Overcoming Student Passivity with Automatic Item Generation
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Studying at German universities is often associated with a passive mode of learning. Using learning tasks and (self-)test items is an effective way to address this issue. However, due to the high cost of creation, these materials are rarely provided to learners. The approach of Automatic Item Generation (AIG) allows for the resource-efficient generation of learning tasks and (self-)test items. This paper demonstrates, after presenting general ideas of AIG, how tasks or items can be automatically generated using the AIG Model Editor designed at TUD Dresden University of Technology. Subsequently, items generated using the AIG approach are compared with items created in a traditional manner. The results show that automatically generated items have comparable properties to traditionally created items, but their generation requires much less effort than the traditional creation, thus making AIG appear as a promising alternative for supporting active learning at universities.
Details
Original language | English |
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Title of host publication | Proceedings of the 16th International Conference on Computer Supported Education, CSEDU 2024 |
Editors | Oleksandra Poquet, Alejandro Ortega-Arranz, Olga Viberg, Irene-Angelica Chounta, Bruce McLaren, Jelena Jovanovic |
Publisher | SCITEPRESS - Science and Technology Publications |
Pages | 789-798 |
Number of pages | 10 |
Volume | 1 |
ISBN (electronic) | 9789897586972 |
ISBN (print) | 978-989-758-697-2 |
Publication status | Published - 2024 |
Peer-reviewed | Yes |
External IDs
unpaywall | 10.5220/0012747500003693 |
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Scopus | 85193973916 |
Keywords
Research priority areas of TU Dresden
DFG Classification of Subject Areas according to Review Boards
Subject groups, research areas, subject areas according to Destatis
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- AIG, Assessment, Automatic Item Generation, Cognitive Model, Item Model