Articles

The Influence of Artificial Intelligence (AI) and Mobile Learning on Learning Outcomes in Higher Education: Did the Mediation of Self-Competence Matter?

Islamic Religious Education (PAI) has a significant impact on the development of students' character, morality, and overall learning outcomes. This study aims to investigate the effects of artificial intelligence (AI) and mobile learning on student learning outcomes, with a specific focus on the role of students' self-competence as a mediating factor. Employing a quantitative survey approach, the research included 208 students from the PAI Study Program at IAIN Ponorogo, using probability sampling techniques. Data was collected through Likert-scale questionnaires, and the research data was analyzed using PLS-SEM analysis. The results indicate a positive influence of AI and mobile learning on student learning outcomes, with self-competence playing a crucial role as a mediating factor. These findings highlight the importance of educators promoting self-regulation, self-efficacy, and motivation skills within online learning environments. The study emphasizes the potential of integrating AI and mobile learning to enhance the quality of education and recommends that educators continuously update their knowledge of technological advancements through training and collaboration. Strengthening these competencies can lead to a more interactive, personalized, and adaptive learning environment for students.

Navigating the Evolving Landscape of Teaching and Learning: University Faculty and Staff Perceptions of the Artificial Intelligence-Altered Terrain

This study examines the perspectives of university faculty and staff regarding the influence of artificial intelligence on the higher education teaching and learning landscape following the global launch of free-to-use OpenAI ChatGPT in the autumn of 2022. The participants were 79 university faculty and staff from diverse academic fields across all campuses of a multidisciplinary university in Finland. The data were collected in two phases in May–June 2023 and in March 2024, with focus group interviews and Learning Café discussions. The results showed that AI has a broad impact on teaching and studying in higher education. Six main categories were identified: (1) the impact of AI on students’ learning processes, (2) the impact of AI on teaching, (3) the knowledge required of future employees and the impact of AI on them, (4) ethical and economic issues, (5) the development of AI or its use in the future, and (6) the nature of the change brought about by artificial intelligence. AI is already making inroads into higher education, and participants underscored its dual impact on teaching and learning, highlighting both opportunities and challenges. While teachers recognized AI’s potential to enhance teaching and assessment methods, they also acknowledged the need to adapt their courses accordingly. They expressed concerns about understanding AI’s impact on students’ learning processes and their own contributions to learning assignments. The participants emphasized the necessity of providing support and training for teachers to ensure AI is meaningfully and effectively integrated into teaching and learning practices and landscapes.

Influence of artificial intelligence on organizational leadership: Challenges and opportunities

Influence of artificial intelligence on organizational leadership: Challenges and opportunities

Influence of artificial intelligence on organizational leadership: Challenges and opportunities

Influence of artificial intelligence on organizational leadership: Challenges and opportunities

Impacts of Artificial Intelligence on Carbon Emissions in China, in terms of Artificial Intelligence Type and Regional Differences

The influence of artificial intelligence (AI) on carbon emissions has long been contentious, and accurately clarifying this impact is crucial for the realization of sustainable smart cities. This article investigates the impact of AI on carbon emissions, distinguishing between applied and innovative AI types. Analyzing data from 267 Chinese cities between 2008 and 2019, the study reveals that applied AI reduces carbon dioxide emissions by an average of 40,100 tons per unit increase. In contrast, innovative AI initially leads to emissions increases before ultimately decreasing, illustrating an inverted U-shaped relationship. Regional variations in AI's impact on emissions are influenced by each region's developmental focus and stage of AI deployment. Specifically, differences arise due to the continuous carbon reduction (-0.024) associated with applied AI and the initial emission increase (0.129) attributed to innovative AI. The study underscores the significance of tailored regional strategies in AI development for fostering sustainable smart cities. These findings contribute to the ongoing discourse on AI's environmental impact, offering insights to inform targeted approaches in green, sustainable urban planning.

Rise of Intelligent Machines: Influence of Artificial Intelligence on Mechanical Engineering Innovation

The integration of artificial intelligence (AI) into mechanical engineering has precipitated a profound transformation in the way engineers conceive, design, and execute projects. This paper explores the multifaceted impact of AI on mechanical engineering innovation, elucidating the myriad ways in which intelligent machines are revolutionizing traditional practices and catalyzing unprecedented advancements. In the realm of design, AI algorithms are revolutionizing the conceptualization and optimization processes. By leveraging machine learning and optimization techniques, engineers can explore vast design spaces with unparalleled efficiency, uncovering innovative solutions that might otherwise remain elusive. These AI-driven design tools not only expedite the development cycle but also enable the creation of products and systems with enhanced performance characteristics, such as improved energy efficiency, structural integrity, and functional versatility. Moreover, AI's influence extends beyond the design phase and permeates the entire manufacturing ecosystem. AI-driven automation is reshaping production lines, enabling agile and adaptive manufacturing processes that respond dynamically to changing demands and conditions. Through the integration of sensors, actuators, and AI-powered control systems, factories are becoming increasingly intelligent and autonomous, optimizing resource utilization, minimizing waste, and maximizing throughput.

Influence of Artificial Intelligence on the Future of Psychiatry: Insights from Recent Advancements

Influence of Artificial Intelligence on the Future of Psychiatry: Insights from Recent Advancements

Influence of Artificial Intelligence on Credit Risk Assessment in Banking Sector

Purpose: The aim of the study was to examine the influence of artificial intelligence on credit risk assessment in banking sector. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that AI-driven models demonstrate superior performance in identifying risky borrowers and capturing complex credit risk patterns compared to traditional methods. Additionally, the integration of explainable AI (XAI) techniques has enhanced transparency and interpretability in credit risk assessment processes, facilitating better understanding among stakeholders and improving decision-making transparency. Unique Contribution to Theory, Practice and Policy: Decision theory & technology acceptance model (TAM) may be used to anchor future studies on influence of artificial intelligence on credit risk assessment in banking sector. Continuously invest in research and development to advance the theoretical understanding of AI-driven credit risk assessment models. This includes exploring the integration of machine learning with behavioral economics theories to better predict borrower behavior and default probabilities. Encourage banks to adopt a hybrid approach that combines the strengths of AI-driven models with human expertise. Develop comprehensive regulatory guidelines and standards to govern the use of AI in credit risk assessment and ensure ethical and responsible practices. This includes establishing transparent model validation and governance frameworks to mitigate the risks of algorithmic bias, data privacy violations, and discriminatory lending practices. Regulatory authorities should also promote industry-wide collaboration and knowledge sharing to foster innovation while safeguarding consumer interests and financial stability.

Exploring artificial intelligence and urban pollution emissions: "Speed bump" or "accelerator" for sustainable development?

Within the framework of the overarching green development objective guiding the transformation and progress of urban green and low-carbon initiatives, the technological advancements stemming from artificial intelligence have introduced fresh paradigms for reducing urban pollution and enhancing environmental governance. A comprehensive exploration into the influence of artificial intelligence on urban pollution emissions has emerged as a pivotal current concern. The findings that the progression of artificial intelligence has effectively curbed urban pollution emissions, assuming the role of a significant "speed bump". Robustness testing corroborated this conclusion. Mechanism testing unveiled that the evolution of artificial intelligence mitigates urban pollution emissions by enhancing production efficiency, minimizing energy consumption, boosting green technology innovation, optimizing industrial structure, and increasing public participation. Heterogeneity analysis underscored substantial variances in the impact of artificial intelligence on urban pollution emissions, influenced by pollutant types, regional disparities, and urban scale differentials. Further scrutiny exposed that while the application of artificial intelligence technology does not entirely mitigate the "local-neighborhood" effect, it does ameliorate the "boundary effect", subsequently reducing pollution emission intensity in cities straddling provincial administrative boundaries.

Influence of artificial intelligence on education in modern conditions

Influence of artificial intelligence on education in modern conditions

Impact of Artificial Intelligence on Marketing strategies with reference to MNCs

Artificial intelligence (AI) is rapidly transforming the marketing landscape. This literature-based study explores the diverse applications of AI in marketing functions, drawing insights from academic journals, industry reports, and marketing publications. The study examines how AI personalizes marketing efforts through targeted advertising and content marketing, while also investigating its role in customer relationship management (CRM). It delves deeper into AI's influence on market research and marketing ROI (Return on Investment) optimization. By analyzing these applications, the study aims to provide a comprehensive understanding of how AI is shaping the future of marketing. Keywords: Artificial intelligence (AI), machine learning, customer segmentation, targeted advertising, content personalization, CRM, market research, marketing ROI, chatbots, recommendation engines, customer churn prediction.

Navigating Narrative Frontiers: Influence of Generative AI on Creative Literature

Navigating Narrative Frontiers: Influence of Generative AI on Creative Literature

The Influence of Artificial Intelligence and Digital Technology on ESG Reporting Quality

Environmental, social, and governance (ESG) reporting is crucial for conveying a company's sustainability performance. However, challenges related to standardization, consistency, and data quality persist. This study explores the potential of artificial intelligence (AI) and digital technology to enhance ESG reporting by addressing these challenges. AI and digital technology utilize advanced tools like natural language processing, machine learning, data analytics, and blockchain to streamline data collection, improve quality, and facilitate communication. Regression analysis using A-share listed companies' data from 2012 to 2021 examines the relationship between digital transformation and corporate ESG performance. The research emphasizes the implications of ESG reporting, AI, and digital technology for corporate management, risk assessment, shareholder value, and social responsibility. AI and digital technology are vital for growth, innovation, efficiency, and competitiveness. ESG reporting significantly impacts a company's risk profile, reputation, performance, and overall value, contributing to sustainable development. Through a comprehensive review, methodology exploration, and in-depth analysis, this study provides valuable insights and recommendations for leveraging AI and digital technology in advancing ESG reporting. It concludes that implementing AI and digital technology enhances the comprehensiveness and assurance level of ESG reporting.

The influence of artificial intelligence in higher education based on four thematic axes: a bibliometric study

The article presents a structured bibliometric study examining the impact of artificial intelligence (AI) in higher education across four thematic axes: AI in higher education, AI in education review, AI in the teaching-learning process, and AI tools applied to higher education. Research productivity and impact indicators are analyzed using data from major databases like Scopus, Web of Science, and ScienceDirect. Results reveal a significant increase in AI-related research output, particularly in machine learning, data mining, and learning analytics. The study highlights China and the United States as leading contributors to AI research in higher education. The findings highlight AI's evolving role in transforming higher education and the need for multidisciplinary research approaches to address emerging challenges and opportunities. However, limitations include the reliance on quantitative measures, the narrow temporal scope, and the limited focus on high-production countries. Future research should incorporate qualitative methods to explore practical applications and social impacts more comprehensively, consider a broader range of geographic contexts, and discuss ethical considerations around integrating AI into higher education.

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett's esophagus: a tandem randomized and video trial.

This study evaluated the effect of an artificial intelligence (AI)-based clinical decision support system on the performance and diagnostic confidence of endoscopists in their assessment of Barrett's esophagus (BE). 96 standardized endoscopy videos were assessed by 22 endoscopists with varying degrees of BE experience from 12 centers. Assessment was randomized into two video sets: group A (review first without AI and second with AI) and group B (review first with AI and second without AI). Endoscopists were required to evaluate each video for the presence of Barrett's esophagus-related neoplasia (BERN) and then decide on a spot for a targeted biopsy. After the second assessment, they were allowed to change their clinical decision and confidence level. AI had a stand-alone sensitivity, specificity, and accuracy of 92.2%, 68.9%, and 81.3%, respectively. Without AI, BE experts had an overall sensitivity, specificity, and accuracy of 83.3%, 58.1%, and 71.5%, respectively. With AI, BE nonexperts showed a significant improvement in sensitivity and specificity when videos were assessed a second time with AI (sensitivity 69.8% [95%CI 65.2%-74.2%] to 78.0% [95%CI 74.0%-82.0%]; specificity 67.3% [95%CI 62.5%-72.2%] to 72.7% [95%CI 68.2%-77.3%]). In addition, the diagnostic confidence of BE nonexperts improved significantly with AI. BE nonexperts benefitted significantly from additional AI. BE experts and nonexperts remained significantly below the stand-alone performance of AI, suggesting that there may be other factors influencing endoscopists' decisions to follow or discard AI advice.

The Influence of Artificial Intelligence on the Evolution of Graphic Design: Explore and Predictions for future trends

The Influence of Artificial Intelligence on the Evolution of Graphic Design: Explore and Predictions for future trends

Design of a Computer Technology-Based Teaching System for College Students Mental Health Course

The hypothetical discussion describes the design of a personal computer innovation-based display structure tailored specifically for subordinates enrolled in an educational well-being course. Using a sophisticated approach, this structure intends to raise understudy devotion, urge dynamic studying, and enhance profitability. The displaying framework promotes reflective thinking, resolute thinking, and the acquisition of practical qualities associated with psychological wellness through the use of intuitive multimedia, competitive elements, and tailored input. This innovative displaying structure allows students to grow a more substantial grasp of mental health concerns while growing their personal psychic flourishing in a consistent and enticing teaching environment through the integration of cutting-edge technology with informative content. Modern instructional tactics stay frequently grounded in scheduled exam-based schooling besides infrequently actually caring about the root cause of pupils' questions, although flipping psychological training methods have emerged in some sectors. The primary goal of this concept is to combine digital intelligence with flipping laboratory brain studies. This essay focuses on the characteristics of fraudulent learning as well as the symbolic significance of flipping their house. What exactly are the advantages of the smart display stage over traditional learning? The following piece chooses crucial 1, the classroom, important 2, the school, main 3, the group, and key 4, from our institution's undergraduates. The A1 and B1 groups guide an academic year of artificial intellect, along with the concept of inverted classrooms for neuroscience. Bundles A2 and B2 depict the under study in accordance with normal training. According to the study data, the size of gatherings A1 and B1 increased respectively. Gatherings A1 and B1 had higher midterm and final normal scores respectively, than assemblages A2 and B2, and their scores have increased by a rate. The influence of artificial intelligence and flipping residence mind study on mental health in education programs may additionally energize subordinates' benefit and forward the advancement of understudy's display throughout autonomous education.

Utilizing AI for Social Good: Tackling Global Issues and Fostering Inclusive Solutions

This research delves into the intricate influence of Artificial Intelligence (AI) on community development across vital sectors such as healthcare, education, environmental sustainability, and community empowerment. Its core aim is to comprehensively analyze how individuals in underserved communities perceive and experience the use of AI technologies. To achieve this, a mixed-methods approach is adopted, combining quantitative surveys for statistical insights with qualitative narratives for nuanced perspectives. Engaging 120 participants from diverse backgrounds and age groups, the research methodology incorporates Likert scales and regression analysis for data interpretation. The study reveals a prevalent positive outlook on AI's impact across various domains, particularly highlighting its significant effects on healthcare, education, and environmental sustainability. Integration of qualitative narratives enriches the findings, offering depth and context to statistical analyses. Its novelty lies in the comprehensive examination of AI's influence on community development, seamlessly blending quantitative and qualitative dimensions. By providing nuanced insights into AI's multifaceted role in community contexts, the research significantly contributes to the field. Ultimately, the study underscores the importance of responsible AI deployment, aligned with community values, to navigate the evolving technological landscape and foster sustainable community development.

On the Influence of Artificial Intelligence on Foreign Language Learning and Suggested Learning Strategies

On the Influence of Artificial Intelligence on Foreign Language Learning and Suggested Learning Strategies

Research on the Influence of Artificial Intelligence on the Employment and Its Countermeasures

Artificial intelligence is the main front to build new quality productive forces and is leading the fourth revolution of science and technology of human beings. The wide application of artificial intelligence technology has triggered people's concerns about unemployment. However, we do not have to worry too much. Artificial intelligence technology will not only replace human work, but also create more job opportunities and higher value-added work. It is imperative to conduct special research on labor force training and re-employment for industries and positions that may be replaced by artificial intelligence in the future, and take the initiative to respond in advance and take comprehensive and effective measures as soon as possible, so as to better adapt to the application and development of artificial intelligence technology.