Educational Intelligence Research Articles

Artificial Intelligence In Education: Ethics & Responsible Implementation

This study investigates the ethical use of Artificial Intelligence in academia, with an emphasis on AI integration in education and its possible impact on learning experiences. It investigates factors to consider when implementing AI in education, such as costs, privacy concerns, job displacement, biases, and safety concerns. In addition, the paper examines techniques for effectively integrating AI in education, such as institutional regulations, plagiarism detection technologies, teaching students and staff, fostering critical thinking, peer review, and organizing ethical AI usage workshops. The study presents findings from several studies and underlines the importance of constant monitoring and evaluation of AI systems in educational settings to ensure responsible and productive use.

The Application and Potential Future Development of Artificial Intelligence in Education

With the coming of the era of artificial intelligence, the impact of artificial intelligence technology on basic education has been widely discussed, but there are still many problems and challenges. This paper focuses on the analysis of AI technology enabling basic education and the challenges in the application process. This paper concludes that artificial intelligence helps teachers carry out intelligent teaching and promotes students' personalized learning. But at the same time, AI also brings many challenges and risks, such as how to protect privacy and filter information in data overflow; And how to keep students creative while using AI. Based on this, this paper puts forward the following suggestions: the government should strengthen the investment and optimize the allocation of basic education resources; The government will explore the development of ethical norms and regulatory mechanisms applicable to artificial intelligence in the field of education; Schools to strengthen the training and introduction of teachers; Individual students combine artificial intelligence with real life.

Zero-Shot Image Caption Inference System Based on Pretrained Models

Recently, zero-shot image captioning (ZSIC) has gained significant attention, given its potential to describe unseen objects in images. This is important for real-world applications such as human–computer interaction, intelligent education, and service robots. However, the zero-shot image captioning method based on large-scale pretrained models may generate descriptions containing objects that are not present in the image, which is a phenomenon termed “object hallucination”. This is because large-scale models tend to predict words or phrases with high frequency, as seen in the training phase. Additionally, the method set a limitation to the description length, which often leads to an improper ending. In this paper, a novel approach is proposed to address and reduce the object hallucination and improper ending problem in the ZSIC task. We introduce additional emotion signals as guidance for sentence generation, and we find that proper emotion will filter words that do not appear in the image. Moreover, we propose a novel strategy that gradually extends the number of words in a sentence to confirm the generated sentence is properly completed. Experimental results show that the proposed method achieves the leading performance on unsupervised metrics. More importantly, the subjective examples illustrate the effect of our method in improving hallucination and generating properly ending sentences.

Understanding Teachers' Perspectives on ChatGPT-Generated Assignments in Higher Education

The rapid integration of artificial intelligence (AI) in education has transformed instructional methodologies and administrative tasks. However, teachers in higher education face challenges, particularly in creating high-quality assignments and rubrics amidst increasing administrative burdens. This study investigates the potential of AI, specifically ChatGPT, in streamlining assignment creation. Through automating aspects of assignment development, AI tools offer support to teachers while maintaining pedagogical integrity. However, empirical investigation is needed to understand perceptions and effectiveness. Using observations and semi-structured qualitative interviews, the study explores teachers' perceptions of AI-generated assignments and their impact on student learning outcomes and engagement. It also examines students' experiences and perceptions, understanding AI's role in enhancing learning experiences and facilitating teacher productivity. The data were analysed by content analysis. Findings suggest that teachers found the usage of ChatGPT helpful in reducing their administrative workload while maintaining academic integrity. Additionally, students embraced attempting the assignments, and doing so contributed to enhancing their subject knowledge. Furthermore, teachers facilitated students by encouraging them to reconsider the problem, persisting in their efforts, and inviting communication and collaboration with peers. The study also discusses the implications for teachers, highlighting AI's transformative potential.

The Impact of AI-Assisted Teaching on Students' Learning and Psychology

The integration of artificial intelligence (AI) in education has garnered significant attention, yet its implications on student outcomes require further exploration. This paper analyzes the impact of AI-assisted teaching on students' learning and psychological well-being. Through a comprehensive review of existing AI applications in education, including intelligent tutoring systems and educational chatbots, the study examines how these technologies influence academic performance and psychological health. The findings indicate that AI-assisted teaching enhances learning outcomes by providing personalized educational experiences and fostering student engagement. Furthermore, AI systems contribute positively to students' psychological well-being by offering timely emotional support and personalized stress management strategies. However, challenges such as technological limitations, resistance to change, and privacy concerns persist. Based on these insights, the paper suggests actionable recommendations for the effective integration of AI in education, emphasizing the need for robust infrastructure, continuous educator training, and ethical considerations to maximize benefits while mitigating potential risks.

The Application and Challenges of ChatGPT in Preschool Education

At present, the application of ChatGPT in education has been widely discussed. However, further research and discussion are needed on how to better integrate artificial intelligence in preschool education for young children aged 3-7 years. This paper analyzes the existing research on the application of AI in young children and concludes that the benefits of AI in preschool education can not only help improve and enrich curriculum design but also contribute to the development of artificial intelligence education. However, there are several challenges associated with AI in preschool children. First, artificial intelligence has limitations in children's language understanding. Second, children's emotional needs may not be satisfied. Last, there are doubts about the rationality of the suggestions made for young children. Based on the Pre-operational Stage of Piaget's children's cognitive development, this paper provides the following insights for the integration of ChatGPT and preschool education. One of the future works for ChatGPT is to combine the multimode to understand children's language. Another approach is to be used as a virtual partner to develop young learners' interpersonal communication and emotional management through scene simulation. Additionally, ChatGPT should provide simple and specific suggestions, according to the cognitive development characteristics of young learners.

Review of Artificial Intelligence in Education – Perspectives and Challenges

Review of Artificial Intelligence in Education – Perspectives and Challenges

Institutional aspects of the use of artificial intelligence in higher education and science: The role and importance of compliance

Institutional aspects of the use of artificial intelligence in higher education and science: The role and importance of compliance

Prospects for Using E-Learning Tools to Implement the Concept of “Lifelong Learning”

This article examines the current state and prospects of utilising e-learning tools within lifelong learning. The study aims to identify methods for leveraging various e-learning platforms to enhance adult lifelong education and assess the potential effectiveness of electronic tools in advancing "lifelong learning." The research employed a case study approach, analysing existing scientific literature and focusing on nine popular adult e-learning tools, such as Coursera, EdX, Moodle, Udemy, and Google Classroom. To achieve this, 50 scientific articles from various databases were reviewed, and the characteristics and potential applications of popular e-learning tools and the role of artificial intelligence in education were investigated. The findings were systematically organised and presented in tables and diagrams, showcasing different categories and applications of e-learning tools for lifelong learning. The study categorises these e-learning tools and highlights their features and applications in the context of lifelong learning. Additionally, the study explores the integration of artificial intelligence in e-learning, discussing its various applications and how it can facilitate adult education. The e-learning tools selected for adult education are divided into four categories: Open Educational Resources (OER), Massive Open Online Courses (MOOC), Technical and Vocational Education and Training (TVET) (digital), and Communication tools (MS Teams, Zoom, and Google Classroom). This research contributes to lifelong learning by demonstrating the potential of selected online platforms and programs to increase the accessibility, inclusivity, and personalisation of lifelong learning tailored to individual learner needs.

Generative Artificial Intelligence Systems and the Challenges in Latin American Education

This article examines the transformative role of Generative Artificial Intelligence (GAI) in education, exploring diverse disciplines such as engineering, medicine, programming, and information systems. GAI emerges as a revolutionary force, promising to fundamentally change educational practices. The PRISMA 2020 methodology (Page et al., 2021) was used to evaluate the relevant scientific literature. The systematic review identified research that applied specific criteria in the analysis of IAG in education. The selected papers covered a variety of disciplines, providing a comprehensive view of the impact of IAG in education. The results show a diversity of approaches and institutional responses to IAG in education. From significant changes in teaching practices to the identification of specific opportunities in disciplines such as computer science and engineering, GAI stands out as a catalyst for transformation. The adaptation of tertiary education, the need for specific skills to work with GAI, and ethical responses emerge as key themes. It focuses on the need for a deeper and more consensual understanding of the role of GAI in education. Concrete research-supported opportunities are highlighted, but ethical limitations and concerns are also underscored. Collaboration, reflection, and adaptation to open educational practices are proposed as approaches to address the challenges and fully exploit the benefits of IAG in education. This comprehensive analysis contributes to understanding the current and future landscape of GAI in education, providing valuable guidelines for educators, institutions, and educational technology developers.

Artificial Intelligence in Higher Education: Enhancing Learning Systems and Transforming Educational Paradigms

This study ventures into the expanding role of artificial intelligence (AI) in higher education and its potential to revolutionize the learning experience. Through a qualitative approach, we investigate how advanced AI-driven educational tools can enhance learning systems through tailored learning experiences, AI-powered adaptive tutoring platforms, immersive digital learning environments, and AI-assisted assessment and feedback systems. From a theoretical perspective, we utilize the constructivist theory of learning as a study framework to explain the role of technology in AI-facilitated personalized and collaborative knowledge construction. This study was executed in three stages. First, we present a brief overview of AI and its recent impact on the education system, including its ethical considerations and implementation hurdles. In the second stage, we propose the potential implications for learning contexts through the constructivist lens, the process of AI-supported cognitive development, and the use of AI tools for optimizing educational processes through AI and transformation in educational paradigms and study work. The findings suggest that institutions can unlock new opportunities for efficiency, accessibility, and personalized learning by adopting AI technology, but they also highlight the need to address ethical considerations and implementation hurdles. This study also contributes to future studies by examining the impact of AI on student outcomes, teacher roles, and institutional practices in education, as well as exploring ethical and equity concerns in AI-driven educational settings.

Structure and process: A theoretical model of intelligent elementary Chinese vocabulary teaching

With the rapid development of artificial intelligence technology, Chinese vocabulary teaching is gradually entering an era of innovation, offering vast potential for more intelligent and personalized teaching models. Existing research mostly focuses on the auxiliary role of AI technology in second language teaching, with less attention given to the implementation of intelligent second language teaching. To address this issue, this study, based on the perspective of Artificial Intelligence Generated Content (AIGC), attempts to construct an elementary Chinese vocabulary teaching (ECVT) theoretical model, presenting the development process of an ECVT system. From the existing research literature on Chinese vocabulary teaching, a total of 17 viewpoints on teaching structures and 19 viewpoints on teaching processes for ECVT are outlined. Based on this, the study first establishes the fundamental macro-level phases of ECVT, then delves into the micro-level structures and processes of each phase, ultimately deducing a theoretical model for ECVT oriented towards intelligent teaching. Integrating the perspectives of artificial intelligence deconstruction and generation into the research on Chinese vocabulary teaching not only offers front-line teachers a reference for optimizing teaching models but also provides a more forward-looking and scientifically grounded framework for Chinese language teaching, even other language teaching. This hence propels innovation in second language teaching models.

Enhancing or Hindering? AI's Role in Sparking Creativity in Language Teaching: Insights from Private High School EFL Teachers

The integration of artificial intelligence in education presents both opportunities and challenges, particularly in the field of language teaching. This study aims to investigate Turkish EFL teachers' perceptions of AI's role in fostering or hindering creativity in language teaching. Through semi-structured interviews with 10 EFL teachers from private high schools, the research explores the potential benefits and challenges of AI integration. Key findings reveal that AI enhances student engagement, provides personalized learning experiences, and offers timely feedback. However, concerns about insufficient training, technical issues, and over-reliance on AI potentially undermining fundamental skills were also expressed. While AI tools support improvements in language skills and foster creative thinking, there is apprehension about standardization and the risk of diminishing originality. The study underscores the necessity for effective teacher training and a balanced approach to AI integration, ensuring it complements rather than replaces traditional teaching methods. These insights provide valuable guidance for educators, policymakers, and technology developers to optimize AI use in EFL education while fostering a dynamic and creative learning environment. Future research should explore innovative ways to integrate AI into language teaching without compromising creativity.

The Use of AI in Improving Student's Critical Thinking Skills

The use of artificial intelligence (AI) in education has the potential to significantly enhance students' critical thinking skills. This study explores how AI tools can improve critical thinking among students majoring in English Education at X University. Utilizing a mixedmethods approach, the research combines quantitative surveys and qualitative interviews to assess the frequency and contexts of AI usage and its impact on critical thinking. Survey results reveal that 64% of respondents use AI tools several times a week, predominantly in educational settings. A smaller percentage of respondents use AI daily (14%), while another 14% use AI rarely, and 7% use it several times a month. Interviews with frequent AI users indicate that AI assists in expanding ideas and providing deeper insights, but its effectiveness depends on the users' ability to ask precise questions and critically interpret AI-generated content. The findings highlight that while AI can significantly aid in developing critical thinking skills through personalized learning experiences and interactive simulations, challenges such as potential biases and the need for foundational understanding persist. Ultimately, this research underscores the importance of thoughtful and critical use of AI in education to foster improved critical thinking skills.

Personalised learning and artificial intelligence in science education: current state and future perspectives

This paper presents a comprehensive examination of the integration of artificial intelligence (AI) in science education and its impact on personalised learning. The research explores current applications, challenges, and future perspectives of AI technologies in educational settings. Through a systematic literature review, we identify the advantages of AI, such as enhanced individualised instruction, data-informed insights, and increased student engagement. The study combines quantitative and qualitative analyses, case studies, expert interviews, and technology assessments to offer a multidimensional understanding of AI's role in personalising science education. Despite the potential benefits, the research highlights barriers, including financial costs, infrastructure requirements, data privacy, and the need for teacher training. The future of AI in education suggests a trajectory towards advanced personalisation capabilities through adaptable learning systems, virtual tutors, and immersive learning environments. We underscore the importance of addressing the identified challenges to fully realise the transformative power of AI in science education. The findings illustrate that, with thoughtful implementation, AI holds promise for tailoring science learning experiences, making them more effective, inclusive, and engaging for students of varied needs and abilities.

Artificial Intelligence in Education: An Exploration into the University Teachers’ Perspectives about Opportunities and Challenges

Artificial Intelligence in Education: An Exploration into the University Teachers’ Perspectives about Opportunities and Challenges

The Impact of Artificial Intelligence for Advancement in Entrepreneurial Education

The changing technology has advanced into new advents like Artificial Intelligence. This technology has diffused into the classrooms through chatbots like ChatGPT, Claude, Google Bard, YouChat, KoalaChat, ChatOn, Microsoft Binge and many others. The conventional softwares are only updated by humans while Artificial Intelligence can correct and remodel itself. Artificial Intelligence is assisting the entrepreneurial organizations and students in data analysis, automation and Natural Language Processing (NLP). It also helps the entrepreneurial organizations in strategic decision making and managing operations and accounts. This research focuses on the opportunities and challenges posed by Artificial Intelligence in the entrepreneurial education across various business schools. It examines the benefits of chatbots for educational purposes. It also studies the limitations of chatbots. It enquires about the business advice sought from chatbots. For this purpose, a survey was applied amongst students of entrepreneurial courses to analyze the impact of Artificial Intelligence in our classrooms. It is a study performed on 103 students enrolled in entrepreneurship courses at two management institutes of India between August, 2023, and December, 2023. The study focuses on the benefits of AI in areas such as assisting in classroom activities like such as market research, competitor analysis and legal aspects. It also aids the students in getting feedback for their assignments, preparing for examinations and rapid access to information. The research suggests that Artificial Intelligence is significantly contributing right from idea generation, planning, forecasting and progress evaluation of business plans to entrepreneurial students. It is extensively helping the entrepreneurial students in developing the business model canvas which assists them in designing the blueprint of the project, strategic management, and development of innovative business models. It also assists in improving the productivity and efficiency of students. This research would facilitate students, teachers and business schools imparting entrepreneurial curriculum inculcate Artificial Intelligence into the classroom studies.

Dispelling the magic of artificial intelligence in medical education

Dispelling the magic of artificial intelligence in medical education

Artificial intelligence in education: Embracing change, addressing challenges, and shaping tomorrow's curriculum

This special issue deliberated on AI and the curriculum with the aim of exposing various debates, controversies, and pathways in terms of policy and praxis in the Global North. Papers published in this special issue presented various arguments drawing from best practices to either problematise or support the use of AI within the curriculum. This is against the background that the advent of Artificial Intelligence (AI), integrating this advanced technology has become a pivotal topic of discussion and research, which in some cases is marred with controversy and the belief that ethical issues such as honesty and hard work are eroded as people use AI within the curriculum. As such, there seems to be resistance among conservative scholars, while other scholars have embraced AI as the future of curriculum implementation. Cognizant of the foregoing, it was critical that this special issue brings together various authors to air their views, which we hope will serve as part of policy formulation in the Global South.

Legal education and artificial intelligence: vectors of interaction

Objective: to develop proposals for the introduction of artificial intelligence (AI) in legal education. Methods: dialectical methods (analysis and synthesis, induction and deduction, systematization, comparison, classification, forecasting), statistical, formal-legal and comparative-legal methods. Used in combination, these methods allow comprehensive analysis of the relationship between AI and legal education. Results: the article reveals the main directions to improve legal education in the conditions of AI development: integration of information and communication technologies and training of specialists able to work effectively at the intersection of law and technology. The advantages and disadvantages of using AI in legal education are identified. Ethical aspects of AI application are outlined, as well as the need to manage the development of technologies based on the principles of fairness, transparency and consideration of human interests. The author states the importance of developing not only specialized knowledge, but also universal competencies that will help students to adapt successfully to the dynamically changing conditions of professional activity. Scientific novelty: a comprehensive analysis of the interaction between legal education and AI was carried out, including the identification of specific opportunities for the AI application in legal education, as well as related risks and problems. The author proposes a systematic approach to improving legal education in the context of AI development, focusing on theneed to revise educational programs in legal areas in terms of integrating information and communication technologies; developing universal competencies in students to adapt to a dynamically changing professional environment; introducing mandatory advanced training for judges, legal practitioners to develop skills for using AI systems. Practical significance: the study results can be used to optimize and adapt the educational programs of law schools to the digital era requirements and to develop effective approaches to the AI application in legal practice and education, taking into account ethical aspects and potential risks.