Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

This work-in-progress paper employs a machine learning method for the automated analysis of research interests in Artificial Intelligence in Education (AIED) at scale. We aim to analyze the essential techniques and critical educational problems studied by researchers in five AIED-related conferences and journals between 2010 and 2022. We trained and compared different machine learning models and feature extraction techniques to achieve the research objective. After comparing different models and hyperparameter combinations, our classifier achieves an accuracy of 0.87 and Cohen's kappa of 0.80. Based on the classification results, we identified the top 10 most frequent keywords within each category for every four year period over the past 12 years. Using the classifier, the 10,723 keywords from 2,684 articles were classified into three categories: educational foci, technical solutions, and AIED applications. We find that 'natural language processing' and 'machine learning' are the primary technical keywords in AIED research, and 'deep learning' and 'artificial intelligence' are the trending technical keywords since 2017. Meanwhile, 'massive open online courses', 'self-regulated learning', 'feedback', 'collaborative learning', and 'online learning' are the top educational foci in the field over the last 12 years. 'Intelligent tutoring systems', 'educational data mining', 'knowledge tracing', and 'learning analytics' continue to receive attention as AIED applications of sustained interest. This study helps to understand the educational foci and technical solutions of AIED research at scale and provides insights into the future of AIED research.

The application of Artificial Intelligence or AI in education has been the subject of academic research for more than 30 years. The field examines learning wherever it occurs, in traditional classrooms or at workplaces so to support formal education and lifelong learning. It combines interdisciplinary AI and learning sciences (such as education, psychology, neuroscience, linguistics, sociology and anthropology) in order to facilitate the development of effective adaptive learning environments and various flexible, inclusive tools. Nowadays, there are several new challenges in the field of education technology in the era of smart phones, tablets, cloud computing, Big Data, etc., whose current research questions focus on concepts such as ICT-enabled personalized learning, mobile learning, educational games, collaborative learning on social media, MOOCs, augmented reality application in education and so on. Therefore, to meet these new challenges in education, several fields of research using AI have emerged over time to improve teaching and learning using digital technologies. Moreover, each field of research is distinguished by its own vision and methodologies. In this article, to the authors present a state of the art finding in the fields of research of Artificial Intelligence in Education or AIED, Educational Data Mining or EDM and Learning Analytics or LA. We discuss their historical elements, definition attempts, objectives, adopted methodologies, application examples and challenges.

<span lang="EN-US">The data-driven development of education through Learning Analytics in combination with Artificial Intelligence is an emerging field in the education sector. In the field of Artificial Intelligence in Education, numerous studies and research have been carried out over the past 60 years, and since then drastic changes have taken place. In the first part of this paper we present a brief overview of the current status of Learning Analytics and Artificial Intelligence in education. In order to develop a better understanding of the relationship between Learning Analytics and Artificial Intelligence in education, we outline the relationship between the two phenomena. The results show that the previous studies only vaguely distinguish between them: the terms are often used synonymously. In the second part of the paper we focus on the question why the European market currently has hardly any real applications for Artificial Intelligence in education. The research is based on a meta-investigation of data-driven business models, in particular the so-called Educational Technology providers. The core of the analysis is the question of how data-driven these companies really are, how much Learning Analytics and Artificial Intelligence is applied and whether there is a causal connection between the growth of the Educational Technology market and the application relevance of Artificial Intelligence in Education. In the scientific and public discourse, we can observe a distortion between the theoretical-conjunctive understanding of the application of Artificial Intelligence in Education and the current practical relevance.</span>

The object of the study is the status, segment analysis, dynamics and prospects of the global markets for higher education and artificial intelligence in higher education. The analysis and systematization of literature data allowed to summarize the results of research in the field of marketing research of higher education markets and artificial intelligence in higher education. To conduct a marketing analysis, the method of literature search and the method of analysis were applied. The main trends, volumes, rates and factors of growth of the higher education and artificial intelligence markets in the field of higher education, as well as some limitations of their development are presented. The analysis of the higher education market is carried out by the following segments: geographical regions, mode of study, educational levels, sources of income, educational institutions, and the market of artificial intelligence in education – market components, deployment mode, technologies, applications, geographical regions. The potential demand and volume of higher education and artificial intelligence markets in the field of higher education in different countries of the world are determined, the dynamics and competition in the world markets are tracked. The state of the art and prospects for further research in the field of higher education and artificial intelligence in education are summarized. The following scientific methods were used: the method of searching for literature data on the topic under study; the method of analyzing literary sources; comparative analysis of different methodological approaches; content analysis of documents; the method of systematization and classification in conducting research on the achievements of modern science and technology in the field of higher education and the use of artificial intelligence in higher education. The systematization of literature data allowed to present the problems of higher education and the use of artificial intelligence in higher education in the form of tables and diagrams, which gives a certain advantage for understanding and using the material.

Survey data on students' perceptions, knowledge, and use of learning analytics (LA) and generative artificial intelligence (GenAI) for the personalization of learning.

The purpose of the study is to develop a model of a hybrid intelligent educational environment according to the intellectual partnership between humans and artificial intelligence, based on an analysis of the practice of using artificial intelligence in school and university education. To achieve this goal, it was necessary to solve the following tasks: to assess the opinions of participants in educational relations about the use of artificial intelligence in education, the associated threats and opportunities; to identify the features of using artificial intelligence in higher education; and to develop methodological approaches to forming an intellectual partnership between students and artificial intelligence as the basis for a model of a hybrid intelligent educational environment. Materials and methods. The study used a range of methods, including inductive-deductive, statistical and comparative analysis, modeling, and visualization of graphical data.The information base was compiled from scientific publications, materials of the All-Russian Public Opinion Research Center, research results of the scientists of the Higher School of Economics, open sources of the Internet. Results. The integration of artificial intelligence into the educational environment is accompanied by a number of problems (technological, social, psychological, ethical), which requires the management of educational organizations to take them into account when creating a new pedagogical ecosystem, in which artificial intelligence acts as a new tool of the educational process. An analysis of the parental community’s opinions regarding the use of artificial intelligence in children’s education revealed diverse assessments: while acknowledging the high educational potential of the technology, there were also concerns about the associated threats, with the main concern being the potential decline in the quality of knowledge. The article identifies the broad opportunities for using artificial intelligence by students and teachers in school and university education. It also highlights the fundamental differences in the use of artificial intelligence in higher education, which are related to the depth and complexity of solving scientific and educational tasks. The article proposes methodological approaches to creating an intellectual partnership between students and artificial intelligence, aimed at preventing the passive use of technology that leads to intellectual stagnation. The model of a hybrid intellectual educational environment is developed, which requires not only the modernization of technological infrastructure, but also pedagogical and cultural transformation based on ethical principles. The tasks have been formulated to train new qualified personnel who can use artificial intelligence technology as a tool for their professional activities. Conclusion. In the era of unprecedented growth in technological achievements and the widespread and deep penetration of artificial intelligence into all areas of life, including the educational environment, the modern education system is in the process of reevaluating the role and place of artificial intelligence in the learning, development, and upbringing of young people. Recognizing the need to adapt to new technological trends, educational organizations are carefully assessing the potential and threats associated with the implementation of artificial intelligence in the educational process, as well as evaluating their own resources to implement the concept of “collaborative intelligence”, which combines human and artificial intelligence. The intellectual partnership of participants in educational relationships with artificial intelligence has a high potential for solving pedagogical tasks: artificial intelligence, by solving routine tasks, frees up the teacher for creative work, emotional support, and the development of new methods for forming meta-cognitive competencies among students; artificial intelligence expands scientific and educational opportunities for students in a proactive position of using technology.

Artificial intelligence technology plays a decisive role in various spheres of life, including education. Modern preschools are faced with the need to adapt to the requirements of the modern world, where technology is a mandatory component. The article defines the regulatory and legal principles of using artificial intelligence technologies in the field of education. Based on the study and systematization of the results of scientific research, directions and methods of using artificial intelligence in the educational field have been identified. Scientific-pedagogical guidelines for the use of generative models of artificial intelligence in a preschool education institution are justified from the author's point of view. Modern possibilities of using artificial intelligence technology in the educational process of a preschool education institution are presented, in particular, the features of using artificial intelligence by parents of preschool children. Also, practical aspects of the use of artificial intelligence by specialists in a preschool education institution are proposed, in particular, ChatGPT, Quillbot, Google Gemini, Vocal Remover. The importance of the right approach to the implementation of artificial intelligence in the educational process to ensure efficiency and safety for children is emphasized. The results of the surveys of parents of preschoolers and specialists of preschool education institutions regarding the potential of using artificial intelligence in preschool education for the development of children are summarized, which requires a careful approach and cooperation between teachers, parents, and the administration of preschool education institutions. The use of artificial intelligence in preschool education is a promising direction that can provide support for preschool education specialists, make the learning process more interesting for children, and contribute to their intellectual development. Therefore, research and development of practices for the use of artificial intelligence in preschool education is an important component of the effective implementation of these technologies.

The application of artificial intelligence in education is one of the focal research today. Researchers have discovered that with the continuous development of artificial intelligence, various artificial intelligence are being utilized in primary and secondary education. However, many issues in this field still lack a unified explanation and understanding. Therefore, the research theme of this paper focuses on the advantages and challenges of using artificial intelligence in education. Based on an analysis of relevant literature and survey data, this study explores the advantages and challenges of artificial intelligence in education. The research findings indicate that artificial intelligence can provide personalized education, offer abundant educational resources for teachers and students, and provide timely feedback on student progress. Thus, enhancing learning outcomes. However, the application of artificial intelligence in education still faces challenges such as funding limitations, inadequate policy support, privacy concerns, varying levels of teacher acceptance, and a lack of standardized curriculum. Nevertheless, the use of artificial intelligence in education holds tremendous potential. In the future, it is necessary to formulate policy and standardization at the national level and address issues such as information security and privacy protection to promote the comprehensive application and development of artificial intelligence in education.

In this study, we review 1830 research articles on artificial intelligence in education (AIED), with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary research field from 2010 to 2019. A novel three-step approach in the analysis of the keyword co-occurrence networks (KCN) is proposed to identify the knowledge structure, knowledge clusters and trending keywords within AIED over time. The results reveal considerable research diversity in the AIED field, centering around two sustained themes: intelligent tutoring systems (2010-19) and massive open online courses (since 2014). The focal educational concerns reflected in AIED research are: (1) online learning; (2) game-based learning; (3) collaborative learning; (4) assessment; (5) affect; (6) engagement; and (7) learning design. The highly connected keywords relevant to analytic techniques within this field include natural language processing, educational data mining, learning analytics and machine learning. Neural network, deep learning, eye tracking, and personalized learning are trending keywords in this field as they have emerged with key structural roles in the latest two-year period analyzed. This is the first article providing a systematic review of a large body of literature on artificial intelligence in education, and in it we uncover the underlying patterns of knowledge connectivity within the field, as well as provide insight into its future development. The three-step multi-scale (macro, meso, micro) framework proposed in this study can also be applied to map the knowledge development in other scientific research areas.

In order to explore the maturity of online concerts and the digital content of music resources, this article analyzes the role of artificial intelligence in music education, discusses the application of artificial intelligence in music education and the development trend of artificial intelligence in education, and studies the quality of vocal music teaching based on artificial intelligence technology. In this paper, ARM and SA algorithms, as well as internal and external probability algorithms, are combined for research and analysis. Through this study, the authors show that human intelligence skills have a certain impact on vocal music teaching, with an impact rate of 56.42%. It can be seen that artificial intelligence can directly optimize the level of music teachers and promote the improvement of teachers' teaching quality and efficiency. This article improves the effective understanding of artificial intelligence in music education and strengthens the scientific and rational application of artificial intelligence in education.

Today, artificial intelligence has penetrated all areas of human activity, including its technologies being actively implemented in the educational process. This article is devoted to issues related to the implementation of artificial intelligence in higher education. The purpose of this work was to determine the prospects and features of using artificial intelligence in the educational process of higher education. The novelty of the study lies in a comprehensive analysis of the areas of artificial intelligence use, its capabilities, risks, and limitations. The research methodology is based on a systems approach using theoretical and experimental methods. The article provides a brief analysis of the work of foreign and Russian researchers on the application of artificial intelligence. As part of the theoretical stage of the study: the main areas of artificial intelligence use are identified, which are systematized into three groups (educational process management, educational process organization, teacher optimization); the content and key benefits are determined for each group; the risks and limitations of using artificial intelligence in education are identified (technical, pedagogical, ethical, social and economic, legal). The experimental portion of the study involved conducting a survey among students and faculty at higher education institutions in the Trans-Baikal Territory and analyzing the results to determine the extent of artificial intelligence implementation in higher education and assess its impact on the educational process. The study demonstrated the need for careful implementation of artificial intelligence in higher education, maintaining a balance between technology and the human factor. Prospects for further research may include developing methods for the effective use of artificial intelligence in higher education.

The current study aims to reveal possible opportunities for applying artificial intelligence in higher education, and to identify the most important challenges that such application faces and the maximum benefits that can be acquired from employing artificial intelligence techniques in developing the educational process and the educational services in higher education institutions. This study followed the descriptive analytical approach in addressing the topic of applying artificial intelligence in higher education by reviewing the literature and previous studies that addressed this topic. The study concluded that it is possible to benefit from the application of artificial intelligence in higher education in the fields of teaching, learning, administration, research, and others, if the requirements of this application are dealt with effectively and the facilities that support the use of artificial intelligence techniques are provided. The study recommends confronting the challenges that weaken the effectiveness of the application of artificial intelligence in higher education. The most important challenges in this regard are: the lack of educational policies related to the application of artificial intelligence in education, the weakness of the infrastructure needed to supports the use of artificial intelligence techniques, the need to train academics and learners on how to deal with new applications, and the lack of due awareness of the importance of artificial intelligence applications and its role in developing higher education. KEY WORDS: artificial intelligence, higher education, opportunities, challenges, foreseeing the future

Application and theory gaps during the rise of Artificial Intelligence in Education

The importance of artificial intelligence (AI) is growing in all economic sectors and thus also in higher education. In recent years, there have been significant developments in this concept of "Artificial Intelligence in Education (AIED)". The purpose of this study was to find out how the concept of artificial intelligence can be applied to teaching and learning in higher education and the implications of the use of artificial intelligence in higher education. The impact of the development of technologies on learning is often studied on the methods and scope of learning and teaching. Artificial intelligence enables higher education services to become easily accessible with extraordinary speed, not only in the classroom but also outside the classroom. This report seeks to explore how AI will become an integral part of universities and seeks to examine its immediate and future impact on various aspects of higher education. The challenges of implementing AI in these institutes were also explored. As artificial intelligence (AI) research in education increases, many researchers in the field believe that the role of teachers, schools and leaders in education will change. In this regard, the aim of this study is to investigate which are the possible scenarios for the arrival of artificial intelligence in education and what impact it can have on the future of schools. In this research, it confirmed that artificial intelligence has been widely adopted and used in various forms in education, especially educational institutions. Artificial intelligence was initially implemented in the form of computers and computer-related technologies, moving to web-based and web-based intelligent educational systems, and finally with the use of embedded computing systems and other technologies such as humanoid robots and web-based chatbots teachers & tasks and assignments independently or with tutors. With these platforms, teachers could perform various administrative tasks such as grading and Work more effectively and efficiently and achieve higher quality in your learning activities. On the other hand, because the systems use machine learning and adaptability, the curriculum and content are adapted which improved uptake and retention, which improved the student experience and the overall quality of education.

The purpose of the study is to predict possible trends in the impact of generative artificial intelligence, in particular ChatGPT technologies, on education. Predictive estimates are formed on the basis of expert discussions of the consequences of using these digital technologies in education, which are currently going on in the public space and in the scientific community. The main groups of expert opinions and scientific approaches are being identified and compared, which makes it possible to present a perspective vision of the processes of integrating generative artificial intelligence into education. Analysis and forecasting are mostly carried out on the example of the practice by using generative artificial intelligence in higher education, however, the main provisions and conclusions can be extrapolated to other levels of education.Materials and methods. In the course of the study, methods of qualitative analysis of expert opinions presented in the public space (in the media, social networks, on the websites of educational organizations and analytical agencies, in public speeches), as well as methods of meaningful analysis of scientific publications, were used. Grouping and classification of expert opinions and scientific approaches were carried out. The analysis also used the results of a sociological study conducted by means of online survey of students from the Plekhanov Russian University of Economics on a sample of more than 3 thousand people. Methods of social forecasting were used to form predictive estimates.Results. The analysis made it possible to conclude that public discourse on employing generative artificial intelligence in education is controversial. Five groups of expert opinions were identified regarding the impact of generative artificial intelligence on education, which differ as to the need for its use in educational organizations and the scope of educational transformations that can occur under its influence. The analysis of scientific discussions showed that scientific community has not finally determined the consequences of the practical impact of generative artificial intelligence on the field of education. At the same time, possible promising areas and problem areas of its use are being identified, as well as its potential to initiate new reforms in education. The following possible trends in the integration of generative artificial intelligence into education are predicted: gradual change in the paradigm of education towards creativity-oriented education; increase of the share and scope of using artificial intelligence technologies in education; formation of new legal and ethical standards governing the use of generative artificial intelligence in education; increasing the importance and changing the role of the lecturer.Conclusions. Generative artificial intelligence has all the potential for solving long-term tasks of developing education. However, rapid technological development is inevitably associated with numerous risks, which require the creation of a methodology for using generative artificial intelligence in education, improvement of regulatory framework and solution of ethical problems. A new qualitative level of integration of a human being and artificial intelligence in the educational sphere is the thing of the future. Such integration will contribute to improving the quality of human capital in line with rapidly developing technologies of 5.0 Industrial Revolution.