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Using the One Minute Paper to Gain Insight into Potential Threshold Concepts in Artificial Intelligence Courses

Lookup NU author(s): Becky Allen, Dr Marie Devlin, Dr Stephen McGough

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Abstract

© 2021 ACM. Interest in Artificial Intelligence (AI) and the popularity of such courses has increased over the past few years, as a consequence higher education (HE) institutions are now offering courses in such fields. However, there is a current lack of research relating to best practice for teaching this complex topic area which encompasses both computing and mathematics knowledge. This paper outlines an initial study that set out to determine the threshold concepts within this domain through use of the One Minute Paper technique with students currently studying AI. Our results identified a number of specific models which students found troublesome including the support vector machine, recurrent neural network and the multilayer perceptron. The results indicated that topics related to deep learning were more complex for the students to fully comprehend and students may require greater in-depth tuition and alternative support mechanisms in this area in particular. Further investigation is needed to determine the heterogeneity of content delivered on courses relating to AI as well as additional studies at other HE institutions to gather more data on potential threshold concepts and the best methods to teach them.


Publication metadata

Author(s): Allen B, Devlin M, McGough AS

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computing Education Practice (CEP '21)

Year of Conference: 2021

Pages: 21-24

Online publication date: 07/01/2021

Acceptance date: 02/04/2018

Publisher: ACM

URL: https://doi.org/10.1145/3437914.3437974

DOI: 10.1145/3437914.3437974

Library holdings: Search Newcastle University Library for this item

ISBN: 9781450389594


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