Abstract

Education has moved beyond imparting information to fostering critical thinking, problem solving, and creativity skills. Future teachers have different educational career paths from traditional teachers in the path of career development, as they have to advance all educational and learning activities using artificial intelligence technology. Teachers will continue to be at the heart of the learning process, but their role will gradually change from a transmitter of information to a guide, facilitator, and coach. Future teachers will act as facilitators of learning, guides and advisors to students and, in addition to technical skills, will have the ability to develop deep connections with students and support their social and emotional development. Using artificial intelligence, we can create intelligent learning systems that respond to each student individually and provide them with personalized learning experiences. However, there are challenges such as maintaining the privacy of students' data that need to be addressed. Education in the digital age is a continuous process based on lifelong learning. Using artificial intelligence and innovative educational approaches, we can envision a future where all students reach their full potential.

Familiarity with digital technologies, data analysis, and the ability to manage and use artificial intelligence tools in the classroom will become part of the essential characteristics of teachers. Artificial intelligence can adapt educational content based on the individual needs and interests of each student by analyzing data about students. This personalization can make learning more efficient and motivating. By using these technologies, teachers can plan more precisely for the progress of students. However, few researches have investigated the educational methods of future teachers in connection with artificial intelligence. The main goal of this research was to identify the educational methods of future teachers based on artificial intelligence and provide a model. In terms of the practical purpose, the present research has been carried out with a meta-synthesis approach in terms of a qualitative method. Choosing a meta-synthesis approach is very suitable for examining a subject such as the educational methods of future teachers in the field of artificial intelligence. This approach comprehensively and systematically analyzes and combines the findings of various researches. The research field included all articles published between 2014 and 2024. The selection of samples has been targeted to the extent of data saturation, which is a screening method from the initial selection of 56 articles based on input criteria (year of publication, profile in reliable scientific databases, study method, and richness of data in terms of depth of analysis) 30 articles in the end was selected for data extraction. The richness of the data was evaluated according to the existence of sufficient details about the subject under study and the use of various qualitative data collection methods (interview, observation, document analysis). Single-authored articles were less selected due to a greater focus on the perspective of a single researcher, and articles with a large number of authors were less likely to be analyzed in depth. 24% of single-authored articles, 43% of two-authored articles, and 33% of more than two-authored articles.

The study tool was reading the texts of the articles and the method of collecting information in a library and electronic way by referring to reliable domestic (SID, Magiran, NoorMagz, IranDoc) and foreign (Emerald, Springer, Elsevier, Google Scholar, Sage Publications) scientific sites. To ensure validity and reliability, four methods of reliability, transferability, verifiability and reliability were used. Validity by in-depth examination of the data and matching them with existing theories, transferability by providing sufficient details of the study context and the possibility of generalizing the results to similar studies, verifiability by providing sufficient evidence to support the claims, and reliability by using systematic methods for data collection and analysis. provided To analyze the data, the method of classifying open, organizing, and inclusive concepts was used according to the differences and similarities of the data, and this process was based on the 7-step model of Sandelowski and Baros. In the first step, the data was read in full and open coding was done. Then, open codes were organized into core codes and finally, comprehensive concepts were extracted from the combination of core codes.

In general, the findings showed that the educational methods of future teachers with artificial intelligence include 118 open concepts, 18 organizing concepts and 9 comprehensive concepts (dimensions). The pattern of identifying the educational methods of future teachers based on artificial intelligence based on nine dimensions (having technological communication, technological attraction of students, using artificial intelligence tools, technological use of educational resources, activity in the educational technological environment, having technological creativity, environmental analysis educational technology, educational technological programming, educational technological evaluation) were compiled.

With the spread of online learning tools, virtual reality and artificial intelligence, teachers must seriously revise their methods. Teachers in the age of artificial intelligence must improve their digital skills. Familiarity with educational tools and technologies based on artificial intelligence is essential for teachers. As a coach, teachers should guide students in the learning process and help them learn independently. Effective communication with students and parents is especially important in the digital age. Teachers should look for new and creative ways to use artificial intelligence in the classroom. Analyzing educational data and using intelligent algorithms will help teachers to meet individual needs. Identify students better and provide them with a personalized learning experience. Students play an active role in this learning environment. AI can help students identify their weaknesses and provide targeted practice. However, in the development and application of educational artificial intelligence technologies, it also has its own ethical and social challenges. Among the concerns is the use of personal data and students' privacy. It is necessary to develop detailed policies and ethical frameworks to protect students' rights and build trust in education systems based on artificial intelligence. To succeed in this transformation, invest in the continuous training of teachers and provide them with access to the necessary resources and tools. The future of education is built by teachers who adapt to changes and use technology as a tool to improve the quality of education.

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