Introduction Of Artificial Intelligence Research Articles

Validation of the Teachers AI-TPACK Scale for the Indian Educational Setting

Educators work in extremely dynamic and complex classroom environments where they must continuously alter and update their understanding. Specifically, possession of rich, organised, and integrated knowledge from various domains including knowledge on subject-matter, knowledge of students' thinking and learning, and, increasingly, knowledge of technology is essential. By integrating these three aspects, Mishra and Koehler developed the Technological Pedagogical and Content Knowledge (TPACK) framework in 2006 which offers a thorough and comprehensive method for incorporating technology into the education setting. On the parallel, use of information technology has rapidly increased in the field of education, especially with the introduction of Artificial Intelligence (AI). Thus, the Technological Pedagogical Content Knowledge (TPACK) framework needed to be updated to reflect the growing incorporation of AI into educational standards. Hence, investigator Ning and colleagues in the year 2024 built a framework for incorporating AI into TPACK and developed a robust scale titled Teachers AI-TPACK Scale that measures the teachers competencies in incorporating AI into their teaching environment. The objective of this work was to test the validity of the scale in the Indian educational setting. With a sample size of 660 teaching faculties in universities and colleges across India, this study followed the routine stages such as construct validity analysis in the form of Exploratory Factor Analysis using SPSS V27, followed by Confirmatory Factor Analysis in AMOS software. The original scale with 39 items across seven dimensions were retained throughout the validation process and resulted in a high reliability score of 0.907. This provides compelling evidence for the validity and reliability of the teachers AI-TPACK scale in measuring Indian educators' knowledge and skills at the juncture of AI with pedagogy, technology and content. This is currently the only scale available to measure this construct in India.

What is the machine? Teachers’ professional learning about generative artificial intelligence as tutors for children

ABSTRACT With the introduction of artificial intelligence (AI), particularly Generative AI (GenAI) to school settings, teachers are likely to be drawn into professional learning scenarios where they will be expected to learn how to use programs and applications for remediation and tutoring of children. Previous research highlights how professional learning for teachers about GenAI has been focused on gaining their acquiescence to using GenAI by arguing that it is both superior and inescapable. This critical posthuman work uses a professional learning scenario to ask questions about the historically present challenges of asking teachers to use GenAI as a universal good when this discourse has been used to colonise and imperialise in schools, particularly with technologies. Our critical posthuman diffractive reading revealed alternative encounters that teachers and students could have with GenAI and reasonable pathways for avoiding it. Implications of this work include a need to draw on the diffractive encounters presented here to understand and address who and what the machine is when it comes to adopting advanced technologies for various purposes in schools.

Human resources management in the age of artificial intelligence

Today's businesses are operating in a complex environment, marked by the emergence of a digital culture that is transforming space and time, as well as relationships at work. These various transformations have given rise to a new concept: artificial intelligence. With the introduction of artificial intelligence, work is being transformed, creating new challenges for organizations and leading to new HR practices in terms of recruitment, training, compensation, talent management and so on.For all these reasons, the mobilization of collective intelligence is ultimately becoming a priority for HR, insofar as it makes it possible to support transformation within organizations by means of agile methods. Against this backdrop of changing organizational practices, a number of questions arise:-What is artificial intelligence and how does it impact organizations? -What role can collective intelligence and artificial intelligence play in the evolution of the HR function?The aim of this theoretical research is to underpin the various concepts linked to these notions. We will also try to understand what is at stake in collective intelligence for HR, and how artificial intelligence can impact organizational practices.

Artificial intelligence in the diagnostics and treatment of inflammatory bowel diseases (review)

Currently scientists from different countries are exploring the possibilities of using machine learning methods to improve the accuracy of endoscopic and radiation diagnostics in patients with inflammatory bowel diseases (IBD) both to reduce the time spent by doctors on describing the results and to reduce the time needed to verify the diagnosis. Predicting the course of IBD based on artificial intelligence (AI) with the creation of predictive scenarios (models) is another promising area in gastroenterology. This review analyzes the main directions of scientific projects on the introduction of AI and machine learning methods in the diagnosis and prediction of the course of IBD. The article pays special attention to the problems faced by specialists in the application of AI methods, ways to solve them, as well as the prospects for using AI in patients with IBD. The possibilities of using AI for colorectal cancer screening and analysis of medical records are presented.

ARTIFICIAL INTELLIGENCE TECHNOLOGIES AND SOLVING SOCIAL PROBLEMS

The use of modern digital technologies, such as paperless document management, automated information systems, blockchain, big data, artificial intelligence (AI), etc., allows you to create high-performance decision-making systems. In the course of the development of modern information technologies, intensive digitalization is taking place in almost all spheres of human activity and the introduction of artificial intelligence, which affects social problems within society. In addition to the obvious advantages of using human intelligence in the new digital world, there may be various situations, primarily related to the digital society and the management decision-making process. Social problems are investigated using artificial intelligence technologies in a digital society. The article discusses the main aspects of social problems related to artificial intelligence technologies, in addition, in order to solve social problems and identify semantic features of the knowledge base, an algorithm has been developed that provides a clear picture of social aspects in the process of filling in the database, taking into account the purpose of forming a thesaurus for a system of questions and answers.

Artificial Intelligence in Higher Education: Bridging the Gap for Students with Disabilities

Students with disabilities experience (SWDS) difficulties in learning due to limitations placed on them by their defect. To meet their learning needs distinguishing educational provisions from regular education were introduced into educational system which consist of special teachers and modification of curriculum, instructional procedures, methodology, instructional materials and learning environment contingent on category and magnitude of disabilities. Similarly, given that learning has to be effective; inclusive education in regular educational institutions was introduced. Nevertheless, while those who cannot benefit from inclusive education due to the severity of their handicap; provisions were made to accommodate them in special classes and special schools. These provisions are indeed beneficial to SWDs. However, introduction of Artificial Intelligence (AI) in tertiary institutions personalizes and has been found to enhance learning for SWDs. Moreover, its use is not without challenges which need to be addressed to enable them benefit maximally from this novel and unique technology. This paper, therefore, through evaluative and prescriptive methodology using google search on the theme, concepts and keywords examines the type of AI technologies used by SWDs in higher education, benefits and challenges. Finally, the paper offers some suggestions on overcoming these challenges to enable SWDs benefit maximally from the usage.

Examination of AI Enhanced Distributed Systems and its Effects on Software Engineering

Distributed systems are groups of independent computers that appear to the system's users as a single coherent system. These systems involve several critical factors, including network communication, concurrency, and fault tolerance, which are vital in software engineering. For example, cloud computing platforms like Amazon Web Services (AWS) use distributed systems to offer scalable, on-demand resources to millions of users worldwide. The introduction of Artificial Intelligence (AI) into software engineering marks a transformative period that reshapes traditional development processes and breaks down the complexity of distributed systems. AI automates routine tasks and simplifies complex processes, serving as a digital collaborator that enables developers to focus on strategic thinking and creativity. One significant advantage of using AI in distributed systems within software engineering is enhanced resource optimization. AI can identify irregularities that might indicate hardware malfunctions and take preventative measures to address them, such as rerouting traffic to healthier servers. However, distributed systems also have challenges, including increased complexity in system design, difficulty ensuring data consistency, and potential security vulnerabilities. The intricate structure of these systems can result in problems with high startup costs, safety risks, and the accuracy of the data provided. Integrating AI into distributed systems offers both significant advantages and disadvantages. This study evaluates how AI impacts the efficiency and security of distributed systems in software engineering. By analyzing the advantages and disadvantages of AI-enhanced distributed systems, we can gain a comprehensive understanding of their overall effectiveness and implications in the field.

Digital Technology in Healthcare—An Ethical Overview

This overview of ethical aspects of artificial intelligence (AI) in healthcare is organized according to major types of medical activities. It discusses important ethical problems in (1) diagnostic uses of AI such as image interpretation and text interpretation, (2) the use of AI as decision support or even as decision-maker, (3) its use for treatment, for instance in robotic surgery, exoskeletons, virtual psychotherapy and therapeutic robots (care robots), and (4) the use of AI for healthcare documentation and communication. Summing up, we emphasize two major challenges in the introduction of AI that should concern not only healthcare professionals but also higher level decision-makers such as politicians and hospital directors. The first of these is the need to retain human contacts between patients and healthcare, in particular contacts that are conducive to patient health and well-being. The second is the need to ensure that the introduction of AI in healthcare does not create or exacerbate injustices in healthcare. This can happen if prevalent human biases are encoded in AI tools. It can also occur if people with less money have to use inexpensive AI tools such as virtual psychotherapists whereas the well-to-do have access to a human psychotherapist. On the other hand, AI tools can be used to provide better healthcare to all who need it, and they can also be programmed to avoid biases and other mistakes that humans are prone to. The article concludes with brief summaries of the articles in the special issue on AI in healthcare that it introduces.

Multifunctional microwave absorption materials: construction strategies and functional applications.

The widespread adoption of wireless communication technology, especially with the introduction of artificial intelligence and the Internet of Things, has greatly improved our quality of life. However, this progress has led to increased electromagnetic (EM) interference and pollution issues. The development of advanced microwave absorbing materials (MAMs) is one of the most feasible solutions to solve these problems, and has therefore received widespread attention. However, MAMs still face many limitations in practical applications and are not yet widely used. This paper presents a comprehensive review of the current status and future prospects of MAMs, and identifies the various challenges from practical application scenarios. Furthermore, strategies and principles for the construction of multifunctional MAMs are discussed in order to address the possible problems that are faced. This article also presents the potential applications of MAMs in other fields including environmental science, energy conversion, and medicine. Finally, an analysis of the potential outcomes and future challenges of multifunctional MAMs are presented.

Exploring the Integration of Artificial Intelligence into Special Education Teacher Preparation through the TPACK Framework

With the introduction of artificial intelligence (AI), specifically generative AI and large language models (e.g., ChatGPT, Google Gemini), into education, there is a conversation regarding what knowledge teachers still need and will need moving forward. In this article, we describe how AI can, and should, be aligned to the Technological Knowledge, Pedagogical Knowledge, and Content Knowledge (TPACK) framework, as a part of special education teacher preparation. Additionally, we explore the implications of AI on the TPACK framework, specifically how AI can be integrated within each of the three components, specific tools that support each aspect, and guiding questions that teacher-educators and pre-service teachers should be using when considering AI. We will provide teacher-educators with example activities they can use with their pre-service teachers to introduce AI and integrate its use within their curriculum, framed within the TPACK.

ВНЕДРЕНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ПРАКТИКУ ВЫСШЕЙ ШКОЛЫ

The article provides an analysis of domestic and foreign publications on the use of artificial intelligence in higher education. The question of the possibility of using artificial intelligence technologies in higher education is raised. The possibilities and risks associated with the introduction of artificial intelligence into the educational process are noted. Among the main threats to the education system are issues related to the ethical use of technology, academic dishonesty on the part of students, a decrease in their motivation, ability to reason, and the emergence of intellectual laziness. The results of surveys of teachers and students devoted to the study of attitudes towards the possibilities of using new technologies in the learning process are presented. Students tend to have a more positive assessment of the use of artificial intelligence in higher education, while concerns, skepticism and fear are noted on the part of the teaching staff. Teachers assess their knowledge and skills in the field of artificial intelligence as insufficient and are ready to improve their skills in this area. The ambiguous attitude of the university administration to the use of artificial intelligence in writing scientific and diploma projects is shown, from a categorical ban on the use of these technologies to experiments on the best application in the form of competitions with incentives for students.

Educational Application of Artificial Intelligence for Diagnosing the State of Railway Tracks

The aim of the work is to present an innovative solution based on artificial intelligence for examining the condition of railway tracks in real time. The system, based on fuzzy logic and metaheuristics such as Fuzzy Logic, Neural Networks and Bee Behavior Optimization, combines hardware and software to provide reliable data on the technical characteristics of the railway. Installed in rail vehicles, hardware collects this data, while software uses artificial intelligence to improve operational reliability and safety. The aforementioned technology is not only useful for infrastructure diagnostics, but also for urban railways such as trams and metros, ensuring a high level of passenger safety. The introduction of artificial intelligence in the railway sector is a key step towards modernisation, improving efficiency, resource optimization and safety. Although still in its infancy, artificial intelligence already shows great potential in transforming the railway sector towards a more efficient, reliable and sustainable future.

ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ В ИСКУССТВЕ. ТВОРЧЕСТВО В ЭПОХУ ИСКУССТВЕННОГО РАЗУМА

The article examines the impact of the development of artificial intelligence technology on art in general. The author describes the principles of image generation using neural networks, citing as examples only a few popular neural technology services, trying to explain in simple words the principle of operation of the image generation algorithm. Innovative artificial intelligence technologies are considered that allow you to independently create copies of artistic designs. Both the characteristic features and disadvantages of digital art, its development in the field of art and the introduction of artificial intelligence into creative practices are analyzed. The relevance of new neural creativity and the creation of artistic works using artificial intelligence are discussed. The technological skills of artificial intelligence in the person of the artist are considered, giving birth to a new era of art, creating their masterpieces differently.This scientific article required the study of both a large amount of literary material and electronic Internet resources, as a result of which the main types of graphic editors, their advantages and disadvantages were studied.

Цифровизация преподавательской деятельности: роль искусственного интеллекта в высшей школе

Digitalization of education is one of the key processes of transformation of modern society, which allows to upgrade the outdated structure of education and introduce new technologies that can improve the quality of the final result and make education more accessible. The introduction of artificial intelligence (AI) in the academic process of higher education helps to simplify and systematize the learning process. Thanks to AI, educational programs become more personalized and the process of analyzing and predicting learning is facilitated. The article investigates the role and impact of AI on teaching activity in higher education institutions in the context of digitalization of education, as well as identifies the positive and negative aspects associated with the introduction of AI in the educational process of higher education. The results of the study showed that it is necessary to conduct intensive retraining of university teaching staff aimed at their mastery of AI. Additionally, the training of students in pedagogical fields should be based on their advanced mastery of modern digital educational technologies, including those related to AI.

The Metaphor of AI in Writing in English: A Reflection on EFL Learners’ Motivation to Write, Enjoyment of Writing, Academic Buoyancy, and Academic Success in Writing

Several barriers hinder students from producing clear and impactful written work. Writing assignments are often given on an individual basis, similar to homework, and without any assistance. Students in a classroom context have access to both their classmates and the teacher while they are working in groups or pairs as part of their assignments. The majority of students, however, are clueless about how to begin their homework assignments. The introduction of artificial intelligence in education may help solve this problem. The current research intended to demonstrate the effects of employing automated writing evaluation (AWE) in fostering learners’ writing skills, motivation to write, enjoyment of writing, and academic buoyancy in open and distributed English as a foreign language (EFL) learning. The participants were 86 intermediate EFL students from China. The participants in the experimental group (n = 44) received instruction and feedback from their teachers only; participants in the control group (n = 42) were exposed to their teachers’ instruction as well as AWE. The results of data analysis via one-way multivariate analysis of variance indicated that the participants in the experimental group outperformed their peers in the control group in motivation to write, enjoyment in writing, academic buoyancy, and academic success in writing. Further in-depth discussions proceed regarding the implications of the study.

Artificial Intelligence System for Automated Breast Cancer Detection in Pathology in Burkina Faso: Methodology Overview.

The introduction of artificial intelligence (AI) in breast cancer diagnosis in Burkina Faso represents a significant advancement in the field of healthcare. Faced with the public health issue posed by breast cancer, this study focuses on the use of AI to improve early and accurate detection of this disease from histopathological images. For the implementation of the system, we utilized a customized architecture tailored to our context where image quality is low, based on the convolutional neural networks algorithm from the Keras library of TensorFlow. Subsequently, we developed a platform to facilitate its use. This article aims to present the methodology that was used and the results obtained.

Transesophageal echocardiography: Revolutionizing perioperative cardiac care.

Cardiovascular diseases (CVDs) are a major challenge in global health. Despite significant advances in treatment and management, the incidence and mortality rates of CVDs have been rising in recent years, particularly in the United States. With continuous advancements in medical technology, perioperative transesophageal echocardiography (TEE) has become a key technology in cardiac surgery, enhancing surgical success rates and patient safety. The application of TEE spans preoperative planning, intraoperative monitoring, and postoperative evaluation, especially in complex procedures such as mitral valve repair and aortic valve replacement, where it plays an indispensable role. Simultaneously, the introduction of artificial intelligence (AI) brings new prospects for TEE image analysis and diagnostic support, significantly improving diagnostic accuracy and real-time decision-making capabilities. However, the application of TEE technology faces challenges such as high costs, uneven technological diffusion, and the high skill requirements for medical personnel. Therefore, establishing standardized training protocols and strengthening multidisciplinary collaboration are crucial. This paper reviews the application of TEE in cardiac surgery and its path toward educational and practical standardization from a global perspective, emphasizing its importance in improving the postoperative quality of life for patients and exploring future directions in technological innovation and educational optimization.

Enhancing academic integrity among students in GenAI Era:A holistic framework

The introduction of Artificial Intelligence (AI), specifically Generative AI (GenAI), has significantly transformed the higher education landscape. Despite the opportunities GenAI offers to students, they pose significant challenges for academic integrity. Thus, it is crucial for higher education institutions (HEI) to balance the use of GenAI for enhancing the learning experience of students with its ethical and responsible use in their educational journey. The present study proposes a comprehensive academic integrity framework focusing on three key stakeholders: students, educators, and institutions. We propose eight strategies ranging from collaborative learning for students to developing a comprehensive GenAI policy for institutions in maintaining academic integrity among students in HEI. Furthermore, we identified four challenges, namely financial, strategic, operational, and cultural, in the implementing a comprehensive academic integrity framework in the GenAI era. This study offers significant insights for HEI to maintain academic integrity among students in the GenAI era.

Technology Innovation Is the Key to Triumph for the Glaring Future of the Fashion Industry

Over the last decade, the fashion industry has been at the forefront of the latest technology. From the introduction of sewing machines for stitching fashion products to biodegradable fabrics to fashion renting apps to needle-free sewing, the fashion industry has seen a lot of changes over the last few years. Evolution in fashion begins with the introduction of artificial intelligence. Technology in fashion is at its profuse self in the current sphere. Technology comprises Artificial intelligence that is enhancing the production capacity of the fashion manufacturing industry, secondly, it comprises Augmented reality which positively boosts the customers' shopping experience and lastly, the virtual outlook increases the remunerative economy in the fashion industry. When one thinks of evolution, artificial intelligence is the latest introduction to the world of technology. Technology in fashion has never been more abundant than it is now. Artificial intelligence is optimizing vast production lines, augmented reality is enhancing the customer experience, and the virtual world is creating lucrative new revenue streams [1]. In the fashion industry, one of the most observable transposes is due to e-commerce. The convenience of online shopping is becoming very appreciated. Fashion companies have started incorporating innovative digital ways to reach their targeted audience. The advanced technologies include virtual fitting rooms which help customers in making more spontaneous decisions in their purchase as they can preview the product and exactly see how that product looks on their body type [2]. Artificial intelligence is used in the design process in a fashion that makes it much easier, like using AI to resize a garment digitally without actually making the garment, digitally changing the color, and also AI can create a visual background to give the buyer the precise judgment about the overall look of the garment. This saves time and resources, which in turn helps in reaching a wider range of customers [3] Another evolution with technology is the introduction of 3d printing and robotics, which cannot accelerate the rate of production. Design software, computerized laser-cutting machines, and digital pattern-making are some of the new manufacturing techniques in the fashion industry.

Artificial Intelligence In The Central Bank: Benefits And Risks Of Public Administration

The article analyzes the benefits and risks of using artificial intelligence (AI) in the public administration of central banks. Using the method of discourse analysis, the advantages and risks of introducing AI into the activities of central banks are investigated. The author also considers the Concept of Artificial Intelligence Development in Ukraine, approved by the Resolution of the Cabinet of Ministers of Ukraine № 1156-r dated 02.12.2020, which defines the priority areas of AI development and the areas to which this initiative is directed. Using AI in central banks can help improve the analysis of large amounts of data, which in turn will help forecast economic trends and manage financial risks. One of the main advantages is the ability to automate routine processes, allowing employees to focus on strategic tasks. An important aspect is the collection of microeconomic and non-economic data from various sources, including the Internet. In addition, AI provides the ability to use synthetic data, which expands the possibilities for analysis. However, the use of AI also carries significant risks. These include problems with data privacy, the risk of false conclusions based on synthetic data, the impact of built-in biases in AI models, and the difficulty of explaining policy decisions. Cybersecurity is a separate issue, as the introduction of AI makes systems more vulnerable to cyberattacks. AI is expected to be increasingly integrated into key functions of central banks, including monetary policy-making and financial risk management. This will allow central banks to make more informed decisions and increase the efficiency of their operations. In addition, the introduction of AI will facilitate the development of information technology and improve analytical capabilities, which will ultimately reduce the workload of employees. At the same time, an important part of the analysis is the impact of AI on the transformation of modern approaches to public administration, especially in the context of the digitalization of the economy. AI can change traditional management methods by offering new tools for decision-making, but it also requires more careful regulation to avoid negative consequences. Therefore, a balanced implementation of these technologies is needed, taking into account potential risks and benefits. This study is a step in understanding how artificial intelligence can change the role of central banks in the modern economy, and how regulatory approaches need to be adapted to ensure the safe and effective implementation of these technologies.