ALIGNING IS CURRICULUM WITH INDUSTRY SKILL EXPECTATIONS: A TEXT MINING APPROACH

Digitalization offers both great opportunities as well as new challenges and uncertainties. In particular, students in their role as future employees will have to cope with the new digital environments, which makes lifelong learning and up-to-date skills even more important than they already are. Key players in this long-term development are the universities as providers of the necessary skills and knowledge. By now, it is clear that digitalization will have a broad impact on the future conditions of universities. But are they already prepared for it? Against this backdrop, we present an approach to combine universities’ offerings with the required industry job skills to identify potential curricular gaps at course level that arise through ongoing digitalization and, as a consequence, changing skill requests for employees. We identify an appropriate set of methods for our project including text min-ing methods, an expert survey and an interview phase for evaluation. We illustrate our approach using a large data set of German IS curricular module descriptions and offers for IS job starters

Exploring Information Systems Curricula

The study considers the application of text mining techniques to the analysis of curricula for study programs offered by institutions of higher education. It presents a novel procedure for efficient and scalable quantitative content analysis of module handbooks using topic modeling. The proposed approach allows for collecting, analyzing, evaluating, and comparing curricula from arbitrary academic disciplines as a partially automated, scalable alternative to qualitative content analysis, which is traditionally conducted manually. The procedure is illustrated by the example of IS study programs in Germany, based on a data set of more than 90 programs and 3700 distinct modules. The contributions made by the study address the needs of several different stakeholders and provide insights into the differences and similarities among the study programs examined. For example, the results may aid academic management in updating the IS curricula and can be incorporated into the curricular design process. With regard to employers, the results provide insights into the fulfillment of their employee skill expectations by various universities and degrees. Prospective students can incorporate the results into their decision concerning where and what to study, while university sponsors can utilize the results in their grant processes

Exploring Information Systems Curricula

The study considers the application of text mining techniques to the analysis of curricula for study programs offered by institutions of higher education. It presents a novel procedure for efficient and scalable quantitative content analysis of module handbooks using topic modeling. The proposed approach allows for collecting, analyzing, evaluating, and comparing curricula from arbitrary academic disciplines as a partially automated, scalable alternative to qualitative content analysis, which is traditionally conducted manually. The procedure is illustrated by the example of IS study programs in Germany, based on a data set of more than 90 programs and 3700 distinct modules. The contributions made by the study address the needs of several different stakeholders and provide insights into the differences and similarities among the study programs examined. For example, the results may aid academic management in updating the IS curricula and can be incorporated into the curricular design process. With regard to employers, the results provide insights into the fulfillment of their employee skill expectations by various universities and degrees. Prospective students can incorporate the results into their decision concerning where and what to study, while university sponsors can utilize the results in their grant processes

BRIDGING THE GAP BETWEEN INDUSTRY SKILL DEMAND AND UNIVERSITY SKILL PROVISION

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