BERT-based distractor generation for Swedish reading comprehension questions using a small-scale dataset
Year: 2021
Type: conference-paper
Abstract: An important part when constructing multiplechoice questions (MCQs) for reading comprehension assessment are the distractors, the incorrect but preferably plausible answer options.In this paper, we present a new BERTbased method for automatically generating distractors using only a small-scale dataset.We also release a new such dataset of Swedish MCQs (used for training the model), and propose a methodology for assessing the generated distractors.Evaluation shows that from a student's perspective, our method generated one or more plausible distractors for more than 50% of the MCQs in our test set.From a teacher's perspective, about 50% of the generated distractors were deemed appropriate.We also do a thorough analysis of the results.
Authors: Dmytro Kalpakchi, Johan Boye
Institution: KTH Royal Institute of Technology
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W3191550737