Empowering Introvert Students: How Artificial Intelligence Applications Enhance Speaking Ability

This paper aims to examine the differences abilities between extrovert and introvert personality in learning English. This study describes the differences in the ability of speaking, writing, listening and reading. The approach used in this study is a qualitative approach. Data were obtained by conducting observations and interviews with research subjects. The subjects of this study were students of the third semester of English Education at IAIN Pekalongan. The analysis in this study uses a descriptive analysis related to the differences in English skills in extroverts and introverts. The results showed that the differences between extroverted and introverted personalities on the ability to learn English. In speaking skills, extroverted students are more mastery than introverted students. While writing, listening, and reading skills introverted students are more mastered. But in the aspect of pronunciation accent, extroverts' vocabulary and fluency are superior than introverts. Introverts good in grammar, and comprehension. On the other hand, introverts have superior writing skills in terms of vocabulary, content, and expression. whereas extroverts only excel in terms of content and expression. The spelling and grammar is not influenced by the personality.Therefore each personality have own skills or advantages and disadvantages.

The advancement of artificial intelligence, which has remarkable applications in numerous industries, is a key area of worldwide science and technology development. Among them, the application of artificial intelligence in new drug research and development and auxiliary disease diagnosis has made such outstanding achievements. Therefore, this paper analyzes the development and application of AI in biomedicine and looks forward to its future development. The detailed review included examples of how artificial intelligence has been used in biological medicine, the research and development of new pharmaceuticals, the development of new drugs, and the diagnosis of auxiliary diseases. Finally, this paper summarizes and prospects the future development of biomedicine.

Введение.Определена актуальность внедрения технологий искусственного интеллекта в Российской Федерации (ИИ-технологий). Установлено, что в нашей стране строительство значительно уступает другим отраслям экономики по использованию ИИ-технологий. Цель исследования – определение приоритетных сфер применения технологий искусственного интеллекта в строительном комплексе РФ. Методы. В ходе исследования использовались генеративные технологии, методы машинного обучения, статистического анализа, экспертных оценок. Результаты. Изучен отечественный и зарубежный опыт внедрения ИИ-технологий в строительстве; выявлены основные причины недостаточного развития этих технологий в строительстве в нашей стране; определены основные направления использования искусственного интеллекта в строительном комплексе РФ; оценены техническая возможность и экономическая целесообразность реализации ИИ-технологий в практической сфере строительства. В качестве основных причин слабого использования искусственного интеллекта в строительном комплексе Российской Федерации следует назвать ограниченное использование данных, отсутствие квалифицированных специалистов, высокую стоимость внедрения, сложности с интеграцией; регулирование и стандарты. Определены наиболее значимые факторы эффективного применения технологий искусственного интеллекта в строительной отрасли: качество данных; интеграция с существующими системами; обучение и поддержка; выбор правильного инструмента; регулярное обновление и улучшение. На основе проведенного анализа выявлены приоритетные направления внедрения ИИ-технологий в строительном комплексе РФ: искусственный интеллект в автоматизированном проектировании, управлении строительством, контроле качества строительных работ, прогнозировании рисков в строительстве, анализе данных, оптимизации ресурсов, обеспечении безопасности и экологической устойчивости. Вывод. Для ускорения внедрения технологий искусственного интеллекта в строительную отрасль России необходимо развивать инфраструктуру данных, обучать специалистов, создавать благоприятные условия для инвестиций и разрабатывать соответствующие регулятивные нормы и стандарты. Introduction. Artificial intelligence has recently found extensive application in the Russian Federation. However, it has been determined that the application of AI technology in the construction industry in our country lags much behind other economic sectors. The aim of research is to determine priority areas for the application of artificial intelligence in the construction industry of the Russian Federation. Materials and methods. The research made use of generative technologies, statistical analysis, machine learning, and expert evaluation methods. Research outcomes. As a result of research, the authors examined the experiences of both national and international construction companies utilising artificial intelligence. They also determined the primary applications of AI in the Russian Federation's construction industry and evaluated the viability of both technological and financial implementation of AI in construction. The following should be listed as the primary causes of insufficient application of artificial intelligence in the Russian Federation's construction industry: restricted data use, a shortage of qualified personnel, high implementation costs, challenges related to integration, regulations and standards. The following are the key elements for effective application of AI in the construction sector: high-quality data; integration with current systems; assistance and training; selection of the appropriate tools; and regular updates and enhancements. Based on the analysis, priority areas for the implementation of AI technologies in the Russian construction industry were identified: artificial intelligence in automated design, construction management, quality control of construction work, risk forecasting in construction, data analysis, resource optimization, ensuring safety and environmental sustainability. Conclusions. The development of data infrastructure, the training of experts, the creation of investment-friendly environments, and the development of suitable regulatory norms and standards are all essential to accelerate the adoption of artificial intelligence technologies in the Russian construction sector.

This research was conducted to find out the significant effect of audiovisual media on students’ speaking ability. This research used a quasi-experimental design, and the sample of this research was class VIII.1 as an experimental class that consists of 22 students, and class VIII.12 as a control class with 22 students. The instrument of this research was a test, it was in the form of pre and post-test. The data analysis in this research was descriptive statistics and inferential statistics. The score of student’s basic speaking ability was calculated using Microsoft Excel 2010. The data resulted through that calculation was analyzed using the Statistical Package for Social Science (SPSS) 21.0 versions. The findings could be concluded that there was a significant effect of using Audio-Visual Media toward students’ speaking ability at second-grade students of SMP Negeri 1 Baubau. It can be seen based on the score of the t-test in the appendix, it showed that there was a significant effect on the students’ speaking ability in speaking. It was proved by the finding t-test (2.696) which was higher than ttable at 5% level of significance (2.04). It could be stated that 2.04<2.696 for students’ speaking ability. It meant that the null hypothesis (Ho) was rejected, while the alternative hypothesis (Ha) was accepted. In conclusion, teaching speaking by using Audio Visual at the second-grade students of SMP Negeri 1 Baubau better than without using Audio-Visual Media.

This study aims to determine the effect of the Application of the Value Clarification Technique (VCT) Learning Model on Students' Speaking Ability in Indonesian Language Subjects in Class IV SDN Sumurwiru. This research is a Pretest Experimental with One Group Pretest-Posttest design. The population in this study were all fourth grade students at SD Negeri Sumurwiru, totaling 24 students. The sampling technique in this study is the sampling technique. Data collection techniques used in this study were interviews, tests and documentation. The data analysis technique used in this study is the normality test, homogeneity test, and hypothesis testing (Wilcoxon). The results of the study showed that (1)students' speaking ability in Indonesian language subjects in class IV SDN Sumurwiru, Cibeureum District, Kuningan Regency before using the Value Clarification Technique (VCT) Learning Model, was still lacking with an averagescore of 62.08. (2) The ability to speak Indonesian language students in class IV SDN Sumurwiru, Cibeureum District, Kuningan Regency, after using the Value Clarification Technique (VCT) Learning Model, was good with an average scoreof 78.63. (3) There is an influence on the application of the Value Clarification Technique (VCT) Learning Model on students' speaking ability in Indonesian language subjects in class IV SDN Sumurwiru, Cibeureum District, Kuningan Regency, with an Asymp value. Sig. (2-tailed) 0.000.

This study was conducted to determine to what extent the English Café Program affected the students’ speaking ability and their attitude toward foreign teachers as well as the significant differences in the effects between the program carried out face-to-face and online as perceived by the participants in this study. This is a descriptive-comparative survey research. Frequency analysis, mean comparison analysis, t-test, and correlation analysis were performed. Mean values show that as perceived by the respondents, the program, implemented face-to-face and online, improve the students’ speaking ability and attitude towards foreign teachers to a great extent. Computations for significant difference show that there is no significant difference in the perceptions of the respondents. In the correlation analyses, in both face-to-face English Cafe and online English Café programs, students’ speaking ability came out to be significantly positively correlated to their attitude towards foreign teachers. The results also reveal that there is a significant negative correlation between students’ speaking ability and teachers’ length of service only in the face-to-face English Café program. There was no correlation between students’ speaking ability and their attitude towards foreign teachers and teachers’ educational qualification in both face-to-face and online English Café programs.

Our presentation focuses on the topic and relationship between religion, ecclesiastical journalism and media technology, artificial intelligence. In the first part of our presentation, we will review how artificial intelligence is changing the media industry on a global scale. As a result, what new inequalities are created in the media industry. After that, we will present which processes related to new AI applications can be automated in the field of media content production. And we also cover the transformation of the role of a journalist and the perception of a journalist’s role. In our presentation, we will demonstrate what artificial intelligence applications Hungarian religious and ecclesiastical media content creators use in their work, what attitudes they have regarding artificial intelligence, and what journalistic ethical issues concern them. We also present whether religious institutional or editorial regulations regarding the applicability of artificial intelligence are implemented or not. In our presentation, we show the results of qualitative research conducted in the fall of 2023 and quantitative research conducted in the spring of 2024. In the fall of 2023, we conducted in-depth interviews with 40 journalists regarding artificial intelligence. The gender and generational differences are clearly visible from the results. Building on this, we prepared a questionnaire in the spring of 2024, in which we also asked about the attitudes of religious and nonreligious content producers regarding artificial intelligence. In our lecture, we present the results of this research. What differences can be shown between religious and non-religious content creators in the use of artificial intelligence tools during their journalistic work.

Drug discovery has traditionally been a time consuming and expensive endeavor. Additionally, drugs weren’t as effectively designed as those that are being predicted and developed through AI and ML today. Machine learning is a form of artificial intelligence that develops and evolves based on experience (similarly to the human mind), and is more recently being utilized in drug discovery and design. The integration of AI and ML into the drug discovery and development process has allowed for higher target precision, lower toxicity, and better dosage formulations. AI more generally has been introduced to and has been leveraged at, each step of drug development, including target identification and validation, hit identification, as well as hit to lead optimization, and has been key in shortening the previously lengthy drug screening process. AI and ML has also been applied downstream in drug formulation where it has maximized resource utilization and is allowing for web-based 3D printing of drugs. Application of AI in the drug development process has also been extended to the modeling of novel drug-like compounds to predict their ADMET properties. This review will address the stages of drug discovery and development in which the application of AI and ML modeling has altered the traditional development of drugs. Keywords: Drug discovery, machine learning, artificial intelligence, computational drug development.

Introduction: In todays rapidly changing technology, artificial intelligence (AI) is changing the way we live, work and create art at an unprecedented speed. As an important part of human culture, dance art has also ushered in new development opportunities and challenges in this scientific and technological revolution. Objectives: This paper aims to explore the innovative application and influence of artificial intelligence (AI) in dance creation and performance. With the rapid development of AI technology, its application is increasingly wide in the field of art, and dance art is no exception Methods: This paper first outlines the application of AI technology in dance creation, including the generation of new dance movements through algorithms, auxiliary choreography, etc. These applications provide unprecedented creative sources and tools for dance creators. Then, this paper analyzes the role of AI in dance performance, such as the accurate movement performance of dance robot, the immersive experience of virtual reality technology in dance performance, etc. Results: These technologies not only enrich the form of dance performance, but also broaden the viewing experience of the audience. In addition, this paper also discusses the application of AI in dance teaching, such as intelligent guidance system, distance dance teaching, etc., which bring convenience and personalization to dance teaching. However, the application of AI in the field of dance also faces technical challenges and art ethical issues, which need further research and discussion. Conclusions: In conclusion, this paper believes that the application of AI technology in dance creation, performance and teaching has broad prospects, but it also needs to pay attention to its potential impact and challenges to promote the harmonious coexistence of dance art and AI technology. The research of this paper provides new perspectives and thoughts in the field of dance art, Provides a reference for future research and practice.

Technological progress, especially in the field of information, has led to reducing the gap between science, information and knowledge. This accelerating change has forced all educational institutions to comply with this new mission by using information technology in the teaching process, as artificial intelligence has become an integral part of the educational and learning process, and a means of Effective in the teaching process, in addition to being research tools in obtaining information and knowledge, the research problem focused on (what are the attitudes of the kindergarten teacher towards using artificial intelligence applications in the effective teaching process in the early education stage in the third Rusafa Education Directorate?), where the importance of The research is considered one of the researches that deals with an important and vital topic (artificial intelligence), as it gains its importance in that it represents the role that kindergarten teachers play in the early education stage in developing the skills and abilities and refining the information of the child through their use of artificial intelligence methods and applications, as well as The positive role of such research in stimulating kindergarten teachers’ motivation to benefit from artificial intelligence applications, which increases the efficiency and effectiveness of their teaching. The aim of the research is to reveal kindergarten teachers’ attitudes towards using artificial intelligence in the effective teaching process in the early education stage, as well as to reveal the most important The challenges facing kindergarten teachers using artificial intelligence in the effective teaching process, and are there any statistically significant differences between the average kindergarten teacher’s attitudes to using artificial intelligence in the effective teaching process in the early education stage according to the research variables? The research reached several conclusions, perhaps the most important of which is the existence of differences. There is statistical significance between the average kindergarten teacher’s attitudes to using artificial intelligence in the effective teaching process in the early education stage according to the research variables. The research recommends holding many workshops and training courses for kindergarten teachers on how to use artificial intelligence in effective teaching, and including programs and rehabilitation plans for kindergarten teachers. About the use of artificial intelligence according to the plans of the Ministry of Education, which are consistent with its vision, and encouraging teachers to proceed and benefit from applications and websites for safe and available artificial intelligence applications in the teaching process

After the revolution of technology and artificial intelligence in all fields, this study aims at investigating the influences of using artificial intelligence applications on learning English language in Iraqi secondary schools. The population is all English language students in Iraqi secondary schools in Baghdad in The General Directorate of Education⁄ Al- Rusafa 2nd. This study has used a descriptive approach, a questionnaire has been used as an instrument to collect data. A sample of 200 students has been chosen randomly. The primary objectives of this study are; to evaluate the effectiveness of AI tools in enhancing English language skills; to assess students' attitudes towards the use of AI in the English language classroom ,and to explore the challenges and benefits associated with AI applications in English language. The results have been shown that Iraqi secondary students have been effected by using AI applications inspite of their probable risk and indicated a positive impact of the use of AI tools and improvement in students’ listening, speaking more than reading, and writing skills. The study has provided some suggestions and recommendations to increase the use of artificial intelligence to keep pace with global development.

In this article, we review a number of pros and cons, including the meaning and application of artificial intelligence. We also considered the latest technological developments in the real world and discussed the application of AI in the fields of heavy industry, gaming, aviation, weather forecasting and expert systems, focusing on expert systems. Specialty applications for AI include expert systems, speech recognition, and machine vision. AI can be classified as weak or strong. Weak AI (also known as Narrow AI) is an AI system designed and trained for specific tasks. Virtual personal assistants (such as Apple's Siri) are weak AI. Powerful AI, also known as artificial intelligence, is an AI system with a wide range of human cognitive capabilities. When performing unfamiliar tasks, powerful AI systems can find solutions without manual intervention. The artificial intelligence that makes computers behave like humans is human-like, fashion-like, and humans spend much less time. Therefore, it is called artificial intelligence. This article concludes by analyzing the future potential of artificial intelligence.

The widespread use and adoption of Artificial Intelligence (AI) applications among university students has drastically transformed the educational landscape. Recognizing the importance of this transformation, this study aims to investigate the factors affecting the adoption and use of AI applications among Pakistani research scholars. This study used an extended version of the unified theory of acceptance and use of the technology model and innovative resistance theory. The data were collected from 235 research scholars through a questionnaire. Descriptive statistics and a multiple linear regression test were used to analyze the collected data. The study found that Pakistani research scholars used various AI applications for research purposes such as ChatGPT, Grammarly, ChatPDF, and SciSpace. This study found that personal innovativeness, performance expectancy, social influence, and trust significantly influence research scholars’ behavioral intention to use AI applications. In contrast, the impact of effort expectancy, facilitating conditions, and resistance to innovation on students’ behavioral intention to use AI tools was statistically insignificant. The findings offer actionable insights for educators, policymakers, and technology developers aiming to enhance AI adoption in higher education.

This study evaluates the impact of Artificial Intelligence (AI) applications in power systems on energy security and to determine relevant policy implications. We use a mixed methods approach to analyze the benefits and risks associated with AI implementation on the European power grid, focusing on four key dimensions of energy security: availability, affordability, accessibility, and acceptability. We investigated the benefits of AI using PyPSA, a Python-based model of the European electricity system. Three AI applications were parametrized: load reduction, load shifting, and wind wake steering. We compared scenarios in which these AI applications are widely deployed against a baseline scenario without these applications to determine if AI improves energy security. The study also analyzes risks associated with AI deployment in the power grid. We developed a risk taxonomy centered around six high-level categories: cybersecurity, jurisdictional or sovereignty issues, unexplained or unexpected actions by the model, unethical or illegal decision-making, reliance and trust in decision-making, and supplier dependency and vendor lock-in. Additionally, we conducted a back-casting exercise with subject-matter experts to determine positive and negative future outcomes of AI deployment and identify actions to create positive outcomes and avoid negative ones. The paper presents a set of policy implications for AI on the European synchronous grid. We find that AI applications can improve energy security in power systems. In the scenarios we tested, behind-the-meter applications have a greater impact on energy security than front-of-meter applications. The results suggest that AI applications targeting energy consumption may significantly improve energy security metrics. Keywords: Energy Security, AI, Power Grid, European Electricity System

This study investigates the scientific development of Artificial Intelligence (AI) and Machine Learning (ML) applications in Human Resource Management (HRM) through bibliometric analysis. To this end, 522 academic publications indexed in the Scopus database between 2020 and 2024 were analyzed using the R-based bibliometrix package and VOSviewer software. Descriptive analysis, scientific productivity metrics, and content analysis techniques were employed. The findings revealed three main patterns. First, research on AI and ML applications in HRM has grown significantly—particularly between 2022 and 2024—driven by post-pandemic digital transformation. Second, India, China, and the USA lead in research output, while the UK and France demonstrate strong citation impact, indicating a globally expanding research ecosystem. Third, the thematic focus of research is shifting from technical infrastructure toward more human-centered and ethical dimensions. Additionally, keyword co-occurrence network analysis identified three major thematic clusters: HRM functions, AI applications, and machine learning analytics, highlighting the field’s interdisciplinary nature. Compared to the previous studies, this research provides a more comprehensive bibliometric analysis of AI and ML applications in HRM. It is the first extensive study to map the intellectual evolution of the field from a multidisciplinary perspective. Furthermore, it charts research trends and collaboration networks, revealing a shift from technical implementations to strategic integration. In conclusion, this analysis offers new insights to the literature by illustrating the technological evolution in HRM and highlighting the growing significance of cutting-edge approaches such as AI and ML, reaffirming the field as a timely and impactful area of research.