Case Studies The Impact of Artificial Intelligence on STEM Education
1Case Studies: The Impact of Artificial Intelligence on STEM Education
Layman Abstract : Artificial intelligence (AI) can enhance education by improving both teaching and learning. This chapter explores how AI can serve as a new method of intervention to reshape the curriculum, particularly in Mathematics and Computer Science education. Two key AI-driven technologies are discussed: educational robotics and learning management systems (LMS).
Educational Robotics: A study involving 75 pre-service computer science teachers examined how robotics helped them learn programming. Their experiences were analyzed using Kolb’s Experiential Learning Cycle, which emphasizes learning through experience. Robotics was also explored for its potential in STEM education.
Learning Management Systems (LMS): Another study examined LMS use among 162 science and engineering students learning mathematics. The research found that AI-powered LMS can enhance teaching and provide more personalized learning experiences.
Overall, the chapter highlights how AI, through robotics and LMS, can positively impact education by making learning more effective and tailored to students' needs.
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Original Abstract : Artificial intelligence can improve the quality of teaching and learning in education. It can have a more positive impact by serving as a new special purpose “method of intervention” that can change our curriculum in education. Artificial intelligence refers to technology that reacts to its environment and responds to tasks in a way that optimizes the levels of success. In this chapter, we certain tasks which were carried out by educational robotics and learning management systems that could maximize the success of teaching and learning, specifically in Mathematics and computer science education, were discussed. The two types of technology discussed in this chapter are robotics and a learning management system. We These two types of technology were considered in a general setting and examples of actual usage in classroom situations were provided. The authors present for each type, an example of intervention of artificial intelligence. In the case of robotics, research was carried out with preservice computer science teachers (n =75). These teachers were asked about their experiences when utilizing robotics when learning computer programming. Kolb’s Experiential Learning Cycle guided that study. In the section that follows, we potentials of robotics in STEM Education were surveyed. In the case of using the learning management systems, a mixed-mode research study was carried out with science students in one study and then with engineering students (n =162) learning mathematics. It was found that there is ample potential for the use of artificial intelligence in education to enhance teaching to support more effective individualized learning. We in this chapter, the benefits of using educational robotics and learning management systems for teaching and learning in education with pre-service teachers and engineering students were shown.
View Book: https://doi.org/10.9734/bpi/aoller/v10/4389
#Artificial_intelligence #education #learning_management_systems #robotics