Research Title: Artificial Intelligence in Science Teaching: Visions and Challenges from a Teacher's Perspective

The current research aimed to identify the role of artificial intelligence in science teaching from the perspective of science teachers, and to provide an inherent understanding of the evidence-based interaction between artificial intelligence and science education, and to achieve the objectives of the research, the researcher adopted the case study design to address the main research question, where a sample of the research community consisting of (7) teachers was selected to teach science from different schools from Qalyubia Governorate (preparatory secondary), and a sample of students was selected for the same sample of teachers, numbering (49) students, where The sample for each teacher ranged between (5-7) students. Some of the lessons of integrated science with artificial intelligence were implemented in two sessions, each of which extended for more than three hours (online), in the lessons of (the first unit) movement in one direction, the graph representation of motion in a straight line, standard and vector physical quantities), and the second unit: light energy (mirrors - lenses). AI science lessons, represented in knowing their perspectives in identifying: similarities and differences between artificial intelligence and science? The relationship between artificial intelligence and science teaching? The most difficult components of teaching science with artificial intelligence? How do AI tools affect student learning outcomes and engagement in science education? What are the potential disparities in the uptake of AI tools in science education? What are the perceptions and attitudes of students and teachers towards the use of artificial intelligence tools in science education? What are the ways to improve science teaching with artificial intelligence? The results showed that there is an increasing interest in teaching science content with artificial intelligence in some schools with distinct infrastructure, in addition to the ease of identifying the similarities between artificial intelligence and science, and the results also showed that the results showed that the integrated TPACK framework for artificial intelligence can be improved and take into account the needs of the educational context, and teachers' awareness of the importance of teaching integrated science with artificial intelligence in Light a set of practical considerations, represented in: the current understanding of artificial intelligence by science teachers, the science curriculum, student engagement, and contribute to the further development of AI science teaching to develop students' knowledge of AI using diverse cognitive practices. The results also showed that AI-powered tools are integrated into science education to achieve various pedagogical benefits, including enhancing the learning environment, creating electronic tests, evaluating students' work, and predicting their academic performance. In the light of these findings, a set of recommendations and proposals were reached.