Harnessing AI for ISCED Labelling of ODL Courses
DOI:
https://doi.org/10.34190/icer.1.1.3048Keywords:
Higher Education, open and distance learning, courses, ISCED, artificial intelligenceAbstract
At the University of Bologna, one of the pioneers of higher education in Europe and the institution that inspired the name of the Bologna Process, courses are labelled according to the International Standard Classification of Education (ISCED), a statistical classification of vocational fields. In Open and Distance Learning (ODL), where the number of programmes is high in parallel with the number of learners, determining the fields of courses taught is crucial not only for measurement and evaluation processes but also for a detailed examination of statistical information in processes such as enrolment and graduation. Processes such as data classification according to specific categories can be rapidly carried out with the help of artificial intelligence (AI) and can be utilised in administrative processes. This study investigated whether ChatGPT-4, one of the AI applications, could classify 1135 courses taught at Anadolu University's Open Education System (AUOES), which is part of the Bologna Process, according to ISCED fields, considering the content of the courses. In this study, document analysis was applied to the data analysis. According to the results, the highest number of courses in AUOES were in business, administration, and law (386), while the fewest courses were in education (27). These results indicate that courses related to white-collar professions are taught frequently and are influenced by the programmes at AUOES. This study suggests that AI can be used in administrative processes and to classify courses according to ISCED fields. Categorising all courses according to ISCED or a similar standard could enable the analysis of courses in vocational fields. Determining the fields of courses according to certain standardisations in ODL could allow the courses, and consequently, the books and materials, to be handled by subject matter experts. Decision-makers in ODL could plan the teaching of courses in line with needs by considering the employment situation in vocational fields when launching new programmes or updating course lists. Researchers could investigate the accuracy of AI's processes in administrative tasks and gather the opinions of subject matter experts, opening up new avenues for further research and exploration in the field of AI in education.Downloads
Published
2024-11-21
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