Artificial intelligence technology as a method to simplify physics learning | ||
| البحوث التطبيقية في العلوم والانسانيات | ||
| Volume 1, Issue 1, July 2024, Pages 181-206 PDF (1.81 M) | ||
| Document Type: المقالة الأصلية | ||
| DOI: 10.21608/aash.2024.376869 | ||
| Authors | ||
| Bavely Mansour Saleh Mansour; Beshoy Mahrous Morsy Bekhet; Mina Emad Alfy Nagy; Mohammed Magdy Ismael Mohammed; Osama Ashraf Youssef | ||
| lecturer, nuclear physics. Ain Shams University, Faculty of Education, Program bachelor’s degree in science and education (prep. and high school), physics. | ||
| Abstract | ||
| We faced a problem while teaching activities and experiments in physics due to a lack of imagination and a good understanding of physical phenomena. Therefore, we used artificial intelligence (AI), especially simulation experiments, to solve this problem. This study examined the determinants of adopting AI for teaching physics. It aimed to explore the basic concepts of AI, its various applications in learning physics, and the benefits and challenges associated with its implementation. The selected studies were analyzed and synthesized to develop a coherent framework for understanding the different ways of using AI in teaching physics. Questionnaires were used to determine the extent of students’ satisfaction with the use of AI by answering several questions after this technology was used through simulation to facilitate and simplify the explanation of physics. The collected data were analyzed using numbers of frequencies and percentages. The results showed that there was a strong demand and satisfaction with the use of this technology in explaining the physics lessons. The obtained results showed that the AI had great potential in the world of education, one of which was in learning physics. AI could also help improve students' understanding and comprehension skills, with 42% strongly agreeing and 30% agreeing, making the overall approval percentage 72%. In this study, the percentage between neutral and disagreeing was 28%. | ||
| Keywords | ||
| AI; Simulations; Education; physics experiments | ||
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