(Generative) AI Competencies for Future-Proof Graduates : Inspiration for Higher Education Institutions

Titelangaben

Gimpel, Henner ; Gutheil, Niklas ; Mayer, Valentin ; Bandtel, Matthias ; Büttgen, Marion ; Decker, Stefan ; Eymann, Torsten ; Feulner, Simon ; Kaya, Muhammed Fatih ; Kufner, Marie ; Kühl, Niklas ; Lämmermann, Luis ; Mädche, Alexander ; Ruiner, Caroline ; Schoop, Mareike ; Urbach, Nils:
(Generative) AI Competencies for Future-Proof Graduates : Inspiration for Higher Education Institutions.
Hohenheim , 2024 . - 34 S. - (Hohenheim Discussion Papers in Business, Economics and Social Sciences )
DOI: https://doi.org/10.5281/zenodo.10680210

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Abstract

The widespread use of Artificial Intelligence (AI) in various areas of professional and private life makes us thoroughly re-evaluate and update the competencies university students should acquire. This whitepaper focuses on what these changes mean for higher education, helping individuals responsible for curricular and extracurricular courses at higher education institutions integrate new competencies.
Competencies are a combination of skills, knowledge, and attitudes that enables a person to perform a task or an activity successfully in a specific context. Basic competencies such as literacy and numeracy are integral to a wide array of professions and in various aspects of daily life. Fur-thermore, this discourse extends to advanced competencies, such as training machine learning (ML) models or preparing annual financial statements, which are indispensable for certain specialized professions or tasks.
Especially the advent of Generative AI (GenAI) is catalyzing a transformative shift in the landscape of competencies. While established overarching competency areas such as literacy or numeracy are likely to remain relevant, their significance is changing, with some areas increasing and others de-creasing in relevance. At a more detailed level, specific knowledge areas, skills, and attitudes are becoming outdated as new ones emerge in response to evolving technological demands. In particu-lar, new competency areas specifically related to AI, such as AI Management or AI Innovation, are emerging. In summary, the competency profiles required for success in the business world, society, and life are undergoing rapid changes, mirroring the swift pace of technological advancements in AI.
Consequently, higher education institutions such as universities should reconsider their peda-gogical approaches, considering a future deeply interwoven with AI technologies. Students, in turn, should plan their educational trajectories to align with this AI-shaped future. Given the constrained scope and duration of higher education degree programs, it is important to utilize these resources in a manner that is both goal-oriented and efficient. As the objectives regarding competencies evolve, there is a corresponding necessity for transforming both teaching offers and learning opportunities.
This whitepaper motivates the topic and emphasizes the relevance of AI as a general-purpose technology in sections 1 and 2. Readers familiar with AI might want to skip these preliminaries. Section 3 details basic and advanced competencies, shifting relevance, and novelties due to AI. Section 4 poses nine key questions for higher education institutions to answer regarding their cur-rent and future teaching with the omnipresence of AI. Section 5 presents examples of AI competen-cy models and their integration into teaching and learning from three different universities. Sections 3 to 5 are the core of this whitepaper and shall inform and inspire the debate about AI competencies in higher education. Section 6 is a brief conclusion.
Feedback on how you approach AI competencies is highly welcome. Let us jointly work towards integrating AI competencies into higher education to train future-proof graduates!