Articles

The Utilization of Artificial Intelligence (AI) in English Skills as an Implementation of the Industrial Revolution 5.0

/in /by

The implementation of Artificial Intelligence (AI) in English skills, as exemplified by the Duolingo application, illustrates the transformative shift in education within the Industrial Revolution 5.0 era, where human–machine collaboration enhances personalized skill development. This study involved 30 Grade XI students at SMKN 3 Baubau and employed a descriptive qualitative approach to examine learners’ perceptions and experiences with AI-based learning tools. Data were collected through field observations, English proficiency tests, questionnaires, and interviews. The results indicate that Duolingo effectively supports self-directed blended learning, improving students’ speaking, listening, reading, and writing skills in an engaging and autonomous manner. Through AI-driven gamification, Duolingo adapts to individual learner performance by providing instant feedback, progressive difficulty levels, and interactive exercises that maintain motivation and reduce learning fatigue. These adaptive features align with the vision of Industrial Revolution 5.0, where technology collaborates with learners to optimize progress. Most participants reported significant improvements in vocabulary acquisition, pronunciation, and comprehension, attributing their advancement to daily practice and active engagement facilitated by the application. In conclusion, AI-powered platforms like Duolingo go beyond digitizing traditional learning; they transform the educational experience by fostering intrinsic motivation, sustaining engagement, and enabling personalized learning pathways, thus equipping learners for global communication demands with both efficiency and enjoyment.

Exploring the Impact of AI on English Learning of Business English Juniors at Nguyen Tat Thanh University

/in /by

This study investigates how artificial intelligence (AI) influences the English‑learning processes of third‑year Business English majors at Nguyen Tat Thanh University (NTTU). A mixed‑methods design was employed, comprising an online survey (n = 34) and semi‑structured interviews (n = 15). Quantitative data were analyzed using SPSS 26, yielding Cronbach’s α = .984, and qualitative responses underwent thematic analysis. Students reported that AI tools (e.g., ChatGPT, Grammarly) enhanced personalized learning (44.1 %), provided instant feedback (17.6 %), and increased motivation (17.6 %). Interview themes highlighted efficiency gains, richer access to specialized Business English materials, and greater communicative confidence. These findings demonstrate AI’s pedagogical value in Business English instruction and suggest that integrating AI‑powered platforms can optimize curriculum design. Future research should compare AI‑mediated and traditional teaching to assess long‑term learning outcomes.

The Impact of AI on The Learning Habits of HEI Students

/in /by

The old paradigms of education are being disrupted as a result of the growing incorporation of artificial intelligence (AI) technology into higher education institutions (HEIs). The purpose of this study is to evaluate the influence that artificial intelligence-driven tools and platforms, such as adaptive learning systems, intelligent tutoring systems, automated feedback mechanisms, and AI-based content recommendation engines, have on the behaviour of students who are enrolled in higher education institutions. The research finds major changes in students’ study behaviours, time management, and learning preferences. This is accomplished via the use of a mixed-methods approach, which combines quantitative surveys and qualitative interviews with undergraduate and postgraduate students from a wide range of academic fields. The findings indicate a trend towards learning experiences that are more personalized, autonomous, and on-demand. This transition is made possible by the ability of artificial intelligence to analyse individual learning patterns and present information that is suited to those patterns. An over dependence on artificial intelligence, a decrease in critical thinking, and digital exhaustion are some of the concerns that are brought to light by the study. The final section of the study emphasises the importance of integrating artificial intelligence in a way that is balanced, so that it may improve learning outcomes while maintaining cognitive engagement and academic integrity.

Artificial Intelligence and Machine Learning- Driven Pharmaceutical Industry

/in /by

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing the pharmaceutical sector at every stage—drug discovery, development, regulatory affairs, quality control, and post-marketing surveillance. These technologies improve data processing, accuracy, and timelines by using complex algorithms and large volumes of healthcare data. AI helps in drug target identification, drug design, prediction of toxicity, and pharmacokinetics modeling, as well as improving regulatory processes and pharmacovigilance. Though they have their benefits, there are still challenges such as data privacy, algorithmic bias, explainability, and accountability. Regulatory structures and ethical implications need to keep pace so that AI can be used safely and fairly in pharmaceuticals. This article discusses the existing applications, advantages, risks, and future possibilities of AI and ML in transforming drug development and healthcare outcomes.

Approaching the ASSURE Model and Proposing a Teaching Process for Mathematics Using AI Chatbots Combined with Gamification in a Self-Regulated Learning Framework

/in /by

The ASSURE model is a method for designing and implementing lessons developed to optimize the teaching and learning process, particularly in integrating educational technologies. This model assists teachers in creating highly flexible lessons, enabling students to acquire knowledge more effectively through the use of technology and modern teaching methods. AI Chatbots facilitate the automation of responses and support personalized learning for students, while gamification provides an engaging learning environment that helps students develop critical thinking and problem-solving skills in mathematics through the incorporation of game elements. Research findings indicate that the combination of AI Chatbots and gamification in teaching can enhance students’ learning of mathematics, while also increasing engagement and motivation. This paper approaches the ASSURE model and proposes a teaching process utilizing AI Chatbots combined with gamification in a self-regulated learning framework, aiming to guide teachers in organizing mathematics instruction in a scientific and effective manner.

AI Chatbot: A Teaching Tool to Support the Development of Self-learning capacity in Chemistry for High School Students

/in /by

In the context of digital transformation and the rapid development of artificial intelligence (AI), the use of AI technology in general and AI Chatbot in particular in education has become a significant trend. There is an increasing number of studies and practical applications of AI Chatbot in teaching and learning. Research indicates that AI Chatbot bring numerous benefits to the teaching process of subjects such as foreign languages, mathematics, science, chemistry, and more. This paper analyzes the potential of AI Chatbot in supporting the self-learning process of high school students in Chemistry. By integrating artificial intelligence technology, AI Chatbot not only provide instant information but also personalize the learning process, helping students enhance their self-learning capacity more effectively. Specifically, the study focuses on identifying the relationship between AI Chatbot and the self-learning process in Chemistry, while also proposing methods to implement AI Chatbot in Chemistry education to improve self-learning capacity for high school students in particular and for other subjects and levels of education in general.

The Future of E-Waste Recycling: Emerging Technologies and Practices Evaluating the Social and Economic Benefits of Advanced E-Waste Recycling Technologies

/in /by

The exponential development in electronic waste (e-waste) has become an urgent global concern, necessitating new and sustainable recycling solutions. Emerging technologies, including bioleaching, robots, and artificial intelligence (AI)-driven material recovery, present prospects to transform e-waste management by enhancing resource recovery, minimizing environmental impact, and boosting social and economic growth. This study assesses the effectiveness of these sophisticated recycling technologies, concentrating on their economic viability, environmental sustainability, and societal advantages. A mixed-methods approach, integrating quantitative data analysis and qualitative insights, gives a full appraisal of the revolutionary potential of these technologies in the context of a circular economy.

А Model for School Subject “AI Proficiency” for Advanced students in Secondary TVET School: Conceptual Framework and Content with Practical Exеmplary Curriculum

/in /by

The article proposes a subject model for special preparation for professional education and training for classes in the professional field Computer Science and Technology, as a continuation of the subject „Introduction to AI: General education“ for TVET secondary schools in Bulgaria, proposed by the author in a previous published article. The model is balanced, with an emphasis on active learning with a synergistic and holistic creative approach, where over 80% of the time the student is involved in an active (individual or collective) activity: researching materials, drawing up models, discussions and debates, SWOT analyses, as well as project-based tasks of greater or lesser volume, problem cases. The topics are considered not only in their strict technical context, but also holistically-synergistically: ethics in the matter of AI, strategies for regulations, future perspectives and benefits, personal interests. The curriculum aims to provide vocational high school students with a comprehensive understanding of AI, covering fundamental concepts, practical applications, advanced technologies, ethical considerations and future trends in the field, through a combination of theoretical learning, practical projects, creative activity and discussions, develop critical thinking skills and will prepare for further study or careers in AI-related fields.

Integrating Artificial Intelligence in Teacher Education: A Systematic Analysis

/in /by

The current work is a systematic review paper that examines the function and significance of artificial intelligence (AI) in teacher education. The researcher gathered almost fifty articles from various platforms, including Google Scholar, Science Direct, Research Gate, and others, on AI and teacher education. Additionally, those publications’ analysis reveals a few key areas and their significance for teacher preparation. By delivering tailored learning experiences, improving instructional strategies, and providing data-driven insights etc. After collecting the article from the above sources, the investigator analyzed all the article on four major points e.g. AI and digital learning, AI and Teacher Education, AI and pedagogical leaning, AI and challenges in teaching learning process systematically, where the investigator found few points and analyzed vividly, at the end the view concern to the Artificial intelligence (AI) has the potential to completely transform Teacher Education. But in order to fully enjoy these advantages, the ethical, equitable, and preparedness issues around AI must be resolved.

The Importance of Creating Artificial Intelligence Supported Future Scenarios in Decision Making Processes

/in /by

Artificial intelligence technologies are rapidly developing and having a major impact on the business world. Decision-making processes play an important role for the success of an organization. However, in today’s business world with its complexity and uncertainty, it becomes difficult to manage decision-making processes. At this point, creating future scenarios supported by artificial intelligence and working on different scenarios helps businesses to be more prepared for uncertainty.

Artificial intelligence-supported scenarios can be utilized across various sectors and fields of work. AI enables businesses to analyze past data, predict trends, and consequently work on future scenarios to make more informed decisions. The significance of future scenarios lies in identifying risks and opportunities in advance, adapting to future changes, and being proactive in competition. By evaluating potential developments, shaping your business strategy, you can gain a competitive advantage and make more reliable decisions.

Qualitative methods were employed in the research. Interviews were conducted with managers from 6 different professional groups (software, biomedical, public, construction, university, e-commerce). Data was collected and analyzed using semi-structured interview forms consisting of 4 questions. When the findings were evaluated, no concerns or negative expressions regarding the use of artificial intelligence were expressed. Except for public institutions, everyone has AI in their planning. Each sector believes it is important. No negative concerns were expressed. The prominent concepts in the findings are: Speed, big data, gaining competitive advantage, personalized customer experience, risk analysis, cost advantage, technology adaptation, optimization, accurate and fast situation detection, efficiency, etc.

It is thought that the research will create significant awareness for businesses in the turbulent period of the 21st century, where uncertainties are greater than ever. Despite all the positive aspects, AI-supported decision-making processes also carry some risks. The most prominent risks include the applicability of AI-supported scenarios, security concerns, the existence of ill-trained AI models, ethical issues and data privacy.