Editorial 18.1

What the paper says

I am excited to announce the official release of Issue 18.1 of JRIT&L. This issue contains the following content: digital competence, videos in teacher education, teachers perceive innovations, hybrid classroom, the implementation of learning apps, assessing the online teaching readiness, hybrid instructional design, effectiveness of massive open online courses (MOOCs), feedback strategies and learning improvement, and innovative curriculum design.Recently, the application of artificial intelligence has continued to expand, and discussions about its use in both basic and higher education have deepened. The scope of teaching and learning primarily focuses on the following applications: personalized learning, data-driven learning, science, technology, engineering and mathematics (STEM) education, mobile learning, intelligent tutoring systems and adaptive learning.The discourse on artificial intelligence (AI) in education has shifted from whether it should be applied to how it should be used. Therefore, we suggest that related research should prioritize exploring how to implement AI effectively rather than justifying its necessity. To this end, we look forward to more data-supported empirical research, particularly in the field of personalized learning.Over the years, as personalized learning has gained widespread attention, it has gradually permeated all areas of education – from compulsory education to higher education, from general education to special education and from subject-specific instruction to education management.With the help of AI, personalized learning and the valuable resources it generates have become particularly important, as it is essential for educators to understand its key elements. The development of AI acts as an enhancement to personalized learning, effectively addressing diverse learning styles and the needs of special education. Whether personalized learning is guided by teachers or driven by students, it has significantly evolved due to AI’s ability to efficiently collect, analyze and process of data, making it a powerful and reliable tool for personalized education.Furthermore, AI-driven learning technologies have the potential to support all learners. This is also highly relevant to traditional differentiated instruction, as it enables teachers to tailor learning experiences based on students' unique learning methods, creating more personalized and effective learning paths.With the emergence of AI tools, personalized learning has gained prominence. Meeting the needs of every student, leveraging their strengths while addressing their weaknesses, and utilizing AI to support diverse learning styles will soon become a reality. Practice has shown that allowing students to determine their own learning paths is one of the key methods for achieving effective learning.We encourage our authors to conduct further research and exploration in this area.The development of AI and the inevitable educational transformations it brings are matters that every educational researcher must consider. These changes in education are unavoidable. In terms of teaching and learning, we look forward to more high-quality articles that contribute to advancements in curriculum design, instruction and assessment.