About this Research Topic
Significant advancements have been made in AI technologies, such as machine learning, natural language processing, and computer vision. AI applications in education encompass adaptive learning systems, intelligent tutoring systems, automated assessment tools, and personalized learning platforms. These technologies have shown promising potential to enhance teaching and learning experiences, improve student outcomes, and optimize administrative processes in educational institutions.
This Research Topic seeks to advance our understanding of the impact, challenges, and opportunities of integrating AI in teacher education. The primary objectives are:
a) To examine the current state of AI integration in teacher education programs globally.
b) To analyze the compatibility between AI and traditional teaching methodologies, including their potential synergies and areas of conflict.
c) To identify the benefits, limitations, and ethical implications of using AI in teacher education.
d) To explore the role of AI in promoting inclusive education and addressing educational disparities.
e) To investigate the necessary digital skills and competencies for teachers to effectively leverage AI in their pedagogical practices.
f) To propose scientifically based guidelines, frameworks, and best practices for integrating AI in teacher education curricula.
The list of topics of interest, without limiting other related themes, can include the following:
1.- Integration of AI in teacher education curricula: Challenges and opportunities
2.- AI-powered personalized learning in teacher education: Benefits and limitations
3.- The role of AI in promoting inclusive education and addressing educational disparities
4.- Ethical considerations in the use of AI in teacher education
5.- AI-based assessment tools and their impact on teacher education
6.- AI and adaptive learning systems in teacher professional development
7.- Teacher roles and responsibilities in the era of AI integration
8.- The impact of AI on student-teacher relationships and social interactions
9.- AI-enabled classroom management: Implications for teacher education
10.- AI-powered intelligent tutoring systems for teacher training
11.- Addressing biases and ensuring fairness in AI algorithms for teacher education
12.- AI and data privacy in educational settings: Challenges and safeguards
13.- AI-powered feedback and its impact on teacher education practices
14.- Building AI literacy in teacher education programs
15.- AI and the future of teaching: Implications for pre-service and in-service teacher training
Regardless of the chosen topic, empirical research with robust quantitative, qualitative, or mixed designs is sought. Empirical studies with samples of questionable representativeness or employing simplistic data analysis procedures will be excluded. Similarly, theoretical papers lacking empirical work will not be accepted unless they are meta-analyses or systematic reviews following an internationally agreed-upon search process (e.g., the PRISMA approach).
This Research Topic seeks to advance our understanding of the impact, challenges, and opportunities of integrating AI in teacher education. The primary objectives are:
a) To examine the current state of AI integration in teacher education programs globally.
b) To analyze the compatibility between AI and traditional teaching methodologies, including their potential synergies and areas of conflict.
c) To identify the benefits, limitations, and ethical implications of using AI in teacher education.
d) To explore the role of AI in promoting inclusive education and addressing educational disparities.
e) To investigate the necessary digital skills and competencies for teachers to effectively leverage AI in their pedagogical practices.
f) To propose scientifically based guidelines, frameworks, and best practices for integrating AI in teacher education curricula.
The list of topics of interest, without limiting other related themes, can include the following:
1.- Integration of AI in teacher education curricula: Challenges and opportunities
2.- AI-powered personalized learning in teacher education: Benefits and limitations
3.- The role of AI in promoting inclusive education and addressing educational disparities
4.- Ethical considerations in the use of AI in teacher education
5.- AI-based assessment tools and their impact on teacher education
6.- AI and adaptive learning systems in teacher professional development
7.- Teacher roles and responsibilities in the era of AI integration
8.- The impact of AI on student-teacher relationships and social interactions
9.- AI-enabled classroom management: Implications for teacher education
10.- AI-powered intelligent tutoring systems for teacher training
11.- Addressing biases and ensuring fairness in AI algorithms for teacher education
12.- AI and data privacy in educational settings: Challenges and safeguards
13.- AI-powered feedback and its impact on teacher education practices
14.- Building AI literacy in teacher education programs
15.- AI and the future of teaching: Implications for pre-service and in-service teacher training
Regardless of the chosen topic, empirical research with robust quantitative, qualitative, or mixed designs is sought. Empirical studies with samples of questionable representativeness or employing simplistic data analysis procedures will be excluded. Similarly, theoretical papers lacking empirical work will not be accepted unless they are meta-analyses or systematic reviews following an internationally agreed-upon search process (e.g., the PRISMA approach).
Keywords: Artificial Intelligence, Teacher Education, Training, Digital Competence, Teaching methods
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
