No AI Generated Content
Introduction: Statistical Anxiety and Academic Performance of Undergraduate Australian Students
Get Free Samples Written by our Top-Notch Subject Expert Writers known for providing the Best Assignment Help Services in Australia
Background
Statistics anxiety is referred to the change of an individual into an anxious entity after being exposed to statistics. Recent research has declared that nearly 80% of college students experience anxiety when they are made to study statistics. The figure below describes the statistics anxiety trait, and it has been found that the majority become anxious when they are made to calculate statistical results. Symptoms might include immense fear of facing numbers, sweating, palpitation, over-emphasising a single calculation and developing the idea that personal worth would get degraded with bad grades. Considering that the factors triggering anxiety are already numerous, it would be considered necessary that optimising the situation is considered a priority. The study focuses on the impact of statistics anxiety on the academic performance of undergraduate students.
Figure 1: Traits of statistics anxiety
(Source: Eric, 2022)
Aim and Hypothesis
The study aims to find the effect of statistical anxiety on the academic performance of undergraduates. It has been hypothesised that the statistical anxiety scale might help in measuring this relation, while the null hypothesis has been on the assumption that the statistical scale cannot help in the measurement.
Rationale
Anxiety is already a mental health issue that has been a concern of health professionals for ages. Adding to that, statistical anxiety might be considered an issue that might affect the educational development of individuals. The reason why statistics anxiety is an issue is that it not only affects the mental peace of an individual but also makes them develop a fear of the subject for a lifetime. As mentioned by Onwuegbuzie & Wilson, (2003), an individual having statistics anxiety develops a fear of numbers with the change of time and hence gets stressed whenever they are exposed to calculations. Considering that numbers are an integral part of our life, it might be quite difficult to avoid them, and this fact justifies why statistics anxiety might be a potential issue. However, unlike other forms of anxiety, statistical anxiety fails to get deserving medical attention due to a lack of knowledge and awareness in people. This is the current issue that has prevented the path of developing strategies to reduce the symptoms (Apadivisions, 2018). The study sheds light on statistical anxiety along with the factors that probably influence it.
Key terms
Statistics anxiety: The condition of developing anxiety when exposed to statistical calculations.
Undergraduate students: Students who are currently studying in college and yet to get their graduate degree.
Academic performance: The extent to which a student has succeeded in achieving their educational goals.
Statistical scale: A set of various statistical methods for analysing survey data.
Literature review
Impact of gender on building confidence in statistics
Anxiety is one of the issues that are likely to affect any individual irrespective of gender or age. However, as opined by Bui & Alfaro, (2011), women are twice as likely to develop signs of anxiety as males, and various social and biological factors might be the reason behind this. The differences in hormonal fluctuations and brain chemistry might be the main drivers of anxiety in women. However, as said by Faber & Drexler, (2019), statistic anxiety is a completely different phenomenon that develops mostly due to negative experiences in the classroom. The teachers, parents, friends and society might be responsible for triggering fear of statistics in a student. Besides, a grip on the subject is necessary for building confidence, which depends on the mental ability of the student. Hence, the assumption that one gender is more likely to develop anxiety on statistics is debatable.
Influence of age on anxiety/confidence in studying statistics
Anxiety is more common with the increase in age due to biological changes and experiences of traumatic events. As mentioned by Forster & Maur, (2015), statistical anxiety is more common in students since they are exposed to numbers more frequently. Hence, changes in anxiety symptoms over the course of three years of college life would be negligible. However, as said by Bui & Alfaro, (2011), once the tendency to develop statistical anxiety is developed in a student, they might fail to get rid of the fear in future. Hence, age might be considered a crucial factor impacting anxiety build-up.
Changes in confidence level and anxiety with experience in statistics
Students lacking the confidence to deal with numbers are the ones who are more susceptible to developing statistical anxiety. As said by Valle et al. (2021), the lack of confidence in a student might be both due to individual nature and due to the lack of support from teachers and parents. The inability to face huge mathematical data is the result of a pre-developed notion of not being able to solve mathematical problems. However, as opined by Faber & Drexler, (2019), the notion might change with repeated exposure to statistical data and regular practice. The experiences gained in this constant exposure might help in mitigating statistical anxiety to some extent.
Research gap and significance of the study
The existing literature has focussed on the factors that trigger statistical anxiety effectively. There has also been enough mention of the individual traits responsible for developing this condition (Onwuegbuzie & Wilson, 2003). However, there has been limited information on the ways that could be applied to minimising the risk. Also, the risks associated with further deterioration of the conditions have not been highlighted. The study has highlighted these factors, and it might be assumed that the findings would provide an idea to health professionals about the significance of the issue. Also, it is expected that the strategies provided against statistical anxiety might help reduce the number of cases to some extent.
Methods
Participants
The students who have been chosen for the study fall into the age group 21-42 years of age. The participants have been recruited during face-to-face tutorials on their statistics subject at one "Australian regional university". Participation has been voluntary, and no penalty or negative consequences have been imposed for students who did not want to take part. Ethics approval has been obtained from the "Human Research Ethics Committee (HREC)" of the University before proceeding with the study.
Materials
The SPSS software had been used to analyse the data that had been collected from the survey. As mentioned by Faber & Drexler, (2019), SPSS is one of the most effective tools that aid in statistical analysis. The demographic factors have been considered for the analysis are- age and sex.
Procedure
The survey has taken nearly 10 minutes to complete. The scales that had been considered to measure the” Confidence in Coping with Statistics" and"Fear of Statistics" have been designed by the lecturer specifically for this study. However, the psychometric properties of the used scales could not be detected. 20 survey items have been considered for measuring the "Fear of Statistics". The survey items have been responded to by ranging the scale between 1 and 3. Followed by that, the participant responses had been summed, forming a total score for each participant. The total score obtained fell in the range of 20 to 60. The higher scores indicated higher fear or anxiety about studying statistics.
Similarly, 10 survey items had been used to measure "Confidence in Coping with Statistics", and the items had been responded to by using a scale ranging between 1 and 4. The responses gathered from the participants have then been summed up to obtain the total score for each participant. The total scores ranged between 10 and 40, and the higher scores indicated high confidence in coping with statistics. The survey had been administered twice in the period of a 12-week semester. The first one has been conducted in week 1 of their classes, followed by the second one in the final week. Students had completed the survey in their computer labs present on the campus during their tutorials.
Result
Australian university in the past years has undergone a notable transformation for the fidelity minority. As opined by Verlie (2022), the socio-culture spectrum has increased the broader aspects of access to tertiary qualification. Higher Education Support Act (2003) has introduced a course of study that is under higher education for pre-university courses. It is actually designated for mature-age students for mathematical and technological students. The statistics student has been evident in finding this difficult in meeting the goal that raised the Australian university student to decrease their ability in statistics. The result obtained reveals in T test paired sample that in pair 1 (fear of stat time 1 and fear of stats time 2) with pair 2 (confidence time 1 and confidence time 2). The data reveal 38.64 in fear of stat time 1 and 33.96 in fear of stats time 2 along with pair mean of 20.92 in confidence time 1 and 26.68 in confidence time 2. The standard deviation resulted out to be 7.389 in fear of stat time 1, 6.90 in fear of stats time 2, 4.93 in confidence time 1 and 5.77 in confidence time 2.
Undergraduate students enable to take STEM courses and related courses that added the learning experience among the large demographic to motivate, education and aspiration. According to Kranzler & Anthony (2022), student confidence levels have been found to be decreased due to the incapability of the individual suffering from the lack of self-efficacy, developing depression, anxiety, trauma and changes in attitude and belief. For example, in the investigation on the Australian undergraduate student, adult learners commencing allow their education to draft negative attitude raised their level of anxiety with lowers self-efficacy. The correlation of the paired sample is 0.692 in pair 1 and 0.611 in pair 2. The pair sample test performed revealed in pair 1 4.68 is the mean whereas -5.76 in pair 2. The standard deviation is 5.6 in pair 1 with a 0.796 standard error and 4.78 in pair 2 with a 0.676 standard error. The difference in the 95% confidence interval in pair 1 is 3.08 as the lower difference and -7.11 as the upper difference. Pair 2 has a 6.26 lower difference and -4.4 in the upper level. With a T significance of 5.87 in pair 1 and -8.5 in pair 2 in 2-tailed.
Discussion
Students studying at university have been found to develop anxiety and other psychological issue. This has an adverse impact on academic performance. As referred by Callow et al. (2021), statistical anxiety calling allow to development of analysis on the nature of anxiety, its intensity and the prevalence of anxiety among undergraduate students. College students develop a lack of confidence, and self-efficacy, therefore, statistical scaling allows measuring academic performance, simultaneously in the psychological condition, students unable to give their best output. Therefore, the aim of this study is to determine academic performance using the statistical anxiety scaling to analyse the psychological distribution through the analysis of the students prior to the experience with the student having no experience with statistics.
Anxiety intensity depends upon ethnicity, gender, and environmental influence. a student suffering from a mental health illness has an effective and perceived application for the critical anxiety evaluation. As stated by Giummarra et al. (2021), analysis of the student's characteristics and terminating the performance level through scaling from the statistical tool has influenced the education hampers. Social interaction exerted pressure on the university student which leads to an increase the mental health illness among the students. The results reflect that the standard deviation resulted out to be 7.389 in fear of stat time 1, 6.90 in fear of stats time 2, 4.93 in confidence time 1 and 5.77 in confidence time 2. Therefore from this analysis, it can be reflected that psychological issues have drafted a negative effect on the student's psychology.
Higher education level has been greatly hampered disrupt learning and teaching due to covid-19. As opined by Dodd et al. (2021), to determine the level of well-being of university students, a cross-sectional study has been done using 787 students in an Australian University. It is reported that psychological well-being has been reported by 34.7%, 33.8% in low well-being and 31.5% in low well-being. Therefore, it is analysed that has increased the mental exhaustion that highly targeted female students with existing disparities. Emotional regulation influences the individual well-being that is linked with psychopathology. Higher education level has been greatly hampered disrupt learning and teaching due to covid-19. As opined by Dodd et al. (2021), to determine the level of well-being of university students, a cross-sectional study has been done using 787 students in an Australian University. It is reported that psychological well-being has been reported by 34.7%, 33.8% in low well-being and 31.5% in low well-being. Therefore, it is analysed that has increased the mental exhaustion that highly targeted female students with existing disparities. The outcome reveals that the correlation of the paired sample is 0.692 in pair 1 and 0.611 in pair 2. The pair sample test performed revealed in pair 1 4.68 is the mean whereas -5.76 in pair 2. The standard deviation is 5.6 in pair 1 with a 0.796 standard error and 4.78 in pair 2 with a 0.676 standard error. The difference in the 95% confidence interval in pair 1 is 3.08 as the lower difference and -7.11 as the upper difference. Pair 2 has a 6.26 lower difference and -4.4 in the upper level. With a T significance of 5.87 in pair 1 and -8.5 in pair 2 in 2-tailed. Therefore from this, it is analysed that the t-test statistic reveals significant positive of an undergraduate student experiencing anxiety in bothering the pairs. However, the anxiety that has been observed is higher in the fear of stat time 1 in confidence time 1. Therefore, from this, it is analysed that this study has met hypothesis 1 which reveals that the statistics analysis scale measures the academic performance of undergraduate students.
Reflection
Australian student universities have been looking into the negatively associated dimension of stress, anxiety and dispersion. The results from the analysis reveal that self-compassion has a negative influence on stress which addresses emotional distress that sympathised with the psychopathology in the context of external stress. Therefore I found these statistical scaling tools to be effective in dealing with the analysis of the student characteristics on academic performance. Mental health illness has been significantly analysed among the student studying in the university. Paired sample t-test is the dependent t-test which is primarily used to analyse the mean difference of the paired samples from the two sets is zero. The T-test is a statistical procedure which enables the analysis of the two paired difference means, standard deviation and the difference at its 95% confidence interval and significance. As mentioned by Stormon et al. (2019), this test has been performed in this study to measure the anxiety among the students studying at the university with the statistical study. Linking with the objective, scaling the anxiety statistically to measure the performance of the Australian student studying in university through determine percentage of the sex difference having anxiety. I found this analysis of the traditional versus peer instruction along with the student having experience with student statistics.
Reference list
Journals
Provided
Bui, N.H., & Alfaro, M. A. (2011). Statistics anxiety and science attitudes: Age, gender and ethnicity factors. College Student Journal, 45 (3), 573 – 585.
Forster, M., & Maur, A. (2015). Statistics anxiety and self-concept of beginning students in the social sciences – A matter of gender and socio-cultural background. Zeitschrift für Hochschulentwicklung, 10(4), 67 – 90.
Onwuegbuzie, A.J., & Wilson, V.A. (2003). Statistics anxiety: Nature, etiology, antecedents, effects, and treatments – a comprehensive review of the literature. Teaching in Higher Education, 8 (2), 195 – 209. doi: 10.1080/1356251032000052447
Others
Callow, T. J., Moffitt, R. L., & Neumann, D. L. (2021). External shame and its association with depression and anxiety: The moderating role of self-compassion. Australian Psychologist, 56(1), 70-80. https://doi.org/10.1080/00050067.2021.1890984
Dodd, R. H., Dadaczynski, K., Okan, O., McCaffery, K. J., & Pickles, K. (2021). Psychological wellbeing and academic experience of university students in Australia during COVID-19. International Journal of Environmental Research and Public Health, 18(3), 866.
Faber, G., & Drexler, H. (2019). Predicting Education Science Students' Statistics Anxiety: The Role of Prior Experiences within a Framework of Domain-Specific Motivation Constructs. Higher Learning Research Communications, 9(1), n1. http://dx.doi.org/10.18870/hlrc.v9i1.435
Giummarra, M.J., Simpson, P. and Gabbe, B.J., 2020. Pain, anxiety, and depression in the first two years following transport-related major trauma: a population-based, prospective registry cohort study. Pain medicine, 21(2), pp.291-307. https://doi.org/10.1093/pm/pnz209
Lisciandro, J. G., Jones, A., & Geerlings, P. (2018). Enabling learners starts with knowing them: Student attitudes, aspiration and anxiety towards science and maths learning in an Australian pre-university enabling program. Australian Journal of Adult Learning, 58(1), 13-40.
Stormon, N., Ford, P. J., Kisely, S., Bartle, E., & Eley, D. S. (2019). Depression, anxiety and stress in a cohort of Australian dentistry students. European Journal of Dental Education, 23(4), 507-514. https://doi.org/10.1111/eje.12459
Valle, N., Antonenko, P., Valle, D., Dawson, K., Huggins-Manley, A. C., & Baiser, B. (2021). The influence of task-value scaffolding in a predictive learning analytics dashboard on learners' statistics anxiety, motivation, and performance. Computers & Education, 173, 104288. https://doi.org/10.1016/j.compedu.2021.104288
Books
Kranzler, J. H., & Anthony, C. J. (2022). Statistics for the terrified. Rowman & Littlefield. https://books.google.com/books?hl=en&lr=&id=I6h5EAAAQBAJ&oi=fnd&pg=PP1&dq=anxious+%2Bstudying+statistics+%2B++books&ots=ph7gxFnw7R&sig=4Pr6e5nLjs99wnt2hbYxXhrjLOE
Verlie, B. (2022). Learning to live with climate change: From anxiety to transformation (p. 140). Taylor & Francis. https://library.oapen.org/bitstream/handle/20.500.12657/49477/9781000438291.pdf?sequence=1
Websites
Apadivisions. (2018). Overcoming the fear of statistics: Integrating statistics within a research methods course. Retrieved on 30 December 2022. Retrieved from: https://www.apadivisions.org/division-20/publications/newsletters/adult-development/2017/10/statistics-research-methods
Cleveland. (2022). Arithmophobia (Fear of Numbers). Retrieved on 30 December 2022. Retrieved from: https://my.clevelandclinic.org/health/diseases/22545-arithmophobia-fear-of-numbers
Eric. (2022). That Old Devil Called ‘Statistics’: Statistics Anxiety in University Students and Related Factors. Retrieved on 30 December 2022. Retrieved from: https://files.eric.ed.gov/fulltext/EJ1336281.pdf [Accessed]
Math. (2020). Math Anxiety is Real; How Teachers Can Help Calm the Nerves. Retrieved on 30 December 2022. Retrieved from: https://mathforall.edc.org/math-anxiety/
Appendices
Appendix: Paired sample T-test
