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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies

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Artificial Intelligence for Knowledge Management (AI4KM 2021)

Abstract

Leading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last 10 years in business informatics and computer science in two selected universities in Poland. Our study relies on a detailed review and analysis of qualitative data, obtained from a literature review and multi-case-study research. In the case of the artificial intelligence domain, we have identified six areas of research, namely: general AI, machine learning (ML), natural language processing (NLP), artificial neural networks (ANNs), expert systems, and hybrids. In the case of the knowledge management domain, we have recognized eleven areas of research, regarding the following sectors: e-government, technology, space exploration, social media, manufacturing, healthcare, finance, entertainment, education, e-commerce, and business. Future research will be directed toward extending the scope by including other regions and universities as well as identifying and analyzing students’ motivational factors, associated with research pro jects and higher education.

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Correspondence to Mieczysław L. Owoc .

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Owoc, M.L., Weichbroth, P. (2021). University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies. In: Mercier-Laurent, E., Kayalica, M.Ö., Owoc, M.L. (eds) Artificial Intelligence for Knowledge Management. AI4KM 2021. IFIP Advances in Information and Communication Technology, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-030-80847-1_5

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  • DOI: https://doi.org/10.1007/978-3-030-80847-1_5

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