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
| dc.contributor.author | Timm, Justin | |
| dc.contributor.author | Otto, Benjamin | |
| dc.contributor.author | Schramm, Thilo | |
| dc.contributor.author | Striewe, Michael | |
| dc.contributor.author | Schmiemann, Philipp | |
| dc.contributor.author | Goedicke, Michael | |
| dc.date.accessioned | 2020-04-22T03:52:19Z | |
| dc.date.available | 2020-04-22T03:52:19Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | 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. | en |
| dc.identifier.doi | 10.1515/icom-2020-0001 | |
| dc.identifier.pissn | 2196-6826 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/32170 | |
| dc.language.iso | en | |
| dc.publisher | De Gruyter | |
| dc.relation.ispartof | i-com: Vol. 19, No. 1 | |
| dc.subject | Blended Learning | |
| dc.subject | E-Assessment | |
| dc.subject | Automated Item Generation | |
| dc.subject | Biology Education | |
| dc.title | 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 | en |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 15 | |
| gi.citation.publisherPlace | Berlin | |
| gi.citation.startPage | 3 |