Abstract:

In 2019, the AI-Campus (in German KI-Campus), a learning platform on artificial intelligence has launched as an R&D project funded by the German government (www.ai-campus.org). At the centre of the three-year pilot phase is the development of a digital learning platform specializing in the field of artificial intelligence. The platform has published first OER content in July 2020 and is planning to develop more than 20 openly licenced courses and other OER content on the topic of AI by the end of 2021. For this purpose, AI Campus collaborates with more than 30 higher education institutions and other partners from Germany and Luxembourg. As a basis, formal QA standards have been developed based, amongst others, on the European Standards and Guidelines (ESG, 2015), the European Recognition Manual (Nuffic, 2016) and the ECTS Users’ Guide (European Commission, 2015) and instructional design principles with a focus on open and smart learning environments (Kunshuk et al., 2016).

These pre-defined standards and guidelines are continuously further developed and revised based on an academic exchange amongst all stakeholders involved in the co-creation of OER content on the AI Campus. This process is proving to be very innovative, but also quite challenging. Whilst quality assurance criteria allow for the embedding of AI online courses in formal higher education curricula and the recognition of AI Campus courses as prior learning (de Witt et al., 2020), formal standards appear not to be sufficient for OER content as, for example, criteria for appropriate licensing must be included. At the same time, the OER content, ranging from non-formal podcasts and videos to formal academic courses (including blended learning scenarios) and micro degrees or alternative credentials, has different requirements and criteria. These must be differentiated on a case-specific basis and concepts, such as micro degrees, alternative credentials and microcredentials must be specified in a continuous dialogue with stakeholders.

At the same time, in addition to comprehensive guidelines and measures for individualisation, it is also necessary to define overarching, concise standards that have a validity for the entire learning ecosystem. Thus the paper reflects on “10 Minimum Standards for AI Campus Originals” that the AI Campus has developed based on its work with its ever-growing community of over 30 partners from different educational sectors.

Keywords:

Artificial Intelligence, QA, Instructional Design, OER, MOOCs, Podcasts, Videos, Micro Credentials, AI Campus.