DIGITAL LIBRARY
USING HARDWARE TO SUPPORT ARTIFICIAL INTELLIGENCE IN EDUCATION
University of Ostrava (CZECH REPUBLIC)
About this paper:
Appears in: INTED2024 Proceedings
Publication year: 2024
Pages: 4519-4524
ISBN: 978-84-09-59215-9
ISSN: 2340-1079
doi: 10.21125/inted.2024.1170
Conference name: 18th International Technology, Education and Development Conference
Dates: 4-6 March, 2024
Location: Valencia, Spain
Abstract:
Machine learning and artificial intelligence are currently undergoing significant and dynamic development. AI applications are increasingly common in industry, agriculture, science, and everyday life. Users are using machine learning and AI tools in text processing applications, images, videos, language translation and many other areas of daily use. Education needs to respond to this dynamic development, not only in software but also in specialised hardware. Edge devices are increasingly being used to support artificial intelligence in addition to software tools. This paper shows the possibilities of using these devices in education, their capabilities, advantages, disadvantages and possible difficulties associated with using dedicated hardware for AI and machine learning in education. This paper presents the results of a case study in which computer science students were introduced to the Coral Board Micro, microcomputers and microcontrollers. Students were asked to explore the capabilities of this hardware using the exploratory method. Students independently commissioned the device, set it up and tried out practical examples of its use. The results of the study show that ICT skills are still needed. It was found that there is a need to master the Linux operating system to work with specific libraries and versions of particular software, as well as the Python programming language. Among the positive findings were the students' high motivation, interest in the subject and desire to learn. Feedback was also obtained through an unstructured interview. Students commented on learning with AI-supported hardware.
Keywords:
Artificial intelligence, Edge devices, education, hardware, machine learning.