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Towards Intelligent Test Sequencing, Enhancing Multiple Choice (MC) Tests in eLearning
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, , , , Edward Waters College, United States

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Orlando, Florida, USA ISBN 978-1-880094-83-9 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

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Abstract

Multiple choice (MC) tests are typically used for formative assessments in eLearning. However, the interaction bandwidth of traditional MC tests is severely limited; students can only make a tick on an answer option. Therefore the eLearning system needs to make assumptions to fill-in the gaps. Nevertheless, the system’s assumption may be wrong. A student may guess a correct answer or may make a careless mistake. If an eLearning system often makes stereo-typed pedagogical decisions based on wrong assumptions, eventually, the students would get frustrated. This research describes an artificial intelligent based methodology that could provide individualized test sequencing and personalized feedback.

Citation

Mohanarajah, S., Betton, S., Ikeokwu, F. & Sundaralingam, N. (2010). Towards Intelligent Test Sequencing, Enhancing Multiple Choice (MC) Tests in eLearning. In J. Sanchez & K. Zhang (Eds.), Proceedings of E-Learn 2010--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 554-559). Orlando, Florida, USA: Association for the Advancement of Computing in Education (AACE). Retrieved April 16, 2021 from .

© 2010 Association for the Advancement of Computing in Education (AACE)

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