**Abstract**

The topic of math anxiety has formed part of a heated discussion covering psychology and research in education for the last few years. Similarly, various international-based studies attest that the anxiety is due to influence registered on the students while in school, though there are fewer studies to justify this. Several countries have set up a big curriculum project through instituting changes in the high school based on the curriculum of teaching mathematics. The changes aim at realizing improvement in the mathematics knowledge of the nation for the reason the scores of math had not been appealing in comparison to the international scene for longer durations. The study aims to establish the linkage of anxiety and knowledge of mathematics. The survey on Revised Mathematics Anxiety (R-MANX) was conducted to the high school student population of 1352. The analysis of data was performed to explore the survey’s validity as well as its reliability and then translated to ascertain the linkage of anxiety in mathematics and success. Besides, the paper presents a report on the study’s findings.

*Keywords***: **anxiety in maths, validity, success of the student, reliability

**Anxiety in Maths among Students in High Schools**

**Chapter 1: Introduction**

Many people are often afraid of mathematics because of a poor attitude. Individuals often feel tense, apprehended, and fearful when they hear of circumstances requiring the use of mathematics (Shernoff et al., 2014). In this regard, such persons are said to be possessed with math anxiety. Through many options, Csikszentmihalyi et al. (2014) assert that it is possible to define math anxiety as a discomfort feeling, and specific aspects of disturbance that some people undergo when handling maths-related problems. Tension and apprehension feelings and even dreadness lead to the interference of the usual ways of handling the issues associated with math. For instance, students may have a high rate of the heartbeats, thus making them not to be able to handle the mathematical problems or even avoid courses associated with the subject. Despite the challenges that some of the high school students face during their studies, it is crucial to understand the existence and effects of such tensions. Civilization has led to an increasing demand for people in STEM fields. Therefore schools have the responsibility of ensuring that the learners have limited or no fear at all towards mathematics.

Formulating the mathematics curriculum represents a significant project where the ministry is in charge of education; many countries set up to realize improvement in the acquisition of knowledge (Csikszentmihalyi et al., 2014). The task of formulating the curriculum is a constituent of many nations’ objective started in the previous years to initiate reforms in the education sector. Also, the students’ performance in the subject represents a significant issue among the students themselves, parents, and teachers. For example, a theory is in place that suggests that success in the subject of maths has a linkage with economic prosperity. Learning institutions are using varied strategies of acquiring good outcomes in a relationship with the vision 20130 of the’ education (Maloney & Beilock, 2012). The high school math curriculum formed an area of focus, and the significant project commenced in April 2011, where the government institutions associated with high school mathematics education were engaged. The strategy of many nations is seeking to deploy the encouragement of rational thinking and development in the handling of problems. The implementation of the curriculum was done in the year 2013. As of now, it is ongoing with the training of teachers and research activity on the scenario of teaching maths and learning process plus the nations’ progress. In any case, it registers success; the same changes will indeed be implemented in higher learning institutions such as colleges.

Elsewhere, Ashcraft and Moore (2009) noted that the aspect of mathematics anxiety refers to the discomfort state linked to the performance of mathematical tasks that affect a sizeable proportion of the school-age pupils. In 2012, the study conducted by Csikszentmihalyi et al. (2014) on 433 secondary pupils established that the students face mathematical anxiety. The study also agreed that the aspect of tension calls for class attentiveness because of substantial evidence that the fear starts from as early as the primary school stages of education. In this regard, the study had a suggestion that a longitudinal type of research is essential in the investigation of the development of mathematics anxiety and the impact it has on the performance in the subject. Added to the same, the string and positive relationship between the two variables stressed the need to undertake studies on the anxiety in maths among high school (Shernoff et al., 2014). The results that will be obtained at the end of the research activity will assist educators, management, and parents in understanding the present status of the mathematical knowledge plus also seeking for ways of improving the performance of the pupils in the subjects in every grade.

**1.1 Aims of the Research**

- To undertake an exploration of the updated Revised Mathematics Anxiety (R-MANX) Survey validity together with reliability when put into use with students in high schools.
- To explore the linkages of the anxiety in mathematics and performance among the students in high school.

**Chapter 2: Literature Review**

The students’ anxiety towards mathematics is vital for educators (Csikszentmihalyi et al., 2014). Math is a critical subject in the curriculum of every school in each country all over the globe. From an early age, a child needs to be taught basic mathematics concepts to operate well in his or her daily life. The teaching of the subject has been done so that the children can be in a position of understanding the information. Also, the students should carry out less complicated tasks in their daily lives. On the same note, it is known that mathematics as a subject is not easy to learn within the students. Through mathematics education, scholars such as Li and Ma (2010) suggested the innovative means of teaching, linkage of the concept and real-life utilities, and the motivation of the students in being more interested in the subject so that they can manage the phobia associated with the mathematical concepts.

As far as from the year 1978, Li and Ma (2010) concurred that there was the application of regression equations using the relationship linking the Otis I.Q and mathematics achievements. In this case, a division was done on a sample of 246 pupils covering three groups of performers and nonperformers in the subject of mathematics. Evaluation of variance was utilized in comparing the three groups’ success based on the general anxiety, test forms of stress, and the mathematics type of fear. The outcomes from the study established that the measurement of the particular concern within maths as a subject was not similar to nonperformance from the other remaining two groups that were much stronger than general measurements and anxiety tests.

In the year 2014, a relationship of mathematics performance was carried out by Shernoff et al. (2014) concerning anxiety, the education of the mother, and gender. The study was conducted on the 17-year-old pupils with their origins from the USA and also Thailand, where they used the sample was at least 7000. A forty item test on the performance of math was utilized as the dependent variable, and the outcome was of anxiety in math and performance being crucial in the identified nations.

Ramirez et al. (2013) conducted a study to explore the nature-link with anxiety in mathematics from a sample of 106 grade two pupils. The results obtained from the survey revealed that the mathematics anxiety among the grade two pupils is a multi-dimensional form of construct. For instance, the unexpected kinds of reactions associated with the foundational concepts in mathematics, the statistical confidence associated with the computational type of skill, and also the worry that has no relationship to any form of the outcome.

The anxiety levels in mathematics have no difference in sex or language origin. Ozgen and Bindaka (2011) carried out a survey on the anxiety levels in the subject of mathematics among the early undergraduates who joined Nottingham University Malaysia in the year 2013. A sample of 206 students was provided with questionnaires for carrying out tests on the anxiety. The measurement of stress levels in maths was done by using seven Likert types of questionnaire-based statements that were extracted from the *‘Test Anxiety Inventory,*‘ describing the emotional form of feeling an individual has during the beginning of the examination. The results found from the study revealed that those pupils that had registered low scores in the subject appeared to be anxious in comparison to those that showed higher performance. Maloney and Beilock (2012), while carrying studies on the same topic, established that mathematics’s anxiety impacted the tasks in mathematics directly. The effects, in this case, have a more significant impact during the completion of a secondary work and eventually may lead to the distraction during the lecture hours or at the time of conducting tests or also during the accomplishment of more complicated tasks.

Li and Ma (2010), studying the relationship between memory, anxiety in mathematics, and performance, established that pupils with higher levels of stress often have small memory spans. Hence, if assigned computation types of tasks, their working memory that is reduced will tend to experience increment with errors. In this regard, there was a suggestion that a more empirical form of attention should be diverted towards mathematics anxiety.

Karimi and Venkatesan (2009) studied the impacts of maths anxiety among 80 fresh students who joined the Southeastern United States University. In this study, they conducted the observational type of survey by use of the pre-existing forms of data collected from the Freshman Orientation Survey that had nine-item *‘Abbreviated Math Anxiety Scale’* plus institutional based research forms of data. Outcomes from the study gave a suggestion that the standardized types of scores and the math anxiety are always endowed with the moderate and cynical form of relationship.

The way to ensure that students walk out of math anxiety indeed is a significant concern to Geist (2010), who had a belief that the issue of math anxiety may start from primary education up to final grade in high school education. The scholar went ahead to publish an article that attested that the previous experiences might bring anxiety in math in classrooms, the parents’ influences, and the recall of the past poor performance on the subject. Almost 75% of the Americans do not continue with studies of mathematics before they wind up their educational needs or job, as stated by Geist (2010). The same research revealed that students endowed with a higher degree of anxiety have low levels of success in mathematics and have little chance of pursuing the courses associated with the subject in their higher education. Hence, teachers need to be aware that students may end up suffering from math anxiety. Consequently, they need to deploy the teaching methodologies for lessening the tension in the subject while in the classroom.

Bekdemir (2010), in his research on math anxiety, collected data on a total of 745 high school category students covering grades one to four in five schools in Southern California. In the study, he utilized the tool for acquiring knowledge on environment and up-to-date Revised Mathematics Anxiety Index, where he found out the significant linkages between anxiety and the learning environment. According to the definition he provided, the learning environment is the sociology, psychology and pedagogy instances where the acquisition of knowledge that takes place, impacts on the success of the student and the attitudes as well. Similarly, teachers may also suffer from mathematics form of anxiety and may end up influencing what and the way they will teach their respective students.

Ozgen and Bindaka (2011) noted that at one time, a school in New York undertook the implementation of a math kind of clinic where the students had to attend classes at least once in a week to interact with the therapists in the subject. The teaching of the issue was not done at the start of the clinic. Instead, the students discussed their feelings toward the subject. Initially, the teacher was not at ease since he had fears that his class would lag as the students did not attend the mathematics lesson fully. Later, the teacher realized that the students were indeed progressing rapidly.

In another study by Beilock et al. (2010) on the evaluation of the training on the attitude of teachers towards mathematics, it established that the math anxiety impact on how teachers assess their respective capability of handling calculation. The same study also found out that teachers with high confidence stand a chance inappropriately developing the desired methods of teaching the subject of mathematics. Not forgetting, the study also suggested in service-based training to take place as a means of adding a focus on confidence among the teachers. In this way, they can enhance their outcomes in the subject towards the pupils as well as their urge to enjoy teaching the subject.

From the literature review, this study has established that there are yet to be enough studies concerning mathematics education, and also a few cases of researchers have managed to study the role played by anxiety in lower-performance in mathematics. Hence, there is a need to come up with a viable tool that can enhance the studies of math anxiety in the schools and eventually touch on this plus other hidden problems.

## Chapter 3: Methodology

**3.1 Population and Sample**

The study’s participants comprised 408 4^{th} grades, 392 3^{rd} grades, 301 2^{nd }classes, and 250 1^{st }graders. Concerning gender, 48.8% equivalents in 605 were females, while 55.2% that represent 747 males were engaged in the survey. The admission point was also taken into consideration, as shown in figure one below.

*Figure 1:* Range of admission points for the participants

**3.2 Research Design**

The nature of the research, according to Maloney and Beilock (2012), was quantitative since it seeks for the various students with anxiety in mathematics and scores that are low on the subject. The ‘R-MANX’ type of survey helped the scholars Ramirez et al. (2013) collect data from the surveyed students. The questionnaire had thirty statements in total, where every participant was graded on a scale of 1 for ‘never’ and 5 for ‘always.’ The reports described the daily life and the academic environments that need a mathematical idea or the tasks that are rated as the anxiety levels where the respondents believed they would go through the prevailing conditions. The survey was initially tested before proceeding to administer to a large group of students. The assessment of the report revealed that the tool had reliability, with a Cronbach Alpha coefficient value of 0.86, which was acceptable in this case.

**3.3 Exploration of Qualitative Methods of Study**

The R-MANX was utilized in acquiring data from a total of 1351 students who were all high school students. Students were challenged to give responses to the R-MANX type of questionnaire to determine their levels of anxiety in mathematics (Ramirez et al., 2013). After this, the students were prompted to make choices on one out of the possible five scenarios that were; ‘never,’ ‘sometimes,’ ‘always,’ ‘rarely,’ and ‘frequently’ for every thirty items that constituted the anxiety scale of the R-MANX. The responses were allocated to a score of one to five during the time of doing the calculation of the scores registered by each respondent surveyed. Low marks, according to Ramirez et al. (2013), depicted low instances of anxiety in mathematics while the highest marks indicated high incidences of anxiety in the subject. For the sake of the research study, the anxiety totals were categorized as ‘anxiety with low levels,’ ‘medium anxiety levels’ and ‘high anxiety levels.’ The classifications were done based on the mathematics percentile scores of anxiety. The students who registered 33% percentiles were categorized as the low categories of mathematics anxiety. For those who recorded scores of 33% and 67%, they were categorized as the medium lots, while those that had achievements of the upper 33% were classified as a higher mathematics anxiety category.

**3.4 Data Collection Procedures**

Intending to attain high reliability, Maloney and Beilock (2012) noted that some problematic statements underwent adjustments to enhance comprehension. The introduction of the survey was then done to grades one, two, three, and four students. From all the participants, there was a total of 1352 usable data acquired. The data was examined to explore the survey’s validity and the reliability plus any linkage of the attitudes towards mathematics and success among the students.

**3.5 Data Analysis**

The global relationship of the set variables constituting the R-MANX was evaluated by using the exploratory type of factor assessment (EFA). A confirmatory factor evaluation (CFE) was utilized to confirm the specific hypothesis associated with the format defined by the set variables constituting the R-MANX. The EFA’s performance was aided by SPSS version 22 (Ramirez et al., 2013). Principle component assessment (PCA) was applied to extract the factors that used the unique change of elements through the use of the Oblimin type of rotation.

CFA, through the use of the possible estimation, was carried out on the sample by using the ‘AMOS Version 22’ to evaluate the model fit. A good model fit is likely to show the relevant results through the use of a nonsignificant type of chi-square. However, other factors may affect the figure (Ramirez et al., 2013). Hence, many fit indices were utilized in measuring the model fit. The CFI values that range between 0.9 and 0.95 depict the reasonable type of fit, while those results falling between 0.95 and 1.0 illustrate a great kind of fit. *‘Standardized root-mean-square residual (SRMR)’* represents ‘absolute’ type of fit category of the index used mostly. For ‘*SRMR,*‘ the values below 0.05 would indicate the well-fitting type of model (Ramirez et al., 2013).

Meanwhile, ‘*Root Mean Square Error of Approximation, RMSEA’* refers to the most informative that assists in the determination of the model fit since it factors in the number of variables approximated for every model (Karimi & Venkatesan, 2009). The values of RMSEA falling 0.08 to 0.08 are reasonable fit, while those that are either less or equivalent to 0.05 depict an excellent fit. Meanwhile, the one way ANOVA tests were utilized in making explorations of the effect of the grade and achievement levels concerning the anxiety levels as well as the calculation of each comparison’s size (Karimi & Venkatesan, 2009). Similarly, two way ANOVA was utilized to compare the anxiety scores of the effect of levels of grade and the impact of gender on anxiety.

**3.6 Tests**

*3.6.1 Descriptive Statistics*

A section of the descriptive statistics type from ‘R-MANX’ is presented in the first Appendix. Mean registered ranges of 2.2 and 3.39. Each standard deviation (SD) recorded was beyond 1.0, thus revealing a broad spread of the item’s scores close to the mean. The data was examined for the sake of the multivariate form of normality, multicollinearity, and other forms of outliers before proceeding with the factor structure’s assessment from each response (Karimi & Venkatesan, 2009). The bivariate types of correlations, an aspect of tolerance, and the variance instance of inflation readings showed that it was not the bivariate nor the multivariate being present. Since the possible approximation gave an assumption of the normality of the variables, the data were evaluated about the univariate and multivariate forms of normalcy.

*3.6.2 Reliability Measures*

The reliability of the measurement of every item, each construct’s reliability and variance averages got were evaluated with the intent of assessing the measurement types of items’ validity convergent in connection to the elements (Karimi & Venkatesan, 2009). The significance of the composite type of reliability is the same as that of the case of the Cronbach’s Alpha with one the exception. It factors in the real factor loadings instead of giving the assumption of every item being the same to those weighted within the composite case of determination of load. Table 1 presents the reliability of the constructs, ranging from 0.86 to 0.95, that is beyond the minimum value that is set at 0.70. The table also gives the association between the constructs and the square root giving mean-variance obtained. The outcomes support the discriminant validity because every construct has a more significant AVE’s square root that is bigger than the internally based correlation of the constructs.

Table 1.

*Construct’s Reliability and the Extracted Variance’s Average*

*3.6.3 Convergent Validity*

Convergent measurement of validity gives item correlation through a construct for ensuring that variables correlate (Ozgen & Bindaka, 2011). Similarly, the aspect also provides the determination of the actual dimensions. Each measurement-reliability, the composite type of reliability of every construct plus mean-variance got underwent an evaluation to assess the convergent type of validity of the items of measurement in connection with the respective constructs (Ozgen & Bindaka, 2011). The significance of the composite kind of reliability is the same as that of the Cronbach Alpha, except that it considers the loadings instead of giving an assumption of every item on an equal basis based on the weighted as specified in the composite load description. For an item’s level of reliability as cited by Ozgen and Bindaka (2011), the least demand for the loading factor was 0.7. Appendix 2 shows the report of the prevalent factor forms of loadings that were beyond the desired point of cut off. Hence, the convergent type of validity satisfied an item’s level.

*3.6.4 Exploration of Quantitative Methods of Study*

The R-MANX’s 30 pieces were made to undergo principal component evaluation (PCA) by use of SPSS version 22, as presented in Appendix 2. The study assessed the data’s suitability through first evaluating the correlation matrix for the evidence of the coefficients beyond 0.3 (Li & Ma, 2010). The matrix of correlation of examination showed the availability of the several ratios of 0.3 and beyond, thus depicting the factor analysis being desirable. To assist in the appraisal of the aspect of the data’s factorability, two cases of quantitative measurements were computed by the use of SPSS. KMO’s value stood at 0.94, thus going above the desired figure of 0.6, and that of Bartlett’s Test of Sphericity was crucial in offering support to the correlation matrix’ factorability (Li & Ma, 2010). PCA was utilized in the extraction of the factors that abided with the oblique form of rotation, thus revealing the availability of a total of five components that have eigenvalues beyond 1 (7.73, 2.02, 1.88, 1.10 and 1.04). The total of five components explained the percentage equating to 45.89 registered from the variance.

*3.6.5 Mathematics’ Scores Representing Anxiety Scale Based on the Levels of Grades*

One –way cases of team’ evaluation of the variation were performed to explore the effect of grade on the anxiety levels on mathematics for students, a measurement made by the R-MANX (low, high moderate) (Li & Ma, 2010). The subjects were for the students in grades 1, 2, 3, and 4. There was in place a significant statistical variation at the value p <.05 levels within the scores of *R-MANX* for all levels of the four of grades; F at 3, 382 = 9.09, with p =.00. The size had an effect of 0.7, and it was determined by the use of the eta squared. The result was regarded as the moderate size effect, while 0.1 was considered as a small effect.

On the other hand, 0.6 was supposed to be a common effect, while 0.14 being categorized as a more prominent effect. Comparison by use of post-hoc with also the specific purpose of the *Tukey HSD* test revealed that grade 1’s ‘*mean score’* stood at; (M=81.88 with SD=17.99) had a significant variation from class 2 (M=84.41 with SD=18.67) and Grade 3(M=77.43 with SD=17.42). Grade 1 had a considerable difference from Grade 2 (M=82.88 with SD=19.36). Class 1 never had a significant variation from 3. Likewise, grade 2 never showed any significant differences from grade 3 (Ramirez et al., 2013). The average scores showed that grade 3 registered higher ratings of anxiety in comparison to the fear in other levels of the grade. The students who attained low marks in anxiety were the grade 1 students. The results obtained from *the one-way ANOVA test* and Tukey multiple comparisons are as presented in the below table 2.

Table 2.

*One-way ANOVA and Tukey Test Outcomes*

*3.6.6 Anxiety in Maths Scale Representing Scores Based on Success*

One way Ozgen performed ANOVA that links the group’s evaluation of variance and Bindaka (2011) to explore the effect of the degrees of performance (0–59%, 60–69%, 70–79%, 80–89%, 90–100%) on the levels of anxiety in maths as determined by the R-MANX. Assessment of pupils was performed to find out on their knowledge and skills in math. Consequently, they were classified into five categories or groups. The first class registered a score of 0-59%, revealing the lack of effectiveness while the second team recorded a score of 60-69%, which showed limited effectiveness.

The third group had a score of 70-79%, thus depicting a bit of efficiency while team 4 registered a score of 80-89%, thus showing off an essential form of effectiveness. The fifth group registered a score of 90 to 100% and, in this regard showing high rates of efficiency. There was in place, as identified by Karimi and Venkatesan (2009), a statistical variation at p <.05 levels in scores of R-MANX of all the five successful teams. The effect due to volume stood at 0.76, and it was determined by the use of the eta squared. The consequence, in this case, was taken into consideration as a medium-sized effect. The examples of comparisons by use of the Tukey HSD test showed the first group means the score (M) being 2.44 and the standard deviation (SD) being 0.71 and had a significant variation with the fifth group (M=1.67, SD=0.76).

On the other hand, the fourth team had M=1.93, SD-=0.84, and the third group registering M=2.00 and SD=0.76. Similarly, the second group had M=2.17 and SD=0.78, which in this case, had a significant variance with that of the third team. The second group never had significant differences from the first, third, and fourth groups (Ramirez et al., 2013). Likewise, the fourth group also never had significant variations from the third or the fifth team. A Tukey test was carried to determine the extent to which the changes were present. The result was that the mathematics anxiety among students with low degrees of success in the subject was indeed high compared to the students that registered success levels in the subject. The *one-way ANOVA test* and Turkey’s several tests on comparing outcomes are reported in table 2 above.

**3.7. Chapter Summary**

Geist (2010) noted that the study made attempts in the validation of the tools used in measuring the anxiety in maths on pupils. The Revised Mathematics Anxiety was administered to a total of 1352 students of the high school. The stress brought as a result of computation has been identified as one of the significant psychological components that have the capability of influencing the academic success of the students. Also, the descriptive type of statistics that constitute the R-MANX revealed that the instrument is endowed with reliability and validity when used in the measurement of the anxiety context among high school students (Ramirez et al., 2013). The factor evaluation showed that the tool has three constructs and reliabilities of every construct ranging from 0.86 to 0.95. The indices of reliability, in this case, are beyond the recognized degrees, and outcomes show the R-MANX being a rapid tool where the scholars may use much courage.

### Chapter 4: Discussion, Limitation, Conclusion, and Recommendation

**4.1 Discussion**

Anxiety towards mathematics, the same way to other forms of phobias, refers to the status that people handle daily (Ramirez et al., 2013). The first action in assisting the students to overcome the anxiety towards mathematics is the identification of the students that undergo higher incidences of fear towards the subject. From this juncture, Bekdemir (2010) advised that educators stand a chance in the selection of the desired informative strategies for reducing the anxiety towards mathematics or the changing of the existing classroom learning environment. Ramirez et al. (2013) explained that success relies on the method or the type of treatment being applied. Teachers who handle mathematics as a subject should consider spending time during class time in discussing the feelings that students have towards the issue. However, the application of the matter of mathematics reigns beyond the classroom level, and engaging in discussions about it stands a chance in assisting the students in understanding the subject much better.

The search in literature, as cited by Bekdemir (2010), revealed that there is no existing instrument to measure the anxiety brought by mathematics. Also, there is no single study that has so far been completed based on this sphere. The pioneering type of attempt, in this case, seeks to offer the chances or opportunities for other scholars in exploring different levels of grades and schools. Also, the findings obtained from this study have been timidly used to inform the management and the planners in the field of education on matters of the sector’s reformation. The results also intend to aid the designing of the new curriculum and in the adoption of related strategies of instructing overcoming the anxiety that is within the students.

**4.2 Conclusion**

The research impacted positively in society, with two significant contributions to the sector of mathematics education. First, the study found out that the R-MANX type of survey may be utilized in this context due to its reliability and validity. Secondly, the research established the association linking anxiety and the success registered by students in high school. The concern in mathematics represents the various possible factors that may impact on the achievement side of a student in the subject. Because success and knowledge of students during the period of education is always complicated and relies on several other factors, education is diverting its attention towards several aspects of the process of teaching and learning. The instances, in this case, are the noncognitive factors that include the beliefs, tolerance, goal orientation, and self-esteem, where some scholars attest to how the influence of such factors affects the success of the education of the students.

Often, persons that are possessed with higher levels of anxiety towards mathematics agree to do fewer courses, low grades in the classes they have registered. Likewise, they record little success in the subject in comparison to their respective counterparts with low instances of math anxiety. The outcomes got from this study reveal that the old trends are still going on with no changes taking place. To an educational officer, the opportunities towards success for the high school students towards mathematics are critical and imperative as well. The anxiety towards math is yet to become a topic of debate in learning institutions. Hence, it is the belief of this study that it will embark on discussions concerning the barriers towards mathematics anxiety and also assist the students in realizing their hopes. Indeed, this issue is of genuine concern. For instance, one parenting or a teenager who finds difficulty in handling mathematics may have little help in overcoming the subject. Consequently, schools need to undertake the exploration of the studies concerning this topic and also to enhance the awareness on teachers, parents, and classroom setting minds concerning handling the problem of mathematics anxiety among the youth of the present and the tomorrow as well.

Future studies need to consider the manner of exploring other forms of cognitive components that may impact on the outcomes in education based on this context altogether. This study has high hopes that the findings from it will help teachers and the management in designing the favor of learning where the students can appreciate the process of learning and also register good performances or results.

**4.3 Limitations**

According to Ramirez et al. (2013), this study has had its limitation towards the high school students only starting from grades 1, 2, 3, and 4. More research has the opportunity also to cover the primary schools and even the college-based students to research the topic that this study has dwelt on. Hence, it is likely to generate some interest in seeing the variation in the schools in town and villages and also gender variations concerning anxiety in maths towards students in high school. Results got from the research study show the statistical importance of the grade level variations. Grade three students registered the leading or the highest mean score of anxiety. In this case, Ramirez et al. (2013) established the scenario implies that anxiety levels experience increment with the progress of the students through the levels of grading. The same also has a possible association with the complex nature of the teaching curriculum, where more advanced concepts get introduced when one proceeds to a higher level of education. The outcome may also impact on the manner of teaching the subject of mathematics in lower levels of grades. Tutors are challenged to utilize the informative based ideas standing a chance in recognition of the students’ capabilities, especially when progressing in the content that needs to be gradual on the same note.

Ashcraft and Moore (2009) attested that the study established on the correlations among the anxiety levels in mathematics and the perceived success among the students. The students were challenged to show their stand concerning their mathematics achievement by assigning five scales starting from minimum to the maximum. The evaluation of results revealed that anxiety levels are indeed very high among the people who regard themselves as poor performers.

**4.4 Recommendations**

Following the findings got from the study, Shernoff et al. (2014) suggested the following for use in the upcoming studies:

- The scholars may utilize the survey’s outcomes in planning advanced studies touching on the anxiety towards mathematics success at high schools. Broader scientific investigations in high schools are missing in the present research studies.
- More investigations that start with the old elementary students require an assessment to understand the reality of the occurrence of mathematics anxiety.
- With the intent of understanding the practices in teaching, a study needs to be carried out based on the ancient and nontraditional modes of teaching methodologies and the impacts they have on the success of the student in mathematics and anxiety towards the subject as well.
- Students endowed with higher incidences of anxiety towards mathematics often register for a few courses in mathematics. Hence, there is a need for conducting a study that may oversee the relevancy of this move.
- A qualitative study, such as interviewing the teachers, counselors, head-teachers, parents, and the respondents, may result in a good understanding of the association between the anxiety towards mathematics and the success in the subject.

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