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Today’s working environments are subject to dynamic changes due to the proliferation of digital technologies and systems. This phenomenon poses a challenge for universities and other institutions of higher education, which are expected to adapt their course offerings to the rapidly changing demands in the labor market. The complexity of the task and the importance of speed pose an opportunity for automated data-driven methods with which the contents of study curricula can be compared, assessed, and, if necessary, adapted to the world of work. Owing to the lack of established solutions, this study presents a procedural methodology to create artifacts for analyzing, evaluating, and comparing curricula as well as job postings using topic modeling. In addition, we demonstrate the practical applicability of the methodology by the example of the IS discipline and present empirical results from the analysis of IS-related study programs in Germany.


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