I am pleased to announce the official release of Issue 18.2 of JRIT&L. This issue contains the following topics: artificial intelligence (AI) factors that impact educational fields and teachers' innovation under these factors; STEM curricula and teaching; teaching and learning for students with learning disabilities; assessment and quality of teaching and social media usage and academic performance.
As we all know, AI is having an increasingly broad impact on education, bringing both opportunities and challenges. For our journal, in future publications, we hope to collaborate with authors to focus more on the impact of AI, particularly its influence on teaching and learning.
Since 2025, AI has advanced rapidly, sparking discussions across all industries about how to adapt. According to Gallup (2025), the application of AI in the workplace is accelerating. Over the past two years, the percentage of US employees who say they use AI several times or more annually has nearly doubled, from 21% to 40%. Growing evidence shows that educators, including teachers, are increasingly searching for AI-generated information, making professional development training crucial to address the challenges of AI. According to RAND Corporation (2025), “about three-quarters of districts will have provided training on AI use by fall 2025”. It's foreseeable that students' use will also follow. AI seems unstoppable, and it will change the way of teaching and learning.
While the impact of AI on education is still being explored, many education-related software programs have already begun to take shape. For example, ChatGPT, Copilot, Gemini, Grammarly, Canvas LMS with AI Features, Turnitin with AI Tools and others are all having a certain impact on educational institutions. Faced with these developments, how should schools, as the main body of educational institutions, respond? We encourage authors of academic journals to contribute empirical studies that illustrate the impact of AI. It's undeniable that AI's involvement in education is new, and this novelty inevitably brings new opportunities. We must consider how to transition from old operations to new ones, which seems to be an inevitable trend.
To this end, with AI development, we propose the following focus areas for K-12 and high-level education.
Teaching methods: AI-based teaching methods, such as tools and accessibility;
Teaching evaluation: Teaching evaluation that aligns with teaching methods;
The relationship between personalized learning and collaborative learning;
AI-integrated teaching platforms and human-computer interaction;
Algorithmic bias and ethical considerations;
Student engagement and teacher-student relationships in AI-based teaching;
Planning and detecting academic integrity and cheating and
Competence in using AI in teaching and learning, as well as professional development.
The development of AI and the inevitable educational changes it brings are issues that every educational researcher must consider. We look forward to working with the authors to conduct further research and exploration in these areas.
