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Mathematics anxiety in undergraduate business studies students.

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Title: Mathematics anxiety in undergraduate business studies students.
Authors: McCullagh, Orla1 orla.mccullagh@ul.ie, Ryan, Maria2, Fitzmaurice, Olivia3
Source: Teaching Mathematics & its Applications. Jun2024, Vol. 43 Issue 2, p125-146. 22p.
Subject Terms: *Math anxiety, *Undergraduates, *Business students, *Mathematical ability, *Artificial intelligence
Abstract: Performance in mathematics can be attributed to factors other than mathematical ability. A growing body of literature examines the significant impact of mathematics anxiety (MA) on mathematical performance and individuals' choices concerning study and career pathways. However, much of the focus has been on science, technology, engineering and mathematics subjects, renowned for their high mathematical content. This study examines the prevalence, characteristics and influence of MA in undergraduate business studies students. In all aspects of business, there is a strong impetus for the adoption of artificial intelligence, data analytics and machine learning, prompting reform of business studies curricula. Hence, this is a critical juncture at which to examine MA within this cohort. We survey undergraduate business studies students using the Mathematics Anxiety Scale-UK as a measure of participants' MA and examine its relevance in business major selection. Gender emerges as a key differentiating factor in levels of MA and the selection of business majors. [ABSTRACT FROM AUTHOR]
Copyright of Teaching Mathematics & its Applications is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Teaching+Mathematics+%26+its+Applications%22">Teaching Mathematics & its Applications</searchLink>. Jun2024, Vol. 43 Issue 2, p125-146. 22p.
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  Data: *<searchLink fieldCode="DE" term="%22Math+anxiety%22">Math anxiety</searchLink><br />*<searchLink fieldCode="DE" term="%22Undergraduates%22">Undergraduates</searchLink><br />*<searchLink fieldCode="DE" term="%22Business+students%22">Business students</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+ability%22">Mathematical ability</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink>
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  Data: Performance in mathematics can be attributed to factors other than mathematical ability. A growing body of literature examines the significant impact of mathematics anxiety (MA) on mathematical performance and individuals' choices concerning study and career pathways. However, much of the focus has been on science, technology, engineering and mathematics subjects, renowned for their high mathematical content. This study examines the prevalence, characteristics and influence of MA in undergraduate business studies students. In all aspects of business, there is a strong impetus for the adoption of artificial intelligence, data analytics and machine learning, prompting reform of business studies curricula. Hence, this is a critical juncture at which to examine MA within this cohort. We survey undergraduate business studies students using the Mathematics Anxiety Scale-UK as a measure of participants' MA and examine its relevance in business major selection. Gender emerges as a key differentiating factor in levels of MA and the selection of business majors. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Teaching Mathematics & its Applications is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jun2024
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