Analysis of Learner's Response to Process Automation Class Design Using Web Content and Python Library

Abstract

The spread of artificial intelligence along with the Fourth Industrial Revolution is bringing about changes in future occupations. Therefore, AI education is emerging as an essential subject in universities, and curriculums are being designed and researched through various approaches. This study introduces a case involving process automation classes that can be applied to university SW and AI liberal arts education by utilizing various learning resources of web content that are encountered in daily life. At a time when artificial intelligence education is emerging as important, the AI pre-processing process is also important. Thus, procedural and experiential learning that can select the tools necessary to collect, process, and analyze appropriate data for problem solving is also important. Therefore, in designing the SW⋅AI liberal arts curriculum, it is meaningful in various aspects to design an education that quickly collects and processes life-linked data based on web content by combining the highly utilized Python library and RPA concept. Through related research, cases where process automation implementation learning can be designed and applied, areas of interest among learners regarding classification were derived through learner responses. Furthermore, web content designed through qualitative responses were shown to be excellent practical resources for process automation learning. In the designed learning of classification, interest in ‘data collection using data crawling and scraping’ ranked the highest, followed by ‘open API integration and utilization’. Based on the research results, improvement points and implications are derived, and research in various directions is suggested in order for us to develop this course into a basic subject of artificial intelligence education in the future.