AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The results indicate that students already use tools such as ChatGPT in their academic and teaching practices, mainly to plan lessons, design activities, and organize ideas, whereas the main concerns relate to intellectual complacency, standardization of productions, and weakened authorship.
It is concluded that initial teacher education must shift the focus from the tool to the pedagogical problem, preparing teachers as learning sequence designers who create, adapt, and critically evaluate AI-powered resources.
Purpose: This study examines science teachers’ experiences with the use of generative artificial intelligence in their teaching and learning processes, as well as the meanings they ascribe to these experiences. Method: The research used a qualitative, descriptive phenomenological approach. The study group consisted of six science teachers who worked in public schools affiliated with the Ministry of National Education and who had received training in generative artificial intelligence. Participants were selected using snowball sampling. Data were collected through online interviews using a 15-item semi-structured form developed by the researchers. Findings: Research findings indicate that science teachers primarily use artificial intelligence as a tool to support instruction. Evidence indicates that AI-supported applications increase students’ interest and motivation in the subject, facilitate the concretization of abstract concepts, and enhance learning retention. However, teachers have noted that factors such as insufficient class time, curriculum designs that are not conducive to the integration of generative AI, lack of technological infrastructure, and an exam-focused education system limit the use of these applications in the classroom. Additionally, it has been emphasized that current assessment and evaluation systems inadequately reflect the quality of learning outcomes supported by generative AI. Implications: Research findings indicate that generative artificial intelligence offers significant pedagogical opportunities in science education. However, to effectively harness this potential, it is necessary to develop teachers’ skills in using generative artificial intelligence for pedagogical purposes, increase practice-based professional development initiatives, and support classroom implementations. Additionally, it is important to develop flexible, process-oriented assessment approaches suitable for generative AI-supported learning environments.
A ten-step teaching framework for AI-supported creative interactive content design is proposed, aimed at fostering pedagogical innovation while preserving critical thinking, creativity, and student authorship.
The results show that most lecturers in Elementary Madrasah Teacher Education have a good understanding of generative AI, with a fairly high frequency of use in the teaching process, and the need for policy support and ongoing training to ensure that the use of AI in education can be optimized is highlighted.
With evolving times, the field of education is undergoing a major transformation with the help of Artificial Intelligence, which aids in the personalization of learning, instructional design, evaluation, and administration. The successful integration of AI depends on teachers' perceptions, experiences and openness. In this study, the convergent parallel mixed-method design was used to identify teachers' perceptions, experiences and challenges with the use of AI technologies in learning activities including eight teachers as respondents by using the purposive sampling method. The data was collected using items that were reported on a Likert scale and processed qualitatively by themes. Results showed that teachers had positive attitudes toward use of AI, with a specific emphasis on its utility in lesson planning, boosting engagement, and streamlining administration. The study found that the main challenges to implementing AI are insufficient institutional support, ambiguous policy guidance, plagiarism, data privacy, and overreliance on AI. Teachers perceived AI as a teaching assistant not a teacher. Thus, the study emphasizes the importance of professional development, institutional preparedness, and ethical guidelines to ensure responsible and effective integration of AI in education.
This study explores university EFL students’ perceptions of Artificial Intelligence (AI) in higher education learning environments, particularly within Faculty of Teacher Training and Education in Indonesia. Employing a qualitative phenomenological design, data were collected through semi-structured interviews with nine students from the Faculty of Teacher Training and Education who actively use AI-assisted tools in their academic activities. The findings reveal that EFL students demonstrate high familiarity with AI applications, especially for language learning, doing tasks, and perceive AI as a supportive learning assistant that enhances efficiency, autonomy, and confidence. AI tools are widely valued for providing immediate feedback, facilitating comprehension, and reducing learning anxiety through flexible and interactive learning experiences. However, the study also identifies critical concerns related to accuracy, ethical integrity, and dependency, as excessive reliance on AI may hinder critical thinking and academic responsibility. These findings highlight the dual role of AI as both an empowering pedagogical resource and a potential challenge when used uncritically. The study underscores the importance of developing deeper AI literacy and institutional guidance to ensure responsible, ethical, and cognitively meaningful AI integration in higher education.
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