Timm, JustinOtto, BenjaminSchramm, ThiloStriewe, MichaelSchmiemann, PhilippGoedicke, Michael2020-04-222020-04-222020https://dl.gi.de/handle/20.500.12116/32170sing two case studies from biology, the article demonstrates and analyses how domain-specific self-learning items with variable content can be generated automatically for a <em>blended learning</em> environment. It shows that automated item generation works well even for highly specific technical properties and that a good item quality can be produced. Evaluations are based on sample exercises from two courses in botany and genetics, each with more than 100 participants.enBlended LearningE-AssessmentAutomated Item GenerationBiology EducationTechnical Aspects of Automated Item Generation for Blended Learning Environments in Biology: An Analysis of Two Case Studies from the Fields of Botany and GeneticsText/Journal Article10.1515/icom-2020-00012196-6826