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Technical Aspects of Automated Item Generation for Blended Learning Environments in Biology: An Analysis of Two Case Studies from the Fields of Botany and Genetics

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Datum

2020

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Verlag

De Gruyter

Zusammenfassung

sing 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.

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Timm, Justin; Otto, Benjamin; Schramm, Thilo; Striewe, Michael; Schmiemann, Philipp; Goedicke, Michael (2020): Technical Aspects of Automated Item Generation for Blended Learning Environments in Biology: An Analysis of Two Case Studies from the Fields of Botany and Genetics. i-com: Vol. 19, No. 1. DOI: 10.1515/icom-2020-0001. Berlin: De Gruyter. PISSN: 2196-6826. pp. 3-15

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