Kasakowskij,ReginaKasakowskij, ThomasSeidel, NielsHenning, Peter A.Striewe, MichaelWölfel, Matthias2022-08-232022-08-232022978-3-88579-716-6https://dl.gi.de/handle/20.500.12116/38826Assessments are an important part of the learning cycle and enable the development and promotion of competencies. However, the manual creation of assessments is very time-consuming. Therefore, the number of tasks in learning systems is often relatively small. In this paper, we present an algorithm that can automatically generate an arbitrary number of German True False statements from a textbook using the GPT-2 model. The algorithm was evaluated with a selection of textbook chapters from four different academic disciplines and rated by domain experts. One-third of the generated MTF Questions are suitable for learning. The algorithm provides instructors with an easier way to create assessments on chapters of textbooks to test factual knowledge.enautomatic question generationtrue false questionsassessmentGPT-2 modelNLPText/Conference Paper10.18420/delfi2022-0261617-5468