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Multiple Choice vs. Fill-in Problems: The Trade-Off Between Scalability and Learning

Conference Paper/Proceedings
Multiple Choice vs. Fill-in Problems: The Trade-Off Between Scalability and Learning
Publication Year:
2024
Publication Source:
Fourteenth International Conference On Learning Analytics & Knowledge, Lak 2024
Funding Type:
ECR:Core
Author(s):
Gurung, Ashish; Vanacore, Kirk; McReynolds, Andrew A.; Ostrow, Korinn S.; Worden, Eamon S.; Sales, Adam C.; Heffernan, Neil T.
Supporting Project(s):

Learning experience designers consistently balance the trade-off between open and close-ended activities. The growth and scalability of Computer Based Learning Platforms (CBLPs) have only magnified the importance of these design trade-offs. CBLPs often utilize close-ended activities (i.e. Multiple-Choice Questions [MCQs]) due to feasibility constraints associated with the use of open-ended activities. MCQs offer certain affordances, such as immediate grading and the use of distractors, setting them apart from open-ended activities. Our current study examines the effectiveness of Fill-In problems as an alternative to MCQs for middle school mathematics. We report on a randomized study conducted from 2017 to 2022, with a total of 6,768 students from middle schools across the US. We observe that, on average, Fill-In problems lead to better post-test performance than MCQs; albeit deeper explorations indicate differences between the two design paradigms to be more nuanced. We find evidence that students with higher math knowledge benefit more from Fill-In problems than those with lower math knowledge.