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Mathematics Anxiety in Undergraduate Business Studies Students

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Title: Mathematics Anxiety in Undergraduate Business Studies Students
Language: English
Authors: Orla McCullagh, Maria Ryan, Olivia Fitzmaurice
Source: Teaching Mathematics and Its Applications. 2024 43(2):125-146.
Availability: Oxford University Press. Great Clarendon Street, Oxford, OX2 6DP, UK. Tel: +44-1865-353907; Fax: +44-1865-353485; e-mail: jnls.cust.serv@oxfordjournals.org; Web site: http://teamat.oxfordjournals.org/
Peer Reviewed: Y
Page Count: 22
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, Undergraduate Students, Business Education, Mathematics Anxiety, Majors (Students), Course Selection (Students), Gender Differences, Beliefs, Self Efficacy
Geographic Terms: Ireland
DOI: 10.1093/teamat/hrae001
ISSN: 0268-3679
1471-6976
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.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1427607
Database: ERIC
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  Value: <anid>AN0177720741;n6201jun.24;2024Jun10.06:47;v2.2.500</anid> <title id="AN0177720741-1">Mathematics anxiety in undergraduate business studies students </title> <sbt id="AN0177720741-2">1 Introduction</sbt> <p>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.</p> <p> <emph>Mathemaphobia</emph> was a term used in early studies ([<reflink idref="bib33" id="ref1">33</reflink>], [<reflink idref="bib33" id="ref2">33</reflink>]) by a teacher who referred to her students' striking emotional reactions in the face of mathematical tasks and challenges. However, in the 1970s, a more widely accepted definition of the phenomenon was provided, describing mathematics anxiety (MA) as '[...] a feeling of tension and anxiety that interferes with the manipulation of numbers and the solving of the mathematical problems in a wide variety of ordinary life and academic situations' ([<reflink idref="bib71" id="ref3">71</reflink>][<reflink idref="bib71" id="ref4">71</reflink>][<reflink idref="bib71" id="ref5">71</reflink>], [<reflink idref="bib71" id="ref6">71</reflink>], p. 551).</p> <p>Early studies into MA recognize that achievements (and non-achievements) in mathematics can be attributed to factors other than intellect ([<reflink idref="bib27" id="ref7">27</reflink>], [<reflink idref="bib27" id="ref8">27</reflink>]; [<reflink idref="bib78" id="ref9">78</reflink>][<reflink idref="bib78" id="ref10">78</reflink>], [<reflink idref="bib78" id="ref11">78</reflink>]). They identify that many issues around mathematics in education can be attitudinal, prompting an examination of affective factors ([<reflink idref="bib12" id="ref12">12</reflink>], [<reflink idref="bib12" id="ref13">12</reflink>]). Moreover, MA is a phenomenon that has been shown to have far-reaching impacts on individuals and society ([<reflink idref="bib29" id="ref14">29</reflink>][<reflink idref="bib29" id="ref15">29</reflink>][<reflink idref="bib29" id="ref16">29</reflink>], [<reflink idref="bib29" id="ref17">29</reflink>]), most significantly as a potential inhibitor of career and educational opportunities.</p> <p>Parallel to these studies, research examining students' selection of higher education majors identifies a wide range of affective, social and cultural influencing factors. Some of these studies are motivated by increasing concerns about the falling numbers of suitable graduates for particular sectors of employment ([<reflink idref="bib73" id="ref18">73</reflink>][<reflink idref="bib73" id="ref19">73</reflink>][<reflink idref="bib73" id="ref20">73</reflink>], [<reflink idref="bib73" id="ref21">73</reflink>]). In particular, the accounting profession is concerned about the pipeline of accounting graduates, prompting studies that examine the factors that influence the choice of accounting as a business major ([<reflink idref="bib77" id="ref22">77</reflink>][<reflink idref="bib77" id="ref23">77</reflink>][<reflink idref="bib77" id="ref24">77</reflink>], [<reflink idref="bib77" id="ref25">77</reflink>]). Similar studies have been carried out concerning the falling numbers of graduates in management information systems ([<reflink idref="bib81" id="ref26">81</reflink>], [<reflink idref="bib81" id="ref27">81</reflink>]). Indeed, the nature of business education is changing, responding to a sector that is increasingly data-driven and where insights from data analytics and machine learning are key to responding to customer needs, product innovation, security, reporting requirements and competitiveness ([<reflink idref="bib70" id="ref28">70</reflink>][<reflink idref="bib70" id="ref29">70</reflink>], [<reflink idref="bib70" id="ref30">70</reflink>]; [<reflink idref="bib45" id="ref31">45</reflink>], [<reflink idref="bib45" id="ref32">45</reflink>]). Business schools are responding to these needs with more data-centric curricula and the integration of data analytics ([<reflink idref="bib67" id="ref33">67</reflink>][<reflink idref="bib67" id="ref34">67</reflink>][<reflink idref="bib67" id="ref35">67</reflink>], [<reflink idref="bib67" id="ref36">67</reflink>]; [<reflink idref="bib6" id="ref37">6</reflink>], [<reflink idref="bib6" id="ref38">6</reflink>]). Traditionally, disciplines related to science, technology, engineering and mathematics (STEM) are renowned for their high mathematical content, with business studies perceived as less intensively mathematical. Hence, we are interested in exploring attitudes towards mathematics among business studies students and whether it influences their choice of sub-discipline study pathway (major).</p> <p>A key contribution of this paper is bringing together insights from previous research into mathematics anxiety and research on influences on the choice of business major. The key research questions this study aims to explore are as follows: What is the prevalence of MA in undergraduate business studies students? What factors are associated with higher levels of MA in this cohort? Does MA influence students' choice of business major (and thereby career)?</p> <p>The study design involves a survey of 244 undergraduate business studies students and incorporates the Mathematics Anxiety Scale-UK (MAS-UK) ([<reflink idref="bib41" id="ref39">41</reflink>][<reflink idref="bib41" id="ref40">41</reflink>], [<reflink idref="bib41" id="ref41">41</reflink>]) as a measure of MA, several demographical questions, prior attainment measures, self-evaluation statements and a series of attitudinal questions focused on evaluating key influences of career and study pathway choices. This study will provide us an empirically informed baseline understanding of MA in this group of interest. This foundation will inform and empirically motivate further research into pedagogical interventions, curriculum design and support mechanisms designed to mitigate MA and any associated impacts on business major selection and career pathways. This addresses a significant gap in the literature and can help inform policy development, particularly concerning the role of third-level education in governments' strategies to support the development of a digital, data literate workforce.</p> <hd id="AN0177720741-3">2 Literature review</hd> <p>Our research objective requires that we explore two two overlapping fields of research. The first focuses on the factors influencing MA and the second examines the factors influencing pathway selection and success in business studies education. Interestingly, many of the same influencing factors are identified, including self-efficacy, gender and referent influence. However, emotion and working memory are prominent influencing factors in the MA literature, while career ideation and cultural values are discussed as significant factors in studies examining business studies pathway choices and success.</p> <hd id="AN0177720741-4">2.1 Self-efficacy</hd> <p>Self-efficacy is a personal judgement on one's capabilities to 'organize and execute courses of action required to attain designated types of performances' ([<reflink idref="bib3" id="ref42">3</reflink>], [<reflink idref="bib3" id="ref43">3</reflink>], p. 76). It can be considered as task-specific self-confidence and has become central to theories on pedagogy, motivation and achievement, and it is a key component of social–cognitive theory. Self-efficacy is an important factor in mathematical performance and success measures ([<reflink idref="bib26" id="ref44">26</reflink>][<reflink idref="bib26" id="ref45">26</reflink>], [<reflink idref="bib26" id="ref46">26</reflink>]; [<reflink idref="bib24" id="ref47">24</reflink>][<reflink idref="bib24" id="ref48">24</reflink>], [<reflink idref="bib24" id="ref49">24</reflink>]). Studies that examine the relationship between mathematics self-concept or self-efficacy and MA typically find a strong negative correlation ([<reflink idref="bib47" id="ref50">47</reflink>][<reflink idref="bib47" id="ref51">47</reflink>], [<reflink idref="bib47" id="ref52">47</reflink>]; [<reflink idref="bib66" id="ref53">66</reflink>][<reflink idref="bib66" id="ref54">66</reflink>][<reflink idref="bib66" id="ref55">66</reflink>], [<reflink idref="bib66" id="ref56">66</reflink>]; [<reflink idref="bib49" id="ref57">49</reflink>], [<reflink idref="bib49" id="ref58">49</reflink>]; [<reflink idref="bib65" id="ref59">65</reflink>][<reflink idref="bib65" id="ref60">65</reflink>][<reflink idref="bib65" id="ref61">65</reflink>], [<reflink idref="bib65" id="ref62">65</reflink>]). However, [<reflink idref="bib24" id="ref63">24</reflink>][<reflink idref="bib24" id="ref64">24</reflink>][<reflink idref="bib24" id="ref65">24</reflink>] argued that these studies do not demonstrate causality between the two variables.</p> <p>[<reflink idref="bib16" id="ref66">16</reflink>][<reflink idref="bib16" id="ref67">16</reflink>][<reflink idref="bib16" id="ref68">16</reflink>][<reflink idref="bib16" id="ref69">16</reflink>] and [<reflink idref="bib61" id="ref70">61</reflink>][<reflink idref="bib61" id="ref71">61</reflink>][<reflink idref="bib61" id="ref72">61</reflink>][<reflink idref="bib61" id="ref73">61</reflink>] found that self-efficacy is a factor in the selection of business majors (sub-discipline pathway). Furthermore, they coupled perceived ability with behavioural control and suggested that this leads to a negative association with the perceived heavy workload of an accounting major. More recent studies, such as [<reflink idref="bib43" id="ref74">43</reflink>][<reflink idref="bib43" id="ref75">43</reflink>], found strong empirical evidence of the relationship between self-efficacy and motivation for business studies students. They argue that self-efficacy is important in determining effort and persistence. Moreover, [<reflink idref="bib80" id="ref76">80</reflink>][<reflink idref="bib80" id="ref77">80</reflink>][<reflink idref="bib80" id="ref78">80</reflink>][<reflink idref="bib80" id="ref79">80</reflink>] found an association between low MA and high self-efficacy and persistence.</p> <hd id="AN0177720741-5">2.2 Emotion and working memory</hd> <p>Related to self-efficacy, emotion is recognized as a concept fundamental to learning, and its relationship to mathematics performance has been explored, particularly concerning how it affects cognitive processing and actions. Emotions and their regulation are seen as keys to resilience and adaptation ([<reflink idref="bib21" id="ref80">21</reflink>][<reflink idref="bib21" id="ref81">21</reflink>][<reflink idref="bib21" id="ref82">21</reflink>], [<reflink idref="bib21" id="ref83">21</reflink>]). [<reflink idref="bib58" id="ref84">58</reflink>][<reflink idref="bib58" id="ref85">58</reflink>][<reflink idref="bib58" id="ref86">58</reflink>][<reflink idref="bib58" id="ref87">58</reflink>], [<reflink idref="bib59" id="ref88">59</reflink>]), in their research, found strong emotional responses linked to self-appraisal regarding students' goals and efforts in mathematical learning. Furthermore, [<reflink idref="bib18" id="ref89">18</reflink>][<reflink idref="bib18" id="ref90">18</reflink>][<reflink idref="bib18" id="ref91">18</reflink>][<reflink idref="bib18" id="ref92">18</reflink>] found that the accumulated self-appraisal of past events influences current behaviour and mathematics performance. In a similar vein, [<reflink idref="bib57" id="ref93">57</reflink>][<reflink idref="bib57" id="ref94">57</reflink>][<reflink idref="bib57" id="ref95">57</reflink>] found that the inhibiting influence of fear can be mitigated by experiences of success. Similarly, [<reflink idref="bib51" id="ref96">51</reflink>][<reflink idref="bib51" id="ref97">51</reflink>] highlighted the role of the metacognitive in controlling affective responses to empower students' mathematical learning. In particular, they find self-appraisal and self-regulation as keys to motivating persistence and participation in challenging growth opportunities, which are recognized as important for mathematical learning and performance. While their research considers cultural and societal influences together with prior learning experiences, they emphasize the importance of student agency.</p> <p>Emotions, such as apprehension and fear, are also associated with general test anxiety, particularly for perceived challenging subjects such as mathematics ([<reflink idref="bib28" id="ref98">28</reflink>][<reflink idref="bib28" id="ref99">28</reflink>], [<reflink idref="bib28" id="ref100">28</reflink>]). Test anxiety can be considered as an unpleasant emotional state that occurs within an evaluation context ([<reflink idref="bib69" id="ref101">69</reflink>], [<reflink idref="bib69" id="ref102">69</reflink>]). While moderate levels of apprehension can be assumed to be integral to student testing, [<reflink idref="bib32" id="ref103">32</reflink>][<reflink idref="bib32" id="ref104">32</reflink>][<reflink idref="bib32" id="ref105">32</reflink>] found a high prevalence of levels of anxiety that impede performance. Unsurprisingly, MA and test anxiety have similar cognitive and physiological characteristics. However, [<reflink idref="bib38" id="ref106">38</reflink>][<reflink idref="bib38" id="ref107">38</reflink>] argued that they are distinct constructs. The meta-analysis carried out by [<reflink idref="bib15" id="ref108">15</reflink>][<reflink idref="bib15" id="ref109">15</reflink>][<reflink idref="bib15" id="ref110">15</reflink>] found that MA has a stronger effect on mathematics performance than test anxiety. Further, they found that the potential mediating factors (gender, age, math task type and working memory dynamics) have different statistical significance for the two constructs. They suggest that heightened levels of general anxiety may become manifest in augmented levels of MA. Interestingly, studies on general anxiety have found a relationship between anxiety and working memory deficits ([<reflink idref="bib10" id="ref111">10</reflink>][<reflink idref="bib10" id="ref112">10</reflink>], [<reflink idref="bib10" id="ref113">10</reflink>]). This is interesting because further studies have found that working memory is particularly associated with the successful completion of mathematical tasks ([<reflink idref="bib56" id="ref114">56</reflink>][<reflink idref="bib56" id="ref115">56</reflink>][<reflink idref="bib56" id="ref116">56</reflink>], [<reflink idref="bib56" id="ref117">56</reflink>]; [<reflink idref="bib30" id="ref118">30</reflink>][<reflink idref="bib30" id="ref119">30</reflink>][<reflink idref="bib30" id="ref120">30</reflink>], [<reflink idref="bib30" id="ref121">30</reflink>]; [<reflink idref="bib15" id="ref122">15</reflink>][<reflink idref="bib15" id="ref123">15</reflink>], [<reflink idref="bib15" id="ref124">15</reflink>]). Moreover, [<reflink idref="bib4" id="ref125">4</reflink>][<reflink idref="bib4" id="ref126">4</reflink>][<reflink idref="bib4" id="ref127">4</reflink>][<reflink idref="bib4" id="ref128">4</reflink>] found that MA influences performance by compromising working memory capacity. Causality is difficult to establish, but a relationship between general anxiety, working memory and MA is an interesting avenue for further study.</p> <hd id="AN0177720741-6">2.3 Referent influence</hd> <p>Parental influence, together with the influence of peers, teachers and third-level lecturers/tutors, is a key thread in the literature discussing both MA and the selection of a business major. Several studies show that students have the propensity to develop MA when their parents also suffer from high MA ([<reflink idref="bib52" id="ref129">52</reflink>][<reflink idref="bib52" id="ref130">52</reflink>], [<reflink idref="bib52" id="ref131">52</reflink>]; [<reflink idref="bib17" id="ref132">17</reflink>][<reflink idref="bib17" id="ref133">17</reflink>][<reflink idref="bib17" id="ref134">17</reflink>], [<reflink idref="bib17" id="ref135">17</reflink>]). An empirical study by [<reflink idref="bib17" id="ref136">17</reflink>][<reflink idref="bib17" id="ref137">17</reflink>][<reflink idref="bib17" id="ref138">17</reflink>][<reflink idref="bib17" id="ref139">17</reflink>] found that parental pressure is a significant factor in students with heightened MA. Conversely, [<reflink idref="bib2" id="ref140">2</reflink>][<reflink idref="bib2" id="ref141">2</reflink>][<reflink idref="bib2" id="ref142">2</reflink>] found that strong levels of parental support ameliorate MA. Several studies examine the relationship between the efficacy of teachers and heightened MA in students ([<reflink idref="bib76" id="ref143">76</reflink>][<reflink idref="bib76" id="ref144">76</reflink>], [<reflink idref="bib76" id="ref145">76</reflink>]; [<reflink idref="bib34" id="ref146">34</reflink>], [<reflink idref="bib34" id="ref147">34</reflink>]), while a number of recent studies have explored the effect of peers on MA ([<reflink idref="bib31" id="ref148">31</reflink>][<reflink idref="bib31" id="ref149">31</reflink>], [<reflink idref="bib31" id="ref150">31</reflink>]; [<reflink idref="bib44" id="ref151">44</reflink>][<reflink idref="bib44" id="ref152">44</reflink>], [<reflink idref="bib44" id="ref153">44</reflink>]).</p> <p>Empirical studies in the literature examining the significance of referents in business major selection do not arrive at a consensus. For example, [<reflink idref="bib54" id="ref154">54</reflink>][<reflink idref="bib54" id="ref155">54</reflink>][<reflink idref="bib54" id="ref156">54</reflink>] provided evidence that parents and instructors have a significant influence on students' major selection, while [<reflink idref="bib48" id="ref157">48</reflink>][<reflink idref="bib48" id="ref158">48</reflink>][<reflink idref="bib48" id="ref159">48</reflink>][<reflink idref="bib48" id="ref160">48</reflink>] found a low influence. A more recent study by [<reflink idref="bib19" id="ref161">19</reflink>][<reflink idref="bib19" id="ref162">19</reflink>][<reflink idref="bib19" id="ref163">19</reflink>][<reflink idref="bib19" id="ref164">19</reflink>] explored the influence of cultural values on students' pursuit of a career in accounting. They found that the influence of parents and peers is very strong in students from countries within cultures characterized by collectivism, large power distance and/or uncertainty avoidance. Moreover, [<reflink idref="bib77" id="ref165">77</reflink>][<reflink idref="bib77" id="ref166">77</reflink>][<reflink idref="bib77" id="ref167">77</reflink>][<reflink idref="bib77" id="ref168">77</reflink>] argued that a person's subjective norms (which they identify as a key determinant of behaviour) are influenced by the degree to which they are motivated to comply with referents. However, they also highlighted that the level of influence of referents changes with the timing of the major selection decision.</p> <hd id="AN0177720741-7">2.4 Career ideation and mathematics</hd> <p>Career ideation is a prominent factor examined in relation to students' selection of a business major but does not feature strongly in MA literature. However, analyses of career ideation often examine perceptions of associated mathematical focus. 'Mathematical skills, academic performance and employment opportunities appeared to be the control perceptions that distinguished between those who intend to major in accounting and non-accounting' ([<reflink idref="bib77" id="ref169">77</reflink>][<reflink idref="bib77" id="ref170">77</reflink>][<reflink idref="bib77" id="ref171">77</reflink>], [<reflink idref="bib77" id="ref172">77</reflink>], p. 251). Furthermore, [<reflink idref="bib74" id="ref173">74</reflink>][<reflink idref="bib74" id="ref174">74</reflink>][<reflink idref="bib74" id="ref175">74</reflink>][<reflink idref="bib74" id="ref176">74</reflink>] found that one of the most important factors for students electing <emph>not</emph> to major in business information systems is the high mathematics content. Accounting, finance and majors in information systems are perceived to be more difficult because of their higher mathematics and analytical skills requirements ([<reflink idref="bib25" id="ref177">25</reflink>][<reflink idref="bib25" id="ref178">25</reflink>], [<reflink idref="bib25" id="ref179">25</reflink>]).</p> <hd id="AN0177720741-8">2.5 Gender</hd> <p>Gender as an influencing factor is often considered and cross-referenced with other influencing factors such as self-efficacy. A number of studies find men's mathematics self-efficacy beliefs to be significantly stronger than women's, with consistency in these findings across different cultural and geographical settings ([<reflink idref="bib36" id="ref180">36</reflink>], [<reflink idref="bib36" id="ref181">36</reflink>]; [<reflink idref="bib35" id="ref182">35</reflink>][<reflink idref="bib35" id="ref183">35</reflink>][<reflink idref="bib35" id="ref184">35</reflink>], [<reflink idref="bib35" id="ref185">35</reflink>]; [<reflink idref="bib64" id="ref186">64</reflink>], [<reflink idref="bib64" id="ref187">64</reflink>]). An empirical study by [<reflink idref="bib55" id="ref188">55</reflink>][<reflink idref="bib55" id="ref189">55</reflink>][<reflink idref="bib55" id="ref190">55</reflink>][<reflink idref="bib55" id="ref191">55</reflink>] on the disparity in self-efficacy between boys and girls (upper secondary) found that girls would prefer not to answer rather than submit an incorrect answer. Further studies comparing students of similar mathematics abilities find lower mathematics self-efficacy in women results in weaker performance and elevated attrition rates ([<reflink idref="bib35" id="ref192">35</reflink>][<reflink idref="bib35" id="ref193">35</reflink>][<reflink idref="bib35" id="ref194">35</reflink>], [<reflink idref="bib35" id="ref195">35</reflink>]). This has a resultant impact on career pathways and contributes to the significant under-representation of women in STEM careers. Statistics from the U.S. Census Bureau show that women made up 27% of the STEM workforce in 2019 ([<reflink idref="bib79" id="ref196">79</reflink>][<reflink idref="bib79" id="ref197">79</reflink>][<reflink idref="bib79" id="ref198">79</reflink>], [<reflink idref="bib79" id="ref199">79</reflink>]). According to 2019 Central Statistics Office data, Ireland has the highest percentage of graduates in STEM in Europe (3.52%) but the largest gender differential (STEM graduates that are men account for 4.73% of graduates aged 20–29 years compared with 2.3% women). This is interesting when considered along with findings by The STEM Education Review Group which finds that only 25% of the Irish workforce working in STEM are women ([<reflink idref="bib22" id="ref200">22</reflink>][<reflink idref="bib22" id="ref201">22</reflink>][<reflink idref="bib22" id="ref202">22</reflink>], [<reflink idref="bib22" id="ref203">22</reflink>]).</p> <p>A number of studies focus on the effect of gender on how MA manifests in test anxiety and numerical task anxiety. For example, [<reflink idref="bib23" id="ref204">23</reflink>][<reflink idref="bib23" id="ref205">23</reflink>][<reflink idref="bib23" id="ref206">23</reflink>] found higher levels of MA and test anxiety for girls (UK secondary school students). Furthermore, when they control for test anxiety, the negative correlation between MA and performance remains for girls only. Their regression analysis provides evidence that MA is a significant predictor of performance for girls but not for boys. [<reflink idref="bib5" id="ref207">5</reflink>][<reflink idref="bib5" id="ref208">5</reflink>][<reflink idref="bib5" id="ref209">5</reflink>][<reflink idref="bib5" id="ref210">5</reflink>] found a significant difference by gender in the results of the gender scale Revised Mathematics Anxiety Rating Scale (RMARS). However, men show significantly higher results in the RMARS subscale numerical task anxiety. Other studies found no gender differences for MA ([<reflink idref="bib13" id="ref211">13</reflink>][<reflink idref="bib13" id="ref212">13</reflink>], [<reflink idref="bib13" id="ref213">13</reflink>]; [<reflink idref="bib1" id="ref214">1</reflink>], [<reflink idref="bib1" id="ref215">1</reflink>]), while a meta-analysis by [<reflink idref="bib7" id="ref216">7</reflink>][<reflink idref="bib7" id="ref217">7</reflink>][<reflink idref="bib7" id="ref218">7</reflink>] found the correlation between MA and Mathematics performance to be similar for both men and women. Interestingly, [<reflink idref="bib40" id="ref219">40</reflink>][<reflink idref="bib40" id="ref220">40</reflink>][<reflink idref="bib40" id="ref221">40</reflink>] found that gender, as an influencing factor for MA, varies by age. [<reflink idref="bib5" id="ref222">5</reflink>][<reflink idref="bib5" id="ref223">5</reflink>][<reflink idref="bib5" id="ref224">5</reflink>][<reflink idref="bib5" id="ref225">5</reflink>] observed that older students exhibit higher anxiety for test and course anxiety but lower anxiety for numerical tasks. Within the Irish third-level education sector, a study by [<reflink idref="bib72" id="ref226">72</reflink>][<reflink idref="bib72" id="ref227">72</reflink>][<reflink idref="bib72" id="ref228">72</reflink>][<reflink idref="bib72" id="ref229">72</reflink>] focused on the experiences of mature students where they find MA to have a profound impact on education and career pathways.</p> <p>Cross-referencing gender with the influence of referents, [<reflink idref="bib46" id="ref230">46</reflink>][<reflink idref="bib46" id="ref231">46</reflink>][<reflink idref="bib46" id="ref232">46</reflink>][<reflink idref="bib46" id="ref233">46</reflink>] provided evidence that girls are more influenced by the opinion of adults while boys formulate their self-efficacy based on personal attributes. This suggests that the relationship between gender and MA is more nuanced and therefore requires a multifactorial approach. Of particular relevance to the Irish context of this study is the finding by [<reflink idref="bib75" id="ref234">75</reflink>][<reflink idref="bib75" id="ref235">75</reflink>][<reflink idref="bib75" id="ref236">75</reflink>], that greater disparity in gender MA (with participants in late teens) was observed in more developed countries with strong metrics on gender equality. Although counterintuitive, [<reflink idref="bib55" id="ref237">55</reflink>][<reflink idref="bib55" id="ref238">55</reflink>][<reflink idref="bib55" id="ref239">55</reflink>][<reflink idref="bib55" id="ref240">55</reflink>] rationalized this as an increased fear of failing to meet the heightened expectations for women. These findings further reinforce the need to explore the factors affecting MA in business studies students facing changing curricula (and thereby changing expectations) to meet the data analytics needs of the business community.</p> <p>Research studies examining women in STEM programmes and STEM careers identify mathematics as a key influencing factor. [<reflink idref="bib20" id="ref241">20</reflink>][<reflink idref="bib20" id="ref242">20</reflink>][<reflink idref="bib20" id="ref243">20</reflink>][<reflink idref="bib20" id="ref244">20</reflink>] described mathematics self-efficacy as an early leak in the gender pipeline to STEM. They argue that the reason women feel out of place in STEM is because of the ubiquitous stereotyping of STEM fields as the domain of men. As the discipline of business studies becomes increasingly STEMified, the barriers to engagement with the more analytical aspects of business (for example, machine learning, data analytics, coding) need to be addressed. This study aims to examine the potential inhibiting presence of MA in business studies students.</p> <hd id="AN0177720741-9">3 Methodology</hd> <p>We adapt the MAS-UK survey to capture demographic and attitudinal information from undergraduate business studies students in their second, third or fourth year of study enrolled at the University of Limerick. The number of survey participants was 305. However, a number of these responses were excluded in parts of the analysis as they had not fully completed the MAS-UK component ([<reflink idref="bib39" id="ref245">39</reflink>], [<reflink idref="bib39" id="ref246">39</reflink>]). The number of completed surveys is 245. We elected to exclude first-year students from the invitation to participate, reasoning that anxieties around the transition to tertiary education could skew the results. Furthermore, students choose their elective pathway in the second year of study, thus determining their business studies specialism which is an important aspect of the study. The survey was hosted by Qualtrics and analysed using SPSS version 28.</p> <p>The study acquired research ethics approval and participants were informed about their rights to opt-out at any stage of the survey and importantly, the independence of the study from their academic progression. Participation was online and participants were asked to provide some non-identifying demographical details. This is important for the integrity of the survey and was part of the assurances provided to participants. For this reason, we have not included participants who identified as non-binary or other, as they may be able to identify themselves, or be identified by others, in the survey results which would contravene the assurances provided to participants.</p> <p>Our study showed a majority of participants in the 20- to 25-year age bracket. This is not surprising for an undergraduate programme that targets secondary school-leavers applying through the Central Applications Office (CAO) system. The Central Applications Office is responsible for overseeing undergraduate applications to colleges and universities in the Republic of Ireland. The impact of excluding or including participants from other age brackets has minimal effect on the results; this means we have a relatively homogeneous group, with a high percentage coming through the Irish Leaving Certificate (LC) programme. The Irish LC programme is the terminal secondary education examination and is used to map results into 'points', which are then used by the CAO to determine entry into Irish Higher Education Institutions (HEI) ([<reflink idref="bib60" id="ref247">60</reflink>][<reflink idref="bib60" id="ref248">60</reflink>][<reflink idref="bib60" id="ref249">60</reflink>], [<reflink idref="bib60" id="ref250">60</reflink>]). Given that for the majority of the study participants, LC mathematics is a key component of their life history with mathematics, it is important to deliberate this context. Mathematics LC can be undertaken at Foundation, Ordinary and Higher-Level, reflecting increasing levels of difficulty. Though not strictly compulsory for LC, mathematics has been treated as such by secondary schools since Higher or Ordinary Leaving Cert Mathematics is a gatekeeper subject for many third-level programmes. Interestingly, 32.9% of students completed the Higher Level option in 2019 ([<reflink idref="bib62" id="ref251">62</reflink>][<reflink idref="bib62" id="ref252">62</reflink>], [<reflink idref="bib62" id="ref253">62</reflink>]). Statistics for 2020 and 2021 are less reliable as, due to the COVID-19 pandemic, predicted and hybrid-predicted grades respectively were deployed. The LC grading scale was reformed in 2017 and 95% of the survey participants undertook the terminal exam under these reformed grading scales. Significantly, bonus points are attained by those achieving at least a pass grade at a higher level in mathematics. This is designed to incentivize students to elect to undertake the higher-level option in mathematics. The 'bonus points' incentive arguably gives mathematics an augmented position inferring its superiority in differentiating levels of intelligence relative to other LC subjects, notably English. This is potentially problematic in an individual's life history of mathematics.</p> <p>The undergraduate business studies programmes are designed to have a 'common entry' point with the opportunity for students to select their discipline specialism as they progress through the programme. We asked the survey participants to evaluate their perceived mathematical difficulty of the programme prior to commencement and currently. We further asked them to rate the mathematical difficulty of a range of business discipline pathways. Finally, we asked the participants to rate the factors that influenced their choice of pathway. To avoid unduly leading participants to respond strongly to an 'avoidance of mathematics' factor, we reframed this as a positively worded statement. This will enable us to examine the influence of MA on the choice of business major.</p> <hd id="AN0177720741-10">3.1 Measuring attitudes and attainment</hd> <p>We asked participants to rate their current mathematical ability, their ability at secondary school and their ability at primary school.</p> <p>We asked participants to select their LC grade in mathematics from a grouped drop-down menu. They also selected whether they undertook the 'higher' or 'ordinary' level programme. We had no participants who undertook the 'foundation' level. Participants indicated the year in which they completed their LC Examinations. This is important because of reforms to the grading mechanism in 2017, as discussed above (Fig. 1).</p> <p>Graph: Fig. 1 Distribution of LC award categories.</p> <p>We categorized the LC grades as follows:</p> <hd id="AN0177720741-11">3.2 Mathematics anxiety survey</hd> <p>We use the MAS-UK survey ([<reflink idref="bib41" id="ref254">41</reflink>][<reflink idref="bib41" id="ref255">41</reflink>], [<reflink idref="bib41" id="ref256">41</reflink>]) to make observations about the levels of MA in the group studied. The MAS-UK was developed by [<reflink idref="bib41" id="ref257">41</reflink>][<reflink idref="bib41" id="ref258">41</reflink>][<reflink idref="bib41" id="ref259">41</reflink>] as a standardized measure of MA appropriate to British and European participants. They developed their survey based on the well-established U.S. Mathematics Anxiety Rating Scale (MARS) ([<reflink idref="bib71" id="ref260">71</reflink>][<reflink idref="bib71" id="ref261">71</reflink>][<reflink idref="bib71" id="ref262">71</reflink>], [<reflink idref="bib71" id="ref263">71</reflink>]).</p> <p>The MAS-UK 23 Likert-scale statements address three aspects of MA:</p> <p>(<reflink idref="bib1" id="ref264">1</reflink>) Maths evaluation anxiety.</p> <p>(<reflink idref="bib2" id="ref265">2</reflink>) Everyday/social maths anxiety.</p> <p>(<reflink idref="bib3" id="ref266">3</reflink>) Maths observation anxiety.</p> <p>The overarching question is 'How anxious would you feel in the following situations?' with an accompanying Likert-scale range starting from 1 'not at all' to 5 'very much'. The minimum score for the MAS-UK scale is 23 and the maximum is 115. With a higher number of related statements (<reflink idref="bib9" id="ref267">9</reflink>), the Mathematics evaluation anxiety component is shown to be the largest contributor to the variance of the MAS-UK score ([<reflink idref="bib41" id="ref268">41</reflink>][<reflink idref="bib41" id="ref269">41</reflink>], [<reflink idref="bib41" id="ref270">41</reflink>]). We examine relationships pertaining to the overall MAS-UK measure and those specific to the three sub-domains.</p> <p>MAS-UK has been used in various studies including [<reflink idref="bib72" id="ref271">72</reflink>][<reflink idref="bib72" id="ref272">72</reflink>][<reflink idref="bib72" id="ref273">72</reflink>][<reflink idref="bib72" id="ref274">72</reflink>], who combined the score with a mathematics life histories approach to examine the MA of mature students. Moreover, [<reflink idref="bib53" id="ref275">53</reflink>][<reflink idref="bib53" id="ref276">53</reflink>][<reflink idref="bib53" id="ref277">53</reflink>] used the MAS-UK scale to assess students' anxiety pre- and post-pedagogical interventions. Analysis of the neurophysiological relationship between MA and emotional states was undertaken by [<reflink idref="bib8" id="ref278">8</reflink>][<reflink idref="bib8" id="ref279">8</reflink>][<reflink idref="bib8" id="ref280">8</reflink>], who carried out a hierarchical cluster analysis of MAS-UK scores followed by emotional state analysis using an electroencephalogram (EEG) analysis. [<reflink idref="bib9" id="ref281">9</reflink>][<reflink idref="bib9" id="ref282">9</reflink>][<reflink idref="bib9" id="ref283">9</reflink>] used both the MAS-UK and the Revised MARS measure and found the two metrics to be internally consistent. An interesting study by [<reflink idref="bib42" id="ref284">42</reflink>][<reflink idref="bib42" id="ref285">42</reflink>][<reflink idref="bib42" id="ref286">42</reflink>] examined the relationship between eye movement and MA and finds a significant correlation between dwell time, fixations and saccades (rapid eye movement between fixation points). The use of the MAS-UK metric in these studies provides further assurance of its legitimacy and effectiveness as a measure of MA.</p> <hd id="AN0177720741-12">4 Findings</hd> <p>The number of completed surveys is 245; however, one entry appears to be an outlier, where on further examination, the survey duration was unrealistically short leading us to discount its veracity. Hence, our study is based on a sample size of 244, 110 men and 134 women. The mean value of the MAS-UK survey is 50.11, minimum value 23 and maximum value 92. The data is positively skewed with some obvious gaps in the higher range of scores between 78 and 82, 82 and 85, 85 and 88 and again between 90 and 92. There is one small gap at the lower end at 25. The highest frequency of 10 is observed for the score of 33.</p> <p>Where appropriate, the MAS-UK scores and the scores of the subscales were cross-referenced with the demographical and participant perception data from the questionnaire. We include Cronbach's alpha in Table 2 to assess the reliability of the questions in the MAS-UK scale (and its subscales). Cronbach's alpha is a popular measure of internal consistency for surveys containing multiple Likert questions. The values in Table 1 indicate a high level of consistency for the MAS-UK scale and its subscales.</p> <p>Table 1 Categorization of LC grades</p> <p> <ephtml> <table><thead><tr><th>LC category. </th><th>Higher level post-2017. </th><th>Ordinary level post-2017. </th><th>Higher level pre-2017. </th><th>Ordinary level pre-2017. </th></tr></thead><tbody><tr><td>1</td><td>H1–H3</td><td /><td>A1–B3</td><td /></tr><tr><td>2</td><td>H4–H5</td><td /><td>C1–C3</td><td /></tr><tr><td>3</td><td>H6</td><td /><td>D1–D3</td><td>A1–A2</td></tr><tr><td>4</td><td /><td>O1–O3</td><td /><td>B1–B3</td></tr><tr><td>5</td><td>H7–H8</td><td>O4–O5</td><td /><td>C1–C3</td></tr><tr><td>6</td><td colspan="4">No answer/prefer not to say</td></tr></tbody></table> </ephtml> </p> <p>Table 1 Categorization of LC grades</p> <p> <ephtml> <table><thead><tr><th>LC category. </th><th>Higher level post-2017. </th><th>Ordinary level post-2017. </th><th>Higher level pre-2017. </th><th>Ordinary level pre-2017. </th></tr></thead><tbody><tr><td>1</td><td>H1–H3</td><td /><td>A1–B3</td><td /></tr><tr><td>2</td><td>H4–H5</td><td /><td>C1–C3</td><td /></tr><tr><td>3</td><td>H6</td><td /><td>D1–D3</td><td>A1–A2</td></tr><tr><td>4</td><td /><td>O1–O3</td><td /><td>B1–B3</td></tr><tr><td>5</td><td>H7–H8</td><td>O4–O5</td><td /><td>C1–C3</td></tr><tr><td>6</td><td colspan="4">No answer/prefer not to say</td></tr></tbody></table> </ephtml> </p> <hd id="AN0177720741-13">4.1 Gender</hd> <p>Cross-referencing the average MAS-UK scores by gender, we find the average score to be higher for women (55.02) than for men (44.15). The Mann–Whitney <emph>U</emph> test reveals a statistically significant difference between scores for men and women (<emph>U</emph> = 10444.0, <emph>p</emph> < 0.001). The gender-conditioned means across each of the subscales are also higher for women (Table 2). See Table 2 for subscale Mann–Whitney <emph>U</emph> test statistics, each of which attests to statistically significant differences in scores between men and women.</p> <p>Table 2</p> <p> <ephtml> <table><thead><tr><th>Distribution. </th><th>Mean—men. </th><th>Mean—women. </th><th>Standard deviation—men. </th><th>Standard deviation—women. </th><th>Median—men. </th><th>Median—women. </th><th>Mann–Whitney <italic>U</italic> test statistic. </th><th><italic>p</italic>-value. </th><th>Cronbach's alpha. </th></tr></thead><tbody><tr><td>MAS-UK</td><td>44.1455</td><td>55.0224</td><td>13.59967</td><td>14.97641</td><td>42</td><td>54.5</td><td>10444.0</td><td><italic>p</italic> < 0.001</td><td>0.925</td></tr><tr><td>Mathematics evaluation anxiety (MASUK1)</td><td>18.4727</td><td>24.7537</td><td>5.99650</td><td>6.83362</td><td>18</td><td>25</td><td>11086.5</td><td><italic>p</italic> < 0.001</td><td>0.881</td></tr><tr><td>Everyday/social mathematics anxiety (MASUK2)</td><td>14.7364</td><td>17.3955</td><td>4.58093</td><td>5.95979</td><td>14</td><td>16</td><td>9349.5</td><td><italic>p</italic> < 0.001</td><td>0.825</td></tr><tr><td>Mathematics observation anxiety (MASUK3)</td><td>10.9364</td><td>12.8732</td><td>5.01059</td><td>4.91648</td><td>9</td><td>12</td><td>9308.0</td><td><italic>p</italic> < 0.001</td><td>0.858</td></tr></tbody></table> </ephtml> </p> <p>Table 2</p> <p> <ephtml> <table><thead><tr><th>Distribution. </th><th>Mean—men. </th><th>Mean—women. </th><th>Standard deviation—men. </th><th>Standard deviation—women. </th><th>Median—men. </th><th>Median—women. </th><th>Mann–Whitney <italic>U</italic> test statistic. </th><th><italic>p</italic>-value. </th><th>Cronbach's alpha. </th></tr></thead><tbody><tr><td>MAS-UK</td><td>44.1455</td><td>55.0224</td><td>13.59967</td><td>14.97641</td><td>42</td><td>54.5</td><td>10444.0</td><td><italic>p</italic> < 0.001</td><td>0.925</td></tr><tr><td>Mathematics evaluation anxiety (MASUK1)</td><td>18.4727</td><td>24.7537</td><td>5.99650</td><td>6.83362</td><td>18</td><td>25</td><td>11086.5</td><td><italic>p</italic> < 0.001</td><td>0.881</td></tr><tr><td>Everyday/social mathematics anxiety (MASUK2)</td><td>14.7364</td><td>17.3955</td><td>4.58093</td><td>5.95979</td><td>14</td><td>16</td><td>9349.5</td><td><italic>p</italic> < 0.001</td><td>0.825</td></tr><tr><td>Mathematics observation anxiety (MASUK3)</td><td>10.9364</td><td>12.8732</td><td>5.01059</td><td>4.91648</td><td>9</td><td>12</td><td>9308.0</td><td><italic>p</italic> < 0.001</td><td>0.858</td></tr></tbody></table> </ephtml> </p> <p>Descriptive data for MAS-UK and its subscales, Mann–Whitney U test statistic for the MAS-UK scores and each of the subscales, and Cronbach's alpha</p> <p>Figure 2 shows a box plot categorized by gender and gives a strong indication that gender is an important differentiating factor in the overall values of the MAS-UK measure and the subscales.</p> <p>Graph: Fig. 2 MAS-UK and subscale scores categorized by gender.</p> <p>Similarly, for the survey sub-scales, we find that the population median is higher than the median for the population of gender category men and lower than the median for the gender category women. That is, the median MAS-UK score (and the median score for each of the subscales) for women is higher than the median score for men. These descriptive statistics flag the need for further examination of gender as a categorization and influential factor in MA.</p> <hd id="AN0177720741-14">4.2 Age category</hd> <p>We note that 96.7% of participants are in the age category 18–24 and we find the same medians across age categories for the MAS-UK scale and each of its subscales (<emph>p</emph>-values: MAS-UK, 0.253; MASUK1, 0.259; MASUK2, 0.28 and MASUK3, 0.256). This indicates that for our study population, age is not a significant differentiating factor.</p> <hd id="AN0177720741-15">4.3 Year of study</hd> <p>Forty percent of survey participants are in their second year of study (98 students), while the remaining 60% is split evenly between third and fourth year students (73 students in third and fourth years). The mean values for MAS-UK and its subscales show little variation when categorized by the year of study. We use the Kruskal–Wallis test to examine if the difference in scores is significant. The test result shows that the distribution of MAS-UK scores is the same across categories of year of study (χ<sups>2</sups>(<reflink idref="bib2" id="ref287">2</reflink>) = 0.619, Asymptotic Significance 0.919).</p> <p>Table 3</p> <p> <ephtml> <table><thead><tr><th>Perceived mathematical ability timepoint. </th><th>Correlation with LC results. </th><th>Correlation with MAS-UK. </th></tr></thead><tbody><tr><td>Primary education</td><td>−0.355</td><td>−0.489</td></tr><tr><td>Secondary education</td><td>−0.569</td><td>−0.514</td></tr><tr><td>Current time</td><td>−0.440</td><td>−0.517</td></tr></tbody></table> </ephtml> </p> <p>Table 3</p> <p> <ephtml> <table><thead><tr><th>Perceived mathematical ability timepoint. </th><th>Correlation with LC results. </th><th>Correlation with MAS-UK. </th></tr></thead><tbody><tr><td>Primary education</td><td>−0.355</td><td>−0.489</td></tr><tr><td>Secondary education</td><td>−0.569</td><td>−0.514</td></tr><tr><td>Current time</td><td>−0.440</td><td>−0.517</td></tr></tbody></table> </ephtml> </p> <p>Correlations of participants' ratings of their perceived ability at different significant time points in their education and their level of mathematics attainment as measured by the category of LC mathematics award. Significant at the 0.01 level (two-tailed). Note that we excluded participants who did not disclose their LC mathematics results, so the sample size is 239. Correlations of participants' ratings of their perceived ability at different significant time points in their education and their level of MA as measured by the MAS-UK scale. Significant at the 0.01 level (two-tailed).</p> <hd id="AN0177720741-16">4.4 Self-efficacy</hd> <p>We examine participants' perception of their mathematics ability cross-referenced with their level of MA as measured by the MAS-UK and its subscales. We ask participants to rate their current mathematical ability, their ability at secondary school and their ability at primary school. First, we note the correlations between perceived ability at these important reflection time points. The correlation between perceived ability in primary school and perceived ability in secondary school is 0.531 (<emph>p</emph> < 0.01), while the correlation between perceived ability at primary school and current perceived ability is 0.334 (<emph>p</emph> < 0.01). The Spearman correlation between perceived current ability and perceived ability at secondary school has the highest value at 0.634 (<emph>p</emph> = 0.01).</p> <p>Second, we look at the relationship between perceived ability and attained performance in mathematics at LC level. Note that four participants chose not to disclose their award level in LC mathematics and that the survey grouped the award levels as described in section 3.1. We find the strongest (negative) correlation of −0.569 between perceived ability at secondary school and attainment in LC mathematics. The correlation is negative as the perceived ability scale increases with positive perception of ability while the attainment categories are highest for category 1. These are the highest awards in LC, H1-H3 (receipt of bonus points) or under the pre-2017 LC grading mechanism A1-B3. The lowest correlation is for category 5. This category includes LC grades H7-H8 (non-receipt of bonus points), pre-2017 LC grades C1–C3 at higher level or O4–O5 ordinary level. The lower correlations between LC results and perceived ability at primary school currently reflects a belief that mathematical ability changes over time and that the LC results only reflect ability at that time point.</p> <p>Third, we look at the relationship between perceived ability and MA. The final column in Table 3 shows the measured association between perceived ability at significant time points and MA as measured by the MAS-UK scale. Unsurprisingly, we find that these correlations are negative. A negative correlation reflects decreasing anxiety corresponding to increasing perceived ability. We can see that the correlation between the MAS-UK measure and the perceived current ability scale is −0.517 which is only marginally stronger than the correlation with perceived ability at secondary school, −0.514.</p> <p>The mean value for perceived ability is highest for primary school (4.16) and depreciates for secondary school (3.53) and current time (3.24). When we layer this analysis with the gender categories, we find a significant difference in their means with men having consistently higher perceived ability than women at the three time points (Table 4).</p> <p>Table 4</p> <p> <ephtml> <table><thead><tr><th>. </th><th>. </th><th colspan="4">Perceived ability—primary. </th><th colspan="4">Perceived ability—secondary. </th><th colspan="4">Perceived ability—current. </th></tr><tr><th>. </th><th>N. </th><th>Mean. </th><th>SD. </th><th>Kurt. </th><th>Skew. </th><th>Mean. </th><th>SD. </th><th>Kurt. </th><th>Skew. </th><th>Mean. </th><th>SD. </th><th>Kurt. </th><th>Skew. </th></tr></thead><tbody><tr><td>Men</td><td>110</td><td>4.409</td><td>0.838</td><td>2.068</td><td>−1.468</td><td>3.791</td><td>0.731</td><td>−0.105</td><td>−0.227</td><td>3.482</td><td>0.687</td><td>−0.192</td><td>−0.106</td></tr><tr><td>Women</td><td>134</td><td>3.955</td><td>0.933</td><td>−0.363</td><td>−0.531</td><td>3.313</td><td>0.780</td><td>0.918</td><td>−0.131</td><td>3.045</td><td>0.734</td><td>1.468</td><td>−0.070</td></tr></tbody></table> </ephtml> </p> <p>Table 4</p> <p> <ephtml> <table><thead><tr><th>. </th><th>. </th><th colspan="4">Perceived ability—primary. </th><th colspan="4">Perceived ability—secondary. </th><th colspan="4">Perceived ability—current. </th></tr><tr><th>. </th><th>N. </th><th>Mean. </th><th>SD. </th><th>Kurt. </th><th>Skew. </th><th>Mean. </th><th>SD. </th><th>Kurt. </th><th>Skew. </th><th>Mean. </th><th>SD. </th><th>Kurt. </th><th>Skew. </th></tr></thead><tbody><tr><td>Men</td><td>110</td><td>4.409</td><td>0.838</td><td>2.068</td><td>−1.468</td><td>3.791</td><td>0.731</td><td>−0.105</td><td>−0.227</td><td>3.482</td><td>0.687</td><td>−0.192</td><td>−0.106</td></tr><tr><td>Women</td><td>134</td><td>3.955</td><td>0.933</td><td>−0.363</td><td>−0.531</td><td>3.313</td><td>0.780</td><td>0.918</td><td>−0.131</td><td>3.045</td><td>0.734</td><td>1.468</td><td>−0.070</td></tr></tbody></table> </ephtml> </p> <p>Descriptive statistics (mean, SD, kurtosis (Kurt) and skewness (Skew)) for perceived ability at primary, secondary and current time points conditioned by gender.</p> <p>It is interesting to note that we observe a depreciating trend in the mean values for perceived ability as we look at the three time points: primary, secondary and current time.</p> <p>Finally, we cross reference prior attainment, MA and gender. When we examine the relationship between prior attainment in LC and MA, we find a correlation of 0.464 (significant at 0.01). The strength of this correlation is higher for women (0.501) than for men (0.344). When we isolate only those in category 1, we find that the mean MAS-UK score for women is higher than the mean MAS-UK score for men (45.34 mean MAS-UK for women compared to 38.55 mean MAS-UK for men with standard deviations of 9.25 and 13.60 respectively). Furthermore, this difference is statistically significant (t(<reflink idref="bib80" id="ref288">80</reflink>) = −2.675 <emph>p</emph> = 0.009). This is also observed for other categories of attainment in LC mathematics. This suggests that even for students with comparable high levels of attainment (category 1), MA is heighted for women.</p> <hd id="AN0177720741-17">4.5 Statements with notable scores</hd> <p>In this section we explore statements within the MAS-UK measure that elicited notably high or low scores. It is worth noting that for 22 of 23 statements, the mean score for women is higher than for men. Statement 8 is the only question where this is reversed. Questions 3, 6, 18 and 23 show high mean scores of 3.61, 3.39, 3.34 and 3.22, respectively. The next highest mean question score is 2.75 and the average mean score is 2.18. See the Appendix for descriptive statistics. These high mean scores prompt further examination. When we look at the distributions of these scores categorized by gender, we find strong evidence of gender disparity. Questions 23 and 3 showed the highest difference in mean by gender.</p> <p>We calculate the cross-tabulation of question 3 (Writing an answer on the board) with gender. Calculating the conditional probability <emph>p</emph> (Likert score of 5 in Q3| Gender = Women) and the <emph>p</emph>(Likert score of 5 in Q3| Gender = Men), we find that there is a 36.57% probability of a Likert score of 5 (high anxiety) given that the individual is a woman compared to a 9.91% probability if the individual being a man.</p> <p>This question, '<emph>Q3. Being asked to write an answer on the board at the front of a maths class</emph>' while it is in the evaluation sub-scale may also trigger social anxiety which arguably contributes to the heightened anxiety response.</p> <p>Figure 3 demonstrates the disproportionately high representation of women exhibiting heightened or extreme anxiety to the scenario of being asked to write an answer on the board at the front of a maths class.</p> <p>Graph: Fig. 3 Breakdown in responses to Question 3. Likert score 1: Not at all anxious; Likert score 2: slightly anxious; Likert score 3: moderate anxiety; Likert score 4: heightened anxiety; Likert score 5: extremely anxious.</p> <p>Similarly, Questions 6, 18 and 23 exhibit a disproportionately high representation of women in heightened and extreme apprehension. The percentages of women within the cohort scoring 5 (extreme apprehension) are 77.50%, 73.49% and 86.57% for questions 6, 18 and 23, respectively. Correspondingly, there is a disproportionately low representation of women in scores 1 and 2, corresponding to <emph>Not at all anxious</emph> and <emph>Slight anxiety</emph> respectively. Perhaps unsurprisingly, two of these questions relate to being tested (Question 6: <emph>Taking a mathematics exam</emph>; Question 18: <emph>Being given a surprise mathematics test</emph>), while Question 23: <emph>Being asked a mathematics question by a teacher/lecturer in front of a class</emph>, has a public exposure element (Fig. 4).</p> <p>Graph: Fig. 4 Breakdown of scores for Q6, Q18 and Q23 conditioned by gender.</p> <p>Graph: Fig. 4 Continued.</p> <p>We also examine the opposite end of the scale where statements have low mean scores. The lower two quartiles of the distribution of mean scores are more tightly clustered. We can identify four questions that cluster significantly below the upper value of the first quartile 1.6926. These questions are Question 2: <emph>Adding up a pile of change</emph>; Question 4 <emph>Being asked to add up the number of people in a room</emph>; Question 9: <emph>Reading the word 'algebra'</emph> and Question 11: <emph>Working out how much time you have left before you set off to work or place of study.</emph> We note that these four statements with the lowest mean scores are also among the six statements with the lowest gender difference (Fig. 5).</p> <p>Graph: Fig. 5 Breakdown of Likert scores for Q2, Q4, Q9 and Q11 conditioned by gender.</p> <p>Graph: Fig. 5 Continued.</p> <p>For each of these low mean score questions, observations of Likert score 4 or 5 form between 2% and 7% of the population. Conversely, Likert scores of 1 represent between 68.9% to 76.2% of the population for these four questions. However, even in these low anxiety scenarios, when we condition on gender, the probability of a Likert score of 1 is at least 10% higher for men. In fact, for Question 11: <emph>Working out how much time you have left before you set off to work or place of study,</emph> 83.6% of men selected <emph>'Not at all anxious'</emph> as their response, while only 68.7% of women selected that response. This suggests that the scenario is dismissed more strongly for men than for women.</p> <p>Examining questions with high mean scores and those with low mean scores indicates that the significant gender disparity in the MAS-UK score is driven by higher scores in almost all scenarios; a higher likelihood for women to identify with Likert score 5: <emph>Extremely anxious</emph> than men, and a lower likelihood for women in the study to select Likert score 1: <emph>Not at all anxious.</emph></p> <hd id="AN0177720741-18">4.6 Prior beliefs and mathematical difficulty</hd> <p>We are interested in whether students electing to pursue an undergraduate programme in business studies are influenced by their perception of the difficulty of the programme. 71.7% of participants perceived the Business Studies programme to be <emph>Average</emph> to <emph>Not at all</emph> difficult mathematically (175 out of 244). Furthermore, the influence of the level of mathematical difficulty was rated as <emph>Not at all</emph> influential by 48.8% of the survey participants (119 of 244). The attitudinal section of the survey asked the participants to rate the influence of different factors on their selected study pathway (business major). A range of factors were utilized to avoid leading participants to myopically view the influence of mathematics. Furthermore, the question was framed as positive influences. We find the positive frame influence of <emph>Development of analytical/mathematical skills</emph> to be the highest ranked influence for 23.4% of survey participants (57 of 244). The mean rank of influences <emph>Alignment to career objectives</emph> and <emph>Personal interest</emph> were higher. However, the survey design allowed for additional commentary and ten students related their pathway choice to a strategy of mathematics avoidance. For example: 'Whether maths is very present or not' and 'One of my reasons that I get on so well in HR is because no maths involved in HR' were additional narratives added to the influence on programme pathway question.</p> <p>We asked participants to evaluate the mathematical difficulty (using 5-point Likert scales) of the key (sub-)discipline pathways within the common entry business programme. Accounting emerged as the business discipline with the highest perceived mathematical difficulty (mean score 3.6025). Human resources and Marketing received the lowest and second-lowest score for perceived mathematical difficulty (mean scores 1.605 and 1.7553, respectively). Relatedly, we asked participants to identify the dominant sub-discipline (major) of their elected study pathway. We cross-examined these results with the MAS-UK scores and found that the distribution of the anxiety scores differed across the pathway categories. Furthermore, we find that students who elect pathways majoring in Human Resources and Marketing display the highest median and upper-quartile MAS-UK across the pathway categories (median MAS-UK of 60 and 54, respectively, compared to the lowest category median for Business Information Systems at 32.5). Conditioning on the study pathway, we find a higher percentage of students in the two highest quartiles of MA as measured by MAS-UK for Human Resources and Marketing (65.7% and 72.8%, respectively). Within the population of survey participants, Marketing has the most significant gender gap, with a higher proportion of women. We conduct a three-way cross tabulation to examine the relationship between gender, MA and business major selection. Using a chi-square test, for men, there is insufficient evidence to reject the hypothesis that they are independent. However, for women, the chi-square test shows statistical evidence for dependence between gender, MA and business major selection (asymptotic significance, 0.038).</p> <hd id="AN0177720741-19">5 Discussion and conclusion</hd> <p>This paper has leveraged insights from studies examining MA and studies examining business major selection. Gender has been identified as an influencing factor in both, and indeed, this study found gender to be an important factor. First, we focused on the prevalence of MA in the surveyed undergraduate business studies students. When we conditioned our analysis on gender, we found that the women in the study exhibited heightened levels of MA as measured using the MAS-UK scale. In our study, women have shown augmented anxiety levels to their peers who are men even when cross-referenced with prior high attainment levels as measured by LC Mathematics grade (see Section 4.6). These results imply a systemic issue of heightened MA for women within the undergraduate business cohort. Furthermore, the phenomenon of higher MA for women compared to men persisted when we drilled down into the MAS-UK subscales. These subscales measure (<reflink idref="bib1" id="ref289">1</reflink>) mathematics evaluation anxiety, (<reflink idref="bib2" id="ref290">2</reflink>) everyday/social mathematics anxiety and (<reflink idref="bib3" id="ref291">3</reflink>) mathematics observation anxiety. We found that women in the study displayed higher anxiety scores across these three MA contexts. This contrasts with a previous study by [<reflink idref="bib5" id="ref292">5</reflink>][<reflink idref="bib5" id="ref293">5</reflink>][<reflink idref="bib5" id="ref294">5</reflink>][<reflink idref="bib5" id="ref295">5</reflink>] that used the RMARS and found that women displayed higher levels of mathematics test anxiety (analogous to subscale 1: mathematics evaluation anxiety), but men displayed higher levels of mathematical <emph>task</emph> anxiety (analogous to subscale 2: everyday/social MA).</p> <p>We further explored self-efficacy as a factor for which previous studies observed a significant negative relationship with MA, whereby as self-efficacy improves, levels of MA decrease. Our results show a similar dynamic. We used a self-reported measure for ability in at key time points, primary school, secondary school and current time. Interestingly, when we condition on gender, we find that the correlation between self-efficacy (as measured by perceived current ability in mathematics) and MA is marginally higher for men than for women in our study population. This finding is consistent with [<reflink idref="bib66" id="ref296">66</reflink>][<reflink idref="bib66" id="ref297">66</reflink>][<reflink idref="bib66" id="ref298">66</reflink>][<reflink idref="bib66" id="ref299">66</reflink>], who found that low self-efficacy in women resulted in higher anxiety and impeded performance.</p> <p>Similarly, we examined prior attainment and its relationship with MA. A causal study by [<reflink idref="bib50" id="ref300">50</reflink>][<reflink idref="bib50" id="ref301">50</reflink>][<reflink idref="bib50" id="ref302">50</reflink>][<reflink idref="bib50" id="ref303">50</reflink>] found that poor prior attainment can lead to the development of MA. However, the direction of causality is debated in [<reflink idref="bib14" id="ref304">14</reflink>][<reflink idref="bib14" id="ref305">14</reflink>][<reflink idref="bib14" id="ref306">14</reflink>]. Our study finds that prior attainment has a significantly stronger (negative) correlation with MA for women than for men in our study population. This suggests that positive prior attainment is a stronger mitigating factor for heightened MA in women than in men. The difference between these two self-efficacy measures is notable, with external validation underpinning the prior attainment factor. Interestingly, [<reflink idref="bib37" id="ref307">37</reflink>][<reflink idref="bib37" id="ref308">37</reflink>][<reflink idref="bib37" id="ref309">37</reflink>] found no significant gender difference in the level of MA. However, they found gender differences in the factors affecting MA. Their findings showed MA in men was strongly associated with test anxiety, while for women, it was more affected by perceived mathematical ability and standardized test scores.</p> <p>Interestingly, when we examine individual statements within the MAS-UK measure that have notably high mean scores, we find that women are more likely to select the highest anxiety rating, <emph>5: Extremely anxious.</emph> Even in statements eliciting low anxiety responses across the study population, women are less likely to select the lowest rating, <emph>1: Not at all anxious</emph>. It is also worth noting that the gender difference in the MAS-UK scores reflects a higher mean score for women for almost all of the 23 statements.</p> <p>Second, we examine the relevance of mathematics and MA in the choice of a business major. Prior studies have found that the highly numeric perception of particular majors impedes their selection as a business major ([<reflink idref="bib68" id="ref310">68</reflink>][<reflink idref="bib68" id="ref311">68</reflink>], [<reflink idref="bib68" id="ref312">68</reflink>]; [<reflink idref="bib63" id="ref313">63</reflink>], [<reflink idref="bib63" id="ref314">63</reflink>]). Our study finds the perceived level of mathematical difficulty to have a low influence on the decision to undertake a business studies programme. We find that the mean perceived level of mathematical difficulty before undertaking the programme does not deviate significantly from the mean current perception of mathematical difficulty. This suggests that the experienced level of mathematical difficulty of the business programme aligns with expectations. Drilling down further, we examined the influence of mathematical content on the choice of major. We find that students reported mathematical content to have a low influence on their choice of a business major.</p> <p>We find varying levels of perceived difficulty across the business majors. The <emph>Accounting</emph> major is rated as having the highest perceived mathematical difficulty. The major with the lowest perceived mathematical difficulty is <emph>Human Resources</emph>. <emph>Marketing</emph> had the second-lowest ranking for mathematical difficulty, which is consistent with [<reflink idref="bib63" id="ref315">63</reflink>][<reflink idref="bib63" id="ref316">63</reflink>]. We further find that the students who had selected the <emph>Marketing</emph> major had the highest mean MA level, while students pursuing <emph>Accounting</emph> displayed the lowest mean MAS-UK score. This suggests that, although students do not explicitly acknowledge the influence of perceived mathematical difficulty on their business major selection, students with higher levels of MA are more likely to select majors that are perceived to be less mathematically difficult. This avoidance strategy has significant implications for future gender disparity in key decision-making roles in business, such as Chief Financial Officer, gender representation on boards ([<reflink idref="bib11" id="ref317">11</reflink>][<reflink idref="bib11" id="ref318">11</reflink>], [<reflink idref="bib11" id="ref319">11</reflink>]) and biases in machine learning algorithms. We further find statistical evidence to suggest that for women, MA is a significant factor in business major selection. Further research could take a temporal approach to explore perceptions of mathematical difficulty and MA before and after students' major selection.</p> <p>Appendix</p> <p>MAS-UK statements.</p> <p></p> <p> <ephtml> <table><thead><tr><th>Statement. </th><th>How anxious would you feel in the following situations?. </th><th>Overall mean. </th><th>. </th><th>Overall mean—men. </th><th>Overall mean—women. </th><th>Difference in mean by gender. </th></tr></thead><tbody><tr><td>1</td><td>Having someone watch you multiply 12×23 on paper</td><td>2.221</td><td /><td>1.845</td><td>2.530</td><td>0.684</td></tr><tr><td>2</td><td>Adding up a pile of change</td><td>1.406</td><td /><td>1.291</td><td>1.500</td><td>0.209</td></tr><tr><td>3</td><td>Being asked to write an answer to a mathematical question on the board in front of a class</td><td>3.336</td><td /><td>2.800</td><td>3.776</td><td>0.976</td></tr><tr><td>4</td><td>Being asked to add up the number of people in a room</td><td>1.463</td><td /><td>1.373</td><td>1.537</td><td>0.165</td></tr><tr><td>5</td><td>Calculating how many days until a person's birthday</td><td>1.898</td><td /><td>1.727</td><td>2.037</td><td>0.310</td></tr><tr><td>6</td><td>Taking a mathematics exam</td><td>3.221</td><td /><td>2.818</td><td>3.552</td><td>0.734</td></tr><tr><td>7</td><td>Being asked to calculate €9.36 divided by 4 in front of several people</td><td>2.750</td><td /><td>2.255</td><td>3.157</td><td>0.902</td></tr><tr><td>8</td><td>Being given a telephone number and having to remember it</td><td>2.348</td><td /><td>2.418</td><td>2.291</td><td>−0.127</td></tr><tr><td>9</td><td>Reading the word 'algebra'</td><td>1.451</td><td /><td>1.409</td><td>1.485</td><td>0.076</td></tr><tr><td>10</td><td>Calculating a series of multiplication problems on paper</td><td>1.922</td><td /><td>1.709</td><td>2.097</td><td>0.388</td></tr><tr><td>11</td><td>Working out how much time you have left before you set off for work or place of study</td><td>1.324</td><td /><td>1.218</td><td>1.410</td><td>0.192</td></tr><tr><td>12</td><td>Listening to someone talk about mathematics</td><td>1.754</td><td /><td>1.618</td><td>1.866</td><td>0.247</td></tr><tr><td>13</td><td>Working out how much change a cashier should give you in a shop after buying several items in cash</td><td>1.672</td><td /><td>1.418</td><td>1.881</td><td>0.462</td></tr><tr><td>14</td><td>Deciding how much each person should give you after you buy an object for which you are all sharing the cost</td><td>1.713</td><td /><td>1.545</td><td>1.851</td><td>0.305</td></tr><tr><td>15</td><td>Reading a mathematics textbook</td><td>2.287</td><td /><td>2.109</td><td>2.433</td><td>0.324</td></tr><tr><td>16</td><td>Watching someone work out an algebra problem</td><td>1.779</td><td /><td>1.709</td><td>1.836</td><td>0.127</td></tr><tr><td>17</td><td>Sitting in a mathematics (or highly mathematical) class</td><td>2.594</td><td /><td>2.191</td><td>2.925</td><td>0.734</td></tr><tr><td>18</td><td>Being given a surprise mathematics test</td><td>3.607</td><td /><td>3.200</td><td>3.940</td><td>0.740</td></tr><tr><td>19</td><td>Being asked to memorize a multiplication table</td><td>2.361</td><td /><td>2.009</td><td>2.649</td><td>0.640</td></tr><tr><td>20</td><td>Watching a teacher/lecturer write equations on the board</td><td>2.135</td><td /><td>1.900</td><td>2.328</td><td>0.428</td></tr><tr><td>21</td><td>Being asked to calculate three fifths as a percentage</td><td>1.861</td><td /><td>1.345</td><td>2.284</td><td>0.938</td></tr><tr><td>22</td><td>Working out how much your shopping bill comes to</td><td>1.623</td><td /><td>1.491</td><td>1.731</td><td>0.240</td></tr><tr><td>23</td><td>Being asked a mathematics question by a teacher/lecturer in front of a class</td><td>3.393</td><td /><td>2.745</td><td>3.925</td><td>1.180</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead><tr><th>Statement. </th><th>How anxious would you feel in the following situations?. </th><th>Overall mean. </th><th>. </th><th>Overall mean—men. </th><th>Overall mean—women. </th><th>Difference in mean by gender. </th></tr></thead><tbody><tr><td>1</td><td>Having someone watch you multiply 12×23 on paper</td><td>2.221</td><td /><td>1.845</td><td>2.530</td><td>0.684</td></tr><tr><td>2</td><td>Adding up a pile of change</td><td>1.406</td><td /><td>1.291</td><td>1.500</td><td>0.209</td></tr><tr><td>3</td><td>Being asked to write an answer to a mathematical question on the board in front of a class</td><td>3.336</td><td /><td>2.800</td><td>3.776</td><td>0.976</td></tr><tr><td>4</td><td>Being asked to add up the number of people in a room</td><td>1.463</td><td /><td>1.373</td><td>1.537</td><td>0.165</td></tr><tr><td>5</td><td>Calculating how many days until a person's birthday</td><td>1.898</td><td /><td>1.727</td><td>2.037</td><td>0.310</td></tr><tr><td>6</td><td>Taking a mathematics exam</td><td>3.221</td><td /><td>2.818</td><td>3.552</td><td>0.734</td></tr><tr><td>7</td><td>Being asked to calculate €9.36 divided by 4 in front of several people</td><td>2.750</td><td /><td>2.255</td><td>3.157</td><td>0.902</td></tr><tr><td>8</td><td>Being given a telephone number and having to remember it</td><td>2.348</td><td /><td>2.418</td><td>2.291</td><td>−0.127</td></tr><tr><td>9</td><td>Reading the word 'algebra'</td><td>1.451</td><td /><td>1.409</td><td>1.485</td><td>0.076</td></tr><tr><td>10</td><td>Calculating a series of multiplication problems on paper</td><td>1.922</td><td /><td>1.709</td><td>2.097</td><td>0.388</td></tr><tr><td>11</td><td>Working out how much time you have left before you set off for work or place of study</td><td>1.324</td><td /><td>1.218</td><td>1.410</td><td>0.192</td></tr><tr><td>12</td><td>Listening to someone talk about mathematics</td><td>1.754</td><td /><td>1.618</td><td>1.866</td><td>0.247</td></tr><tr><td>13</td><td>Working out how much change a cashier should give you in a shop after buying several items in cash</td><td>1.672</td><td /><td>1.418</td><td>1.881</td><td>0.462</td></tr><tr><td>14</td><td>Deciding how much each person should give you after you buy an object for which you are all sharing the cost</td><td>1.713</td><td /><td>1.545</td><td>1.851</td><td>0.305</td></tr><tr><td>15</td><td>Reading a mathematics textbook</td><td>2.287</td><td /><td>2.109</td><td>2.433</td><td>0.324</td></tr><tr><td>16</td><td>Watching someone work out an algebra problem</td><td>1.779</td><td /><td>1.709</td><td>1.836</td><td>0.127</td></tr><tr><td>17</td><td>Sitting in a mathematics (or highly mathematical) class</td><td>2.594</td><td /><td>2.191</td><td>2.925</td><td>0.734</td></tr><tr><td>18</td><td>Being given a surprise mathematics test</td><td>3.607</td><td /><td>3.200</td><td>3.940</td><td>0.740</td></tr><tr><td>19</td><td>Being asked to memorize a multiplication table</td><td>2.361</td><td /><td>2.009</td><td>2.649</td><td>0.640</td></tr><tr><td>20</td><td>Watching a teacher/lecturer write equations on the board</td><td>2.135</td><td /><td>1.900</td><td>2.328</td><td>0.428</td></tr><tr><td>21</td><td>Being asked to calculate three fifths as a percentage</td><td>1.861</td><td /><td>1.345</td><td>2.284</td><td>0.938</td></tr><tr><td>22</td><td>Working out how much your shopping bill comes to</td><td>1.623</td><td /><td>1.491</td><td>1.731</td><td>0.240</td></tr><tr><td>23</td><td>Being asked a mathematics question by a teacher/lecturer in front of a class</td><td>3.393</td><td /><td>2.745</td><td>3.925</td><td>1.180</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead><tr><th>Reference name. </th><th>Description. </th><th>Question range. </th><th>No. of questions. </th></tr></thead><tbody><tr><td>MASUK1</td><td>Mathematics evaluation anxiety</td><td>Q1, Q3, Q6, Q7, Q10, Q18, Q19, Q21, Q23</td><td>9</td></tr><tr><td>MASUK2</td><td>Everyday/social mathematics anxiety</td><td>Q2, Q4, Q5, Q8, Q11, Q13, Q14, Q22</td><td>8</td></tr><tr><td>MASUK3</td><td>Mathematics observation anxiety</td><td>Q9, Q12, Q15, Q16, Q17, Q20</td><td>6</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead><tr><th>Reference name. </th><th>Description. </th><th>Question range. </th><th>No. of questions. </th></tr></thead><tbody><tr><td>MASUK1</td><td>Mathematics evaluation anxiety</td><td>Q1, Q3, Q6, Q7, Q10, Q18, Q19, Q21, Q23</td><td>9</td></tr><tr><td>MASUK2</td><td>Everyday/social mathematics anxiety</td><td>Q2, Q4, Q5, Q8, Q11, Q13, Q14, Q22</td><td>8</td></tr><tr><td>MASUK3</td><td>Mathematics observation anxiety</td><td>Q9, Q12, Q15, Q16, Q17, Q20</td><td>6</td></tr></tbody></table> </ephtml> </p> <p> <bold>Dr Orla McCullagh</bold> is a lecturer in risk management and insurance at the University of Limerick, teaching modules across the overlapping disciplines of risk, insurance and finance at the undergraduate, postgraduate and professional education levels. Previously, McCullagh worked in financial services in various quantitative analyst roles. She has a PhD in quantitative finance, and her research interests include mathematics education, financial literacy and the role of calculative technology at the intersection between capital markets and society.</p> <p> <bold>Dr Maria Ryan</bold> is a lecturer in business at Mary Immaculate College, Thurles. Her research focuses on mathematics anxiety and examines its impact on mature students, primary and secondary students and secondary teachers. She is a co-chair and researcher with the Mathematical Resilience Network—Ireland branch.</p> <p> <bold>Dr Olivia Fitzmaurice</bold> is a senior lecturer in mathematics education and the director of the Mathematics Learning Centre at the University of Limerick. 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Header DbId: eric
DbLabel: ERIC
An: EJ1427607
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PubType: Academic Journal
PubTypeId: academicJournal
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IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Mathematics Anxiety in Undergraduate Business Studies Students
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Orla+McCullagh%22">Orla McCullagh</searchLink><br /><searchLink fieldCode="AR" term="%22Maria+Ryan%22">Maria Ryan</searchLink><br /><searchLink fieldCode="AR" term="%22Olivia+Fitzmaurice%22">Olivia Fitzmaurice</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Teaching+Mathematics+and+Its+Applications%22"><i>Teaching Mathematics and Its Applications</i></searchLink>. 2024 43(2):125-146.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Oxford University Press. Great Clarendon Street, Oxford, OX2 6DP, UK. Tel: +44-1865-353907; Fax: +44-1865-353485; e-mail: jnls.cust.serv@oxfordjournals.org; Web site: http://teamat.oxfordjournals.org/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 22
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Business+Education%22">Business Education</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+Anxiety%22">Mathematics Anxiety</searchLink><br /><searchLink fieldCode="DE" term="%22Majors+%28Students%29%22">Majors (Students)</searchLink><br /><searchLink fieldCode="DE" term="%22Course+Selection+%28Students%29%22">Course Selection (Students)</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Beliefs%22">Beliefs</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Ireland%22">Ireland</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1093/teamat/hrae001
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0268-3679<br />1471-6976
– Name: Abstract
  Label: Abstract
  Group: Ab
  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.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1427607
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1427607
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1093/teamat/hrae001
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
        StartPage: 125
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Business Education
        Type: general
      – SubjectFull: Mathematics Anxiety
        Type: general
      – SubjectFull: Majors (Students)
        Type: general
      – SubjectFull: Course Selection (Students)
        Type: general
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: Beliefs
        Type: general
      – SubjectFull: Self Efficacy
        Type: general
      – SubjectFull: Ireland
        Type: general
    Titles:
      – TitleFull: Mathematics Anxiety in Undergraduate Business Studies Students
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Orla McCullagh
      – PersonEntity:
          Name:
            NameFull: Maria Ryan
      – PersonEntity:
          Name:
            NameFull: Olivia Fitzmaurice
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0268-3679
            – Type: issn-electronic
              Value: 1471-6976
          Numbering:
            – Type: volume
              Value: 43
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Teaching Mathematics and Its Applications
              Type: main
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