Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education

This exploratory review attempted to gather evidence from the literature by shedding light on the emerging phenomenon of conceptualising the impact of artificial intelligence in education. The review utilised the PRISMA framework to review the analysis and synthesis process encompassing the search, screening, coding, and data analysis strategy of 141 items included in the corpus. Key findings extracted from the review incorporate a taxonomy of artificial intelligence applications with associated teaching and learning practice and a framework for helping teachers to develop and self-reflect on the skills and capabilities envisioned for employing artificial intelligence in education. Implications for ethical use and a set of propositions for enacting teaching and learning using artificial intelligence are demarcated. The findings of this review contribute to developing a better understanding of how artificial intelligence may enhance teachers’ roles as catalysts in designing, visualising, and orchestrating AI-enabled teaching and learning, and this will, in turn, help to proliferate AI-systems that render computational representations based on meaningful data-driven inferences of the pedagogy, domain, and learner models.

Educating for the future? Mapping the emerging lines of precision education governance

Managing the future has become one of the major focuses of global governance in education. In its current mode, education seems unable to answer the needs and interests of the market and future megatrends, such as globalisation and digitalisation. Calls for precision education to introduce the usage of digital platforms, artificial intelligence in education, and knowledge from the behavioural and life sciences are getting a foothold in widening powerful networks of strengthening global governance and EdTech business. By bringing together some of the emerging changes in education governance, in this article we argue for a new constitution of governance, precision education governance. Precision education governance combines three overlapping and strengthening lines of governance: (i) global governance of education, (ii) marketisation, privatisation and digitalisation, and (iii) behavioural and life sciences as the basis for managing the future education. In the article, we highlight the importance in bringing these so far separately studied lines together to understand how they shape the aims and outcomes of education, knowledge and understanding of human subjectivity more thoroughly than before.

The concept of using artificial intelligence in distance learning

The article presents an analysis of possible directions of using artificial intelligence in education. It is shown that artificial intelligence in modern distance education contributes to its further development in the direction of modernization and has a significant impact, especially on the modern distance learning system. The requirements for artificial intelligence on the part of education and the negative consequences of the use of artificial intelligence and problems that may affect the quality of education are analyzed. The possible directions of work in terms of the development of artificial intelligence related to the development of knowledge representation models, the creation of knowledge bases forming the core of the expert system are considered. Attention is drawn to the fact that an intelligent learning system should be able to perform various functions of a teacher (to help in the process of solving problems, to determine the cause of students’ mistakes, to choose the optimal educational impact) almost as intelligently as a person does. Attention is also paid to such a direction as the use of intelligent chat-bots or conversational agents and their applications.

Synthetic Governance: On the Impossibility of Taming Artificial Intelligence in Education

This paper claims it is impossible to tame Artificial Intelligence in education. The paper is not advocating that AI should be used in an unfettered way in education. Rather, the paper suggests that despite ongoing policy attempts to regulate AI, these policy moves are unlikely to succeed due to a synthesis of machines and humans in education governance. The paper briefly outlines attempts to tame AI, and proposes that rather than considering taming AI, a new politics of education may be necessary.

Artificial Intelligence in Education (AIEd): from Applied Problems of Informatization to Studying a Topic in a Computer Science Course

The article provides an overview of two main possibilities of using artificial intelligence in education: as new educational tools and as the development of the theoretical and practical foundations of artificial intelligence in the school computer science course. A comparison of approaches to the use in education and the study of artificial intelligence issues at the level of secondary general education in different countries is given. The development of the topic at all levels of general education is considered.

A Common Framework for Artificial Intelligence in Higher Education (AAI-HE Model)

This research aims to 1) Develop a common framework for artificial intelligence in higher education (AAI-HE model) and 2) Assess the AAI-HE model. The research process is divided into two stages: 1) Develop an AAI-HE model, and 2) Assessment the model. The sample consists of five experts chosen through purposive sampling. The data is analyzed by means and standardized deviations statistically. The research result shows that 1) the AAI-HE model consists of seven key components which are 1.1) User Interactive Components and Technology of AI, 1.2) Components and Technology of AI, 1.3) Roles for Artificial Intelligence in Education 1.4) Machine Learning and Deep Learning 1.5) DSS Modules 1.6) Applications of Artificial Intelligence in Education, and 1.7) AI to enhance campus efficiencies, and 2) The result of the assessment of the AAI-HE model is rated as absolutely appropriate overall.