A Bibliometric Study on Mathematics Anxiety in Primary Education

Citation: Sagarduy, A.; Arrieta, N.; Antón, A. A Bibliometric Study on Mathematics Anxiety in Primary Education. Educ. Sci. 2024,14, 678. https://doi.org/10.3390/ educsci14070678 Academic Editor: Daniel Muijs Received: 29 April 2024 Revised: 7 June 2024 Accepted: 19 June 2024 Published: 21 June 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). education sciences Article A Bibliometric Study on Mathematics Anxiety in Primary Education Ainhoa Sagarduy * , Nikole Arrieta and Alvaro Antón Department of Didactics of Mathematics, Experimental and Social Sciences, Bilbao Faculty of Education, University of the Basque Country, Barrio Sarriena, 48940 Leioa, Bizkaia, Spain; [email protected] (N.A.); [email protected] (A.A.) *Correspondence: ainhoa.sagar[email protected] Abstract: Mathematics anxiety, stemming from negative perceptions and feelings of tension among students, significantly impacts academic outcomes and attitudes at all ages, starting from Primary Education. Thus, this study aimed to investigate the existing scientific literature on mathematics anxiety in this context. A bibliometric analysis was developed using the Core Collection of the Web of Science database, resulting in 360 scientific publications. The distribution of publications by journal, institution, country, and authorship, as well as the temporal evolution of them and the co-occurrence of keywords, was analysed and visualised through the SciMAT and VosViewer software. Findings reveal a growing interest in mathematics anxiety within the scientific community, particularly concerning its correlation with gender stereotypes and students’ mathematical perceptions at the primary level. Moreover, the distribution of publications highlights the United States as the primary contributor to this research, with a notable majority of distinguished female authors. Keywords: mathematics anxiety; primary education; bibliometric analysis; gender 1. Introduction Despite the fact that learning mathematics constitutes a basic pillar in the comprehensive training of students [ 1 ], there is a negative perception on the part of the students towards this discipline, stereotyping it as a complex subject with important detachments [ 2 ]. There is enormous variability in terms of the emotions and feelings that people experience in different mathematical contexts. Sometimes, mathematics is perceived as a set of rules and disconnected numbers that must be memorised mechanically, which generates displeasure and discomfort among students [ 3 ]. This unfavourable perception of mathematics is significantly manifested in the results of the last Programme for International Student Assessment (PISA) test, focused on mathematical competence, where the skills of 15-yearold students are evaluated in various disciplines, and where anxiety and unfavourable perceptions impact student achievement [4]. This adverse attitude and predisposition towards mathematics is known as mathematics anxiety [ 5 , 6 ]. This emotional response has been defined as the set of feelings of tension, worry, and fear that hinder the successful completion of tasks that involve the manipulation of numbers and mathematical reasoning, both in the school environment and in a daily context [ 7 – 9 ]. Indeed, the significant effects of math anxiety extend beyond academic performance, impacting students’ emotional well-being and educational experience. Research has shown that math anxiety can lead to the avoidance of math-related tasks, diminished self-confidence, and increased stress levels, ultimately hindering students’ ability to reach their full potential in mathematics and related fields [10]. Conversely, in mathematics anxiety, the following two dimensions are identified: a cognitive dimension, which encompasses concerns about failure in mathematical tasks, and an affective dimension, which encompasses the emotions of nervousness and tension Educ. Sci. 2024,14, 678. https://doi.org/10.3390/educsci14070678 https://www.mdpi.com/journal/education Educ. Sci. 2024,14, 678 2 of 19 in test situations. These dimensions reinforce the complexity of mathematics anxiety and highlight that it goes beyond simple negative emotions [11]. According to Pekrun’s control–value theory [ 12 ], math anxiety arises from the interaction between perceived control over learning outcomes and the value attributed to success in mathematics. This theory suggests that students experience math anxiety when they perceive low control over their performance and high value in succeeding in mathematics. Regarding the factors that influence this phenomenon, Fernández and Ayán propose the existence of both external and internal causes [ 13 ]. The external causes include those related to the context of the individual (school environment, family environment, gender stereotypes, etc.) and the internal causes include those that start from the individual themself (self-regulation ability, performance, etc.). Regarding the factors of external origin, it has been shown that the pedagogical strategies used in the classroom are directly related to students’ levels of mathematics anxiety and mathematical performance [ 14 ]. In addition, the mathematics anxiety experienced by teachers represents a limiting factor in the development of mathematical competence in the classroom [ 15 ]. The experience of mathematics anxiety by teachers seems to have a direct influence on the attitude of students towards the discipline and, consequently, on their own level of mathematics anxiety [ 16 – 18 ]. Likewise, other studies propose the existence of a direct relationship between the probability of a student experiencing mathematics anxiety and the mathematics anxiety experienced by their parents [ 19 , 20 ]. Regarding gender stereotypes, a recent study by Doz et al. reveals that girls tend to experience greater mathematics anxiety than do boys in the context of Primary Education [ 21 ]. However, no differences are found in relation to the gender variable in terms of precision in solving mathematical problems or in the perception of the difficulty of such problems. This finding aligns with those of other studies, highlighting the influence of mathematical gender stereotypes on anxiety and mathematical self-concept [22–25]. In contrast, among the internal causes, Blair and Ku find a negative correlation between self-regulation ability and levels of mathematics anxiety [ 26 ]. As students mature and develop their executive function skills, they demonstrate an increased ability to regulate their emotional response. In this sense, numerous studies have shown the negative effect of high levels of mathematics anxiety on performance [ 27 – 29 ]. However, math performance is commonly considered an outcome of math anxiety rather than just a precursor, as the relationship between math anxiety and math performance is bidirectional [ 17 ]. Conversely, Živkovi´c et al. find a positive correlation among mathematical performance, self-efficacy, and the enjoyment of mathematics [30]. Some of these factors are included among the tools used to measure mathematics anxiety. One of the first psychometric scales was the Mathematics Anxiety Rating Scale (MARS), developed by Richardson and Suinn [ 7 ]. Subsequently, specific scales have been adapted and developed for the context of Primary Education. The first scale was a shortened version of the MARS [ 31 ], followed by the Mathematics Anxiety Scale for Children (MASC) [ 32 ], and the Abbreviated Math Anxiety Scale (AMAS) [ 33 ]. Other tools, such as the Scale for Early Mathematics Anxiety (SEMA) [ 34 ], the Child Mathematical Anxiety Questionnaire (CMAQ) [ 35 ] and its revised version (R-CMAQ) [ 36 ], and the Mathematics Anxiety Scale for Young Children (MASYC) [ 37 ], have since been developed. To effectively advance the research on mathematics anxiety, it is imperative not only to examine the manifestations, causes, and tools of this emotional response, but also to understand its evolution and trends in the academic literature. Here, bibliometric analysis emerges as an indispensable tool. The interest in this strategy is motivated by the need to evaluate the progress of scientific production and its influence, and to understand the situation of the field in which such investigations are carried out [ 38 ]. Similarly, Cardona et al. indicate that through bibliometric studies, trends can be detected, and patterns that facilitate the identification of advances and the level of scientific development in a specific area, for which various bibliometric indicators are used, can be established [39]. To date, two studies have analysed publications on mathematics anxiety through a bibliometric approach—those of Ersozlu and Karakus [ 40 ] (Web of Science (WoS) and Educ. Sci. 2024,14, 678 3 of 19 Radevic and Milovanovi´c [ 41 ] (Scopus))—but neither of these studies has focused on a specific topic in the child population in general or in the Primary Education context particularly. Primary students represent a unique population with distinct developmental characteristics that make them particularly susceptible to math anxiety-related issues [ 42 ]. Their formative years are crucial to establish the bases of mathematical skills and attitudes that can influence their academic trajectory and emotional well-being throughout their lives [ 43 ]. Consequently, understanding and addressing math anxiety in Primary Education is essential for fostering positive learning experiences and outcomes. Therefore, the main objective of this study is to quantitatively analyse the existing scientific literature on mathematics anxiety in Primary Education to provide a panoramic view of the existing scientific findings. To achieve this objective, we propose the following specific objectives: to offer an overview of the evolution of the research on mathematics anxiety in this educational context; to identify the co-occurrence of the keywords used and analyse their impact in the area; and to identify the most active and relevant journals, institutions, countries, and authors to establish patterns of development, collaboration, and evolution over time. 2. Materials and Methods Next, the method used to collect the data and the procedure used for the analysis and visualisation of the data are described. 2.1. Data Sample First, the search syntax was identified from the keywords “math* anxiety” and “child”, “primary school”, or “primary education” in the journals indexed in the Core Collection of the WoS database to collect the largest possible number of scientific publications related to mathematics anxiety in Primary Education. Boolean operators (AND-OR) were used to improve the outcome of the publication search. The following citation indices were selected within the Core Collection: the Social Science Citation Index (SSCI), Science Citation Index Expanded (SCIE), Arts and Humanities Citation Index (AHCI), and Emerging Source Citation Index (ESCI). In this study, only articles, reviews, and early access articles were included for analysis, as they contained full information about the research ideas and results, and most of the publications were classified into the three categories. Book reviews, minute documents, book chapters, and editorial materials were excluded from this study in order to focus on original, peer-reviewed research that will provide significant contributions to scientific knowledge. These types of documents, although important in other contexts, may not offer the same level of scientific rigor or relevance to the objectives of the bibliometric study. A depuration of the database was also carried out to remove duplicated and nonrelated manuscripts. Finally, a total of 360 publications or metadata were included in the bibliometric analysis. Institutional access was required to download and analyse the content of many of the publications included in this study. This search was carried out in the second quarter of 2023, and the year of publication of the documents was not limited. 2.2. Data Analysis and Visualisation For the analysis and visualisation of the metadata imported from the WoS, SciMATv1.1.04 and VOSviewer 1.6.19 were used. 2.2.1. SciMAT A cleaning of the data corpus was carried out by combining or discarding terms that SciMAT recognised as synonyms based on the programmed differences (1 difference). This data cleaning process was carried out for the identification of both keywords and authors. For the analysis of the keywords, the keywords selected by both the author and the WoS journals were used. The data reduction frequency was set to 1 since the data volume was not large. The network was constructed by means of the co-occurrence of terms, with a minimum frequency of co-occurrence of 1. The measure of similarity of the Educ. Sci. 2024,14, 678 4 of 19 equivalence index was used to normalise the network due to its effectiveness in highlighting the structure of the network and facilitating the interpretation of the results [ 44 ]. For the clustering of keywords, the algorithm of simple centres was used with a minimum network size of 3 and a maximum size of 7 keywords. The main mapper was used routinely to determine associations among the documents. It refers to the algorithm used to map the thematic structure of the citation network as it identifies the main or dominant themes in the field of study. As a bibliometric measure of quality, the h index was used to select the number of documents since it is a measure to evaluate the influence and relevance of the articles. One of the analyses of the co-occurrence of keywords was performed using the centrality and density of Callon [ 45 ]. Centrality measures the importance of a topic in the development of the entire field of research being analysed. Conversely, density measures the strength that unites a topic with the rest of the keywords of the analysed research area. 2.2.2. VOSviewer VOSviewer visualisation maps were used to represent the results obtained from the bibliometric analysis. To refine the data and reduce the degree of variation in the terminology, a synonym dictionary file, also known as a Thesaurus, was generated. This file groups similar or related terms, facilitating the analysis by consolidating related concepts under a single label. In the maps, the nodes represent each element of the network, and the clusters represent a group of nodes closely related to each other. The colour, size, and centrality of the clusters, as well as the distance between them, provided information on the relationships or links between the elements analysed. The colour of the cluster represented the independence of the categories between the elements that made up the network. The intensity of the colour indicated the importance of the element within the category. The size of the cluster, similar to the intensity of colour and its centrality, represented the number of elements it encompassed, that is, the importance it had within the network. The distance between the nodes represented the degree of relationship between them and was expressed as the total strength of the link (total link strength), which indicates the total strength, that is, the sum total, of the links connecting the nodes. 3. Results The results obtained from the bibliometric analysis are presented below. The first four sections show the distribution of publications by journal, institution, country, and authorship. Next, the distribution of publications by year of publication is presented, and finally, the co-occurrence of keywords where the network map is analysed, as well as the parameters of centrality and density of Callon, are analysed. 3.1. Distribution by Journal The 360 publications analysed in this study were distributed in a total of 180 journals. Frontiers in Psychology topped the list, with a total of 35 papers (9.72% of the total) and 809 citations and a total link strength of 182. The most cited article in this journal was that of Carey et al. [46], with a total of 163 citations. The analysis of the network map revealed two well-differentiated clusters. The first cluster, represented in red, included journals such as Frontiers in Psychology,Contemporary Educational Psychology,Annals of the New York Academy of Sciences,Journal of Experimental Child Psychology,PLOS One,Developmental Science, and the British Journal of Educational Psychology. The second cluster, represented in green, included journals such as Learning and Individual Differences,Journal of Cognition and Development,Journal of Educational Psychology, Journal of Experimental Education,Mathematics Education Research Journal, and Journal of Early Childhood Teacher Education (Figure 1a). Educ. Sci. 2024,14, 678 5 of 19 Educ. Sci. 2024, 14, x FOR PEER REVIEW 5 of 20 and Individual Differences, Journal of Cognition and Development, Journal of Educational Psychology, Journal of Experimental Education, Mathematics Education Research Journal, and Journal of Early Childhood Teacher Education (Figure 1a). In addition, the analysis of the temporal visualisation map based on the distribution of publications by journal provided significant information on the current situation of the journals and their impact on the academic community. Annals of the New York Academy of Sciences and Mathematics Education Research Journal stood out due to their topicality, as illustrated in Figure 1b. Figure 1. Network (a) and temporal (b) visualisations of the distribution of publications by journal based on the number of citations. Table 1 presents the results of the map analysis, highlighting the 13 journals that met the requirements of having at least 5 publications and 15 citations. The journals are published by seven different editorials. Among them, Elsevier, Wiley-Blackwell, and Taylor and Francis stand out, since they had published 9 of the 13 contributions. These journals were organised according to the number of publications, total link strength, and number of citations. Figure 1. Network (a) and temporal (b) visualisations of the distribution of publications by journal based on the number of citations. In addition, the analysis of the temporal visualisation map based on the distribution of publications by journal provided significant information on the current situation of the journals and their impact on the academic community. Annals of the New York Academy of Sciences and Mathematics Education Research Journal stood out due to their topicality, as illustrated in Figure 1b. Table 1presents the results of the map analysis, highlighting the 13 journals that met the requirements of having at least 5 publications and 15 citations. The journals are published by seven different editorials. Among them, Elsevier, Wiley-Blackwell, and Taylor and Francis stand out, since they had published 9 of the 13 contributions. These journals were organised according to the number of publications, total link strength, and number of citations. 3.2. Distribution by Institution A total of 394 institutions that participated in the 360 publications analysed in this study were identified. Only those institutions with at least 5 publications and 50 citations were considered. Thus, 22 of the 394 institutions met this criterion and are presented in Table 2, and are ordered according to the total link strength and where the data on the number of publications and citations were also collected. Educ. Sci. 2024,14, 678 6 of 19 Table 1. Journals sorted by total link strength. Journal Editorial Total Link Strength Publications Citations Frontiers in Psychology Frontiers Media 35 182 809 Learning and Individual Differences Elsevier 15 83 337 Contemporary Educational Psychology Elsevier 10 101 224 Annals of the New York Academy of Science Wiley-Blackwell 10 54 19 Journal of Cognition and Development Taylor and Francis 7 94 387 Journal of Educational Psychology American Psychological Association 7 63 93 Journal of Experimental Child Psychology Elsevier 7 51 305 PLoS ONE Public Library of Science 6 38 394 Developmental Science Wiley-Blackwell 6 21 134 Journal of Experimental Education Taylor and Francis 5 55 206 British Journal of Educational Psychology Wiley-Blackwell 5 43 134 Mathematics Education Research Journal Springer 5 11 26 Journal of Early Childhood Teacher Education Taylor and Francis 5 6 29 Note: The colors used in the table indicate different clusters in the network, corresponding to the colors in the network visualization. Table 2. Institutions ordered by total link strength. Institution Total Link Strength Publications Citations University of Chicago 323 18 1615 University of Cambridge 208 10 729 University of Trieste 192 12 232 University of Padua 183 13 217 Florida State University 179 7 418 Stanford University 141 8 470 University of Ottawa 124 9 150 University of California Los Angeles 119 6 376 New York University 119 5 293 University of Oxford 113 9 169 University of Haifa 112 7 135 Temple University 104 5 350 Ohio State University 101 6 220 Tomsk State University 98 5 212 University of Colorado 93 5 247 Pontificia Universidad Católica de Chile 80 7 74 Purdue University 77 7 71 University of Florence 77 5 61 University of Minnesota 74 8 170 Columbia University 57 6 92 University of Jyväskylä 56 5 135 Beijing Normal University 56 12 82 Note: The colors used in the table indicate different clusters in the network, corresponding to the colors in the network visualization. Educ. Sci. 2024,14, 678 7 of 19 The network map showed two clearly differentiated clusters based on similarities in their characteristics and citation relationships (Figure 2a). The first cluster, represented in red, was composed of institutions such as the University of Chicago (US), University of Florida (US), University of Ottawa (US), University of California Los Angeles (US), University of Haifa (Israel), Temple University (US), Ohio University (US), Tomsk University (Russia), Pontificia Universidad Católica de Chile (Chile), Purdue University (US), University of Minnesota (US), and Columbia University (US). The second cluster, represented in green, included the University of Cambridge (England), University of Trieste (Italy), University of Padua (Italy), Stanford University (US), New York University (US), University of Oxford (England), University of Colorado (US), University of Florence (Italy), University of Peking (China), and the University of Jyväskylä (Finland). 1 Figure 2. Network (a) and temporal (b) visualisations of the distribution of publications by institution based on the number of citations. Educ. Sci. 2024,14, 678 8 of 19 In contrast, the temporal visualisation network map, built to take into account the distribution of publications by institution based on the citations, allowed us to identify the University of Ottawa, the Pontificia Universidad Católica de Chile, Purdue University, and the University of Peking as those institutions that were most notable for their production and more current publications (Figure 2b). 3.3. Distribution by Country The 360 publications analysed in this study were published in a total of 42 countries. Those countries with a minimum of 5 publications and 50 citations were included. Thus, 19 of the 42 countries met this criterion. Table 3presents the results according to the total link strength, the number of publications, and the number of citations. Table 3. Countries ordered by total link strength. Country Total Link Strength Publications Citations US 1229 118 4165 UK 727 39 1192 Italy 447 28 445 Germany 399 33 527 Canada 297 18 499 People’s Republic of China 226 30 172 Israel 193 12 165 Spain 187 19 123 Austria 171 8 251 Finland 170 7 139 Poland 146 7 55 Russia 132 5 212 Netherlands 124 8 209 Chile 121 9 74 Belgium 120 13 229 Turkey 74 18 159 Switzerland 58 8 160 Australia 44 13 120 Taiwan 23 7 145 Note: The colors used in the table indicate different clusters in the network, corresponding to the colors in the network visualization. The bibliometric network map, built to take into account the distribution of these publications based on the number of citations in the country, showed a network formed by six clusters, represented by different colours (Figure 3a). The US had the greatest bond strength (1229), the greatest number of publications (118), and the greatest number of citations (4165) (Figure 3b). Most importantly, the cluster represented in red was composed of the US, Canada, the Netherlands, Australia, and Taiwan. The second cluster, represented in green, included the UK, Italy, Israel, and Russia. The third cluster, represented in dark blue, was made up of Germany, Austria, Finland, and Switzerland. The fourth cluster, represented in yellow, included Poland, Belgium, and Turkey. The fifth cluster, represented in purple, included Spain and Chile. Finally, the sixth and last cluster, represented in light blue, included China. Conversely, in the analysis of the temporal distribution of these publications, China, Spain, Poland, and Chile stood out as having the highest number of current publications (Figure 3c). Educ. Sci. 2024,14, 678 9 of 19 Educ. Sci. 2024, 14, x FOR PEER REVIEW 10 of 20 Figure 3. Network (a), density (b), and temporal (c) visualisations of the distribution of publications by country based on the number of citations. 3.4. Distribution by Authorship In the 360 publications, a total of 933 authors were found. Only the 15 authors that met the established criteria of having a minimum of 6 publications were included in the analysis. Table 4 shows the distribution of authorship ordered according to total link Figure 3. Network (a), density (b), and temporal (c) visualisations of the distribution of publications by country based on the number of citations. 3.4. Distribution by Authorship In the 360 publications, a total of 933 authors were found. Only the 15 authors that met the established criteria of having a minimum of 6 publications were included in the analysis. Table 4shows the distribution of authorship ordered according to total link strength. It is noteworthy that 13 out of the 15 authors included in the analysis were women, who represent 87% of the total. Educ. Sci. 2024,14, 678 16 of 19 cognitive processes and individual differences, while the third cluster is more focused on educational aspects related to teaching and learning in Primary Education. Key concepts such as “academic performance”, “motivation”, and “individual differences” are identified as affecting mathematics anxiety, in agreement with the results of Wang et al. [ 53 ]. In addition, there is a growing interest in the relationship between “motivation” and mathematics anxiety. These results provide a solid foundation for future research and the development of effective interventions in this field. Furthermore, educators and policymakers can apply these findings practically by designing curricula and learning environments to alleviate math anxiety’s risk factors. Techniques such as reducing pressure and stress during math assessments and fostering supportive classroom environments can promote a positive attitude toward mathematics [54]. Despite the valuable findings obtained in this study, it is important to recognise some limitations that may have influenced the interpretation of the results. Although our methodological search strategy aimed to capture a broad range of relevant studies, the potential omission of studies using alternative terminology such as “elementary school” could be a limitation of this study. Additionally, as the focus was solely on Web of Science (WoS), the selection of databases for the literature search may have introduced potential biases. While WoS is widely used and recognised, excluding other databases like Scopus or PubMed may have omitted relevant studies published in different contexts. Moreover, while our main focus was to measure production trends in research on math anxiety at the Primary Education level, it is important to state that our analysis is primarily centred on the quantitative evolution of scientific production. Although the temporal evolution of keywords was considered, with motivation emerging as the most prominent term in recent publications, this methodology might have overlooked certain qualitative or more detailed content aspects. Despite these limitations, the results of this study offer significant insights into research on math anxiety at the Primary Education level and highlight key areas for future research in this field. 5. Conclusions The distribution of journals related to mathematics anxiety in Primary Education with the highest number of citations is concentrated mainly among three publishers (Elsevier, Wiley-Blackwell, and Taylor and Francis). The study of this distribution yields a classification that includes the following two clusters: one cluster that is more focused on psychology and another cluster that is more related to learning. Regarding geographic location, a certain structure is observed since the institutions of the most important cluster, in addition to including some of the largest and most recognised universities worldwide, such as the University of Chicago, Columbia University, or University of Florida, are located mainly in the US, with some exceptions, such as the University of Haifa in Israel and the University of Tomsk in Russia. In contrast, the institutions in the minority cluster, though they are also prestigious universities, are smaller or have less international recognition than the previous universities [ 55 ]. Additionally, these universities exhibit a more dispersed geographical distribution, with representation spanning across various countries such as the UK, Italy, the US, China, and Finland. This diversity in geographical locations suggests a broader global presence among the institutions in the minority cluster, potentially indicating a more inclusive and internationally collaborative research landscape. Moreover, there is growing interest on the part of the scientific community in the mathematics anxiety experienced by the youngest students—those in Primary Education. This finding points to an emerging trend that reflects the importance of addressing this phenomenon beginning in the early educational stages. The study of the co-occurrence or joint appearance of the keywords used in the 360 publications included in the bibliometric analysis of mathematics anxiety in Primary Education highlights the interest of the scientific community in understanding how factors Educ. Sci. 2024,14, 678 17 of 19 such as gender stereotypes or the perception of mathematics among students can influence the appearance and development of this phenomenon. Finally, the predominance of women among the authors who investigate mathematics anxiety in Primary Education is very noteworthy. This finding is influenced by aspects ranging from historical representation in related fields to the multidisciplinary nature of the subject, and even to differences in sensitivity to the emotional and social experiences of students [ 56 ]. In any case, this aspect indicates a promising direction for future research in the field, highlighting the importance of considering social and emotional aspects in the teaching and learning of mathematics in Primary Education. Author Contributions: Conceptualisation, A.S., N.A. and A.A.; formal analysis and investigation, A.S.; methodology and validation, A.S. and N.A.; writing—original draft, A.S., N.A. and A.A.; funding, A.A. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the projects GIU21/029 (University of the Basque Country, UPV/EHU) and PES17/39 (University of the Basque Country, UPV/EHU). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s. Acknowledgments: The authors acknowledge the assistance of T. Villarroel. Conflicts of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References 1. Rodríguez, M.E. La Matemática: Ciencia Clave En El Desarrollo Integral de Los Estudiantes de Educación Inicial Math. Zona Próxima 2010,13, 130–141. [CrossRef] 2. Mendías, J.S.; Alex, I.S.; Espigares, A.M. Ansiedad Matemática, Rendimiento y Formación de Acceso En Futuros Maestros. 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