Application Of Artificial Intelligence In Education Research Articles

Problem Penggunaan AI (Artificial Intelligence) dalam Bidang Pendidikan

Artificial intelligence (AI) has become an increasingly important research subject in various fields, including education. In the educational context, the use of AI promises a fundamental transformation in the way we teach and learn. However, despite AI's enormous potential to improve the efficiency and effectiveness of education, there are a number of challenges that need to be overcome. The purpose of this research is to provide readers with the view that apart from the many positive sides of AI, there are also negative sides. This research focuses on the negative side of using AI in the education sector. The method used is library research. However, if managed wisely, the use of AI in education can provide significant benefits. For example, AI can be used to personalize learning, enabling teaching tailored to each student's individual needs. Additionally, AI can help in automated grading, freeing up teachers' time to focus on direct interactions with students. By considering existing challenges and exploiting the opportunities offered by AI, education can make significant progress in improving its quality and accessibility. Therefore, further research and development is needed to overcome technical and ethical obstacles to the application of AI in education, while ensuring that its benefits are widespread and non-discriminatory.

Artificial intelligence for teaching and learning in schools: The need for pedagogical intelligence

Artificial intelligence (AI) has been hailed for its potential to revolutionize teaching and learning practices. Undoubtedly, there has been development, but has it transferred to a new pedagogical trend? Indeed, research shows more tools, software, etc., built through AI, but there is still a limited understanding of its pedagogical impact. This review aims to assess whether AI has indeed led to new pedagogical trends in education using a Human Center AI framework. To accomplish this, a systematic review of research on the pedagogical applications of AI in K-12 contexts was conducted, following the PRISMA guidelines. The review involved an inductive coding analysis of a comprehensive search across WoS, Scopus, and EBSBU. From a pool of 3277 publications spanning 2019 to 2023, 183 papers met the inclusion criteria for detailed analysis. Six categories emerged: Behaviorism, Cognitivism, Constructivism, Social Constructivism, Experiential Learning, and Community of Practices. The findings of this research provide a promising perspective on synthesizing the results based on the pedagogical framework that describes AI implementation. While technological advancements have improved AI capabilities, the application of AI in education largely follows the same principles of previous technologies. This research suggests that the failure to transform education through AI stems from a lack of consideration of Gardner's proposed ninth intelligence type—pedagogical intelligence. Furthermore, this paper offers a critical analysis of the HCAI framework and proposes an adaptation called Pedagogical Centered AI (PCAI) for designing and using AI in K-12 education. Final discussions highlight the implications and future perspectives of AI in educational settings.

Application of Artificial Intelligence in Chinese Education based on Bibliometric Analysis

In the last decade, artificial intelligence (AI) has been widely used in education in China. Many scholars have carried out research on the theory of the integration of AI and education and have produced a lot of achievements. In this paper, CiteSpace software is used to visually analyze the research status, progress, hotspot and trend of the application of AI in education in China from the core database of China National Knowledge Net. According to the analysis of the results, it is suggested that educational AI policy and future research should be constructed mutually.AI in education co-constructs a three-dimensional pattern of researchers, research institutions and policy promoters; Focus on the high-quality, scientific and cross-field comprehensive development of AI in education field; Educational AI pays attention to the diversified research of quality combination.

IMPACT OF GENERATIVE AI ON EDUCATIONAL SECTOR

This study looks into how generative artificial intelligence (AI) is affecting the field of education. The study examines the possible advantages of using generative AI into instruction, such as more individualized learning opportunities, enhanced accessibility, and creative teaching strategies. The study also recognizes and examines the moral issues raised by the application of AI in education, highlighting the significance of upholding academic honesty and openness. It draws attention to the necessity of cautious application in order to guarantee that AI fosters fruitful learning results. The suggested research technique describes a mixed methods strategy that combines quantitative data analysis with qualitative information from surveys and interviews. The goal of the project is to provide best practices and standards for the appropriate integration of generative AI in education, while also identifying the potential and problems that this technology presents. The anticipated results include a thorough comprehension of how generative AI will affect education and how it might improve learning opportunities, ethical issues for responsible usage, and the identification of possible problems and solutions. In the end, the research hopes to promote a more inclusive and productive learning environment by aiding in the creation of useful frameworks for incorporating AI into educational settings. The education industry has drastically evolved in recent years, thanks to the remarkable advancements made by artificial intelligence. With the integration of generative AI technology, educators and students are now presented with a wealth of possibilities and opportunities. As AI continues to advance further, it holds great potential for revolutionizing education as we know it through improved efficiency measures that personalize learning experiences while enhancing overall student outcomes. Harnessing this power-packed tool in teaching environments creates an opportunity for educational institutions across various sectors allowing them efficient intelligent assessment tools coupled with personalized tutoring provisions towards addressing classroom weaknesses resulting in custom-made lesson plans aimed at betterment of individual academic progress developed using predictive models creating ample time such that teachers can focus solely on providing tailored instruction & support based exclusively around their Student's requirements& specifications. This groundbreaking technological development provided meaningfully leveraging Generative Intelligence efforts promises nothing short but will be instrumental when shaping how Education is structured from henceforth enabling automation capabilities within the Administrative tasks management system,& content-building-The advantages come twofold-Enhancement not only resides generally concerning Upgrade Learning Experience situations; there exist tailor solutions projecting Speaker understanding regarding distinctive needs pupils have always had throughout all levels ultimately leading to Developmental Progression heights hitherto attainable anticipated sooner than later.

The Ethical Challenges of Educational Artificial Intelligence and Coping Measures: A Discussion in the Context of the 2024 World Digital Education Conference

Artificial intelligence (AI), as the core technology of the fourth industrial revolution, has been widely deployed in many areas, bringing tremendous changes to human society. At the same time, AI has also instigated a variety of ethical issues regarding basic human rights, social order, private safety, and more. In order to maintain a balance between technological development and the ethics of AI, governments of various countries and international organizations are working to develop AI regulations and ethical norms. A forum themed “Artificial Intelligence and Digital Ethics” was held as a side event during the 2024 World Digital Education Conference (WDEC), showcasing the Chinese government’s adherence to the ethical notion of “human-centered AI” and the principle of “digital for good” in using AI in digital education. The forum emphasized the importance of establishing the ethics of educational AI for circumventing relevant ethical risks and creating healthy environments for the digital transformation of education. Based on the forum’s theme, this article seeks to set forth the necessity of formulating a code of ethical norms for educational AI and to explore pathways to building an ethical framework in this regard in order to provide insights into the rational application of AI in education and promote the sustainable development of digital education.

Towards a New Conceptual Model of AI-Enhanced Learning for College Students: The Roles of Artificial Intelligence Capabilities, General Self-Efficacy, Learning Motivation, and Critical Thinking Awareness

In the aftermath of the COVID-19 pandemic, college students have faced various challenges that could negatively impact their critical thinking abilities due to disruptions to education, increased stress and anxiety, less social interaction, and the advancement of distance learning relying more heavily on digital tools. With the increasing integration of AI technology across sectors, higher education institutions have deployed various AI capabilities for intelligent campuses and modernized teaching. However, how to fully utilize AI capabilities to promote students’ thinking awareness on learning effectiveness is still not clear, as critical thinking is an essential skill set holding significant implications for college students’ development. This research adopts the resource-based theory (RBT) to conceptualize the university as a unified entity of artificial intelligence (AI) resources. It aims to investigate whether AI capabilities can foster critical thinking awareness among students by enhancing general self-efficacy and learning motivation. In particular, it examines the causal relationships between AI capabilities, general self-efficacy, motivation and critical thinking awareness. Primary data was collected through a questionnaire administered to 637 college students. Structural equation modeling was employed to test hypotheses pertaining to causality. The results showed that AI capabilities could indirectly enhance students’ critical thinking awareness by strengthening general self-efficacy and learning motivation, but the effect on critical thinking awareness was not significant. Meanwhile, general self-efficacy significantly affected the formation of learning motivation and critical thinking awareness. This indicates that AI capabilities are able to reshape the cognitive learning process, but its direct influence on thinking awareness needs to be viewed with caution. This study explored the role of AI capabilities in education from the perspective of organizational capabilities. It not only proves how AI facilitates cognition, but also discovered the important mediating role of general self-efficacy and motivation in this process. This finding explains the inherent connections between the mechanism links. Furthermore, the study expands research on AI capabilities research from the technical level to the educational field. It provides a comprehensive and in-depth theoretical explanation theoretically, guiding the practice and application of AI in education. The study is of positive significance for understanding the need for the future development of the cultivation of critical thinking awareness talents needed for future development through AI capabilities in education.

Features, Components and Processes of Developing Policy for Artificial Intelligence in Education (AIED): Toward a Sustainable AIED Development and Adoption

ABSTRACT Governments and private sectors are now putting in place the needed resources and infrastructure to harness the power of emerging technologies in education. One of these technologies is Artificial Intelligence (AI) which gained increasing attention due to its potential to enhance learning and teaching experiences, hence achieving better learning outcomes. However, AIED also comes with several concerns that raise continuous questions about its safe and effective adoption. The application of AIED needs to be planned and executed properly. One of the basic requirements for this to happen is that a comprehensive national policy on the use of AIED is put in place to guide its implementation and evaluate its effectiveness. Limited information exists in the literature on how to write an AIED policy. To address this research gap, this study therefore discusses the features, major components and processes that countries are advised to adopt for a comprehensive AIED policy development. Specifically, this study highlights four features for a good AIED policy, namely contextual, consultative, dynamic, and, implementable and measurable. It further proposes seven steps for an AIED policy development, namely (1) pre-drafting consultation, (2) stakeholder survey, (3) writing draft policy, (4) discussion on draft policy, (5) adoption and communication of policy document, (6) policy implementation plan, and (7) policy evaluation.

Using an Artificial-Intelligence-Generated Program for Positive Efficiency in Filmmaking Education: Insights from Experts and Students

In recent years, despite the widespread success of artificial intelligence (AI) across various domains, its full potential in the field of education, particularly in filmmaking education, remains largely untapped. The purpose of this study is to explore the application of AI-generated programs in filmmaking education to address existing shortcomings in curriculum design. We employed a comprehensive approach, starting with an extensive review of existing filmmaking courses and AI-recommended courses. Subsequently, two rounds of in-depth interviews were conducted, involving both experts and students, to gain profound insights. We utilized user journey maps to visualize the participants’ experiences and feedback, complemented by a mixed-methods analysis approach for a comprehensive data assessment. The study revealed that both the experts and the students derived positive benefits from AI-recommended courses. This research not only provides a fresh perspective on the practical applications of AI in filmmaking education but also offers insights for innovation in the field of education. Theoretically, this study establishes a new foundation for the application of AI in education. In practice, it opens up new possibilities for filmmaking education and promotes the development of cutting-edge teaching methods. Despite limitations in sample size and geographical scope, this study underscores the immense potential of AI in filmmaking education. It provides directions for future research to deepen our understanding of AI’s impact on education.

The Rise of Hybrid Educators

Highlights We live in a technology-driven age, so the education field must rationally consider chatbots powered by artificial intelligence (AI). Faced with increasing application of AI in education, teachers should be reflective educators, and students should be self-educators. AI chatbots will evolve into a new prosthesis before being institutionalized into the fabric of school education. Reflective, institutionalized, self-educators foreshadow the future rise of hybrid educators.

Artificial Intelligence: The Future of Education

Artificial Intelligence (AI) has the potential to transform the way we teach and learn. In recent years, there has been a growing interest in the application of AI in education, with a range of initiatives and products emerging in the market. This review article provides an overview of the literature on the use of AI in education, focusing on the following areas: personalized learning, intelligent tutoring systems, natural language processing, gamification, and ethics.The article begins by discussing personalized learning with AI, highlighting the potential benefits of using AI to tailor learning experiences to individual students' needs and preferences. The article then explores intelligent tutoring systems, which use AI to provide students with personalized feedback and support. The use of natural language processing in education is also discussed, including the potential for AI to facilitate language learning and communication skills. The article then examines gamification and AI, discussing how gamification can be used to increase student engagement and motivation, and how AI can enhance the effectiveness of gamified learning environments. The ethical considerations of using AI in education are also discussed, including issues around privacy, bias, and transparency. the article concludes by summarizing the current trends and future directions in the use of AI in education. The potential of AI to revolutionize education is significant, but there are also challenges to be addressed. The review article highlights the need for further research to fully understand the potential of AI in education and to ensure that its use is ethical and effective. Overall, the review article suggests that AI has enormous potential to transform the future of education and highlights some of the key areas where AI is likely to have the most impact.

Exploration on College Ideological and Political Education Integrating Artificial Intelligence-Intellectualized Information Technology.

In recent years, with the vigorous development and application of Artificial Intelligence (AI), the application of AI in education is becoming more and more extensive. This study makes a theoretical analysis of AI-Intellectualized Information Technology (IT). Discrete Cosine Transform (DCT)-Based Speech Recognition (SR) and Genetic Algorithm (GA)-Based Image Recognition (IR) are used to analyze the College Ideological and Political Education (IAPE). The research findings prove that the advantages of integrating AI-intellectualized IT on College IAPE outweigh the disadvantages. The improvement of technological development, which accounts for 71.17% of undergraduate gains, is the most significant, and the smallest gain is technology coverage, which is 36.80%. Overall, 57.21% are interested in new technology, and the students' enthusiasm accounts for 30.77%. Most of the students focus on the innovation performance of technology, accounting for 75.92%. With an average influence of 89.04% on undergraduates, technology has the largest impact, followed by 85.78% on students with masters or higher degrees. The largest impact of diversified teaching methods for all students is 62.48%. This study provides some reference values for AI-intellectualized IT research and analysis, as well as students' IAPE.

A multi-perspective study on Artificial Intelligence in Education: grants, conferences, journals, software tools, institutions, and researchers

With the rapid development of artificial intelligence (AI) technologies and a continuously growing interest in their application in educational contexts, there has been significant growth in the scientific literature in relation to the application of AI in education (AIEd). This study aims to present multiple perspectives on the development of AIEd in terms of relevant grants, conferences, journals, software tools, article trends, top issues, institutions, and researchers to provide an overview of AIEd for its further development and implementation. With this study, we contribute to the research field by enabling educators and scholars to understand the status and development of relevant grants and publications concerning AIEd. Also, findings concerning active actors can help educators and scholars identify the active researchers and institutions in the research on AIEd. Furthermore, researchers and educators are able to identify relevant journals and be more aware of major issues in AIEd studies. In addition, we also highlight the significance and necessity of the launch of the new Elsevier journal AIEd-related journal named Computers & Education: Artificial Intelligence . • Present a multi-perspectives study on Artificial Intelligence in Education (AIEd). • Analyze relevant funds, conferences, journals, software, institutions, and scholars. • Demonstrate increasing interest in and impact of AIEd. • Highlight the significance and necessity to launch specialized AIEd journal. • Introduce a new Elsevier journal Computers & Education: Artificial Intelligence.

Systematic review of research on artificial intelligence applications in higher education \u2013 where are the educators?

According to various international reports, Artificial Intelligence in Education (AIEd) is one of the currently emerging fields in educational technology. Whilst it has been around for about 30 years, it is still unclear for educators how to make pedagogical advantage of it on a broader scale, and how it can actually impact meaningfully on teaching and learning in higher education. This paper seeks to provide an overview of research on AI applications in higher education through a systematic review. Out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis, according to explicit inclusion and exclusion criteria. The descriptive results show that most of the disciplines involved in AIEd papers come from Computer Science and STEM, and that quantitative methods were the most frequently used in empirical studies. The synthesis of results presents four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education.