ENHANCING STUDENTS’ PSYCHOLOGICAL RESPONSES IN IMPROVING MATHEMATICS PERFORMANCE IN SECONDARY SCHOOLS IN SUBA NORTH SUB-COUNTY, KENYA
Abstract
Persistent underperformance in mathematics remains a significant challenge in Kenyan secondary schools, particularly in rural settings where learners continue to record low achievement despite various educational interventions. Although previous studies have largely focused on instructional strategies, curriculum implementation, and school-based structural factors, limited attention has been given to psychological determinants of learners’ achievement in mathematics. In consideration of this gap, there was a need to focus a study on psychological determinants in enhancing performance in mathematics. The objective of the study was to determine the influence of students’ psychological responses on performance in mathematics in secondary schools in Suba North Sub-County, Homa Bay County, Kenya. The study was anchored on Victor Vroom’s Expectancy Theory, which explains that individuals’ performance is influenced by their beliefs about their ability to succeed and the expected outcomes of their efforts. The theory posits that learners are more likely to perform better when they believe in their capabilities and expect positive outcomes from their academic effort. A descriptive survey design within a mixed methods approach was adopted. The target population comprised 2,285 respondents from 28 public secondary schools, including 2,204 Form Four students, 53 mathematics teachers, and 28 principals. Using Taro Yamane’s formula (e = 0.05), a sample of 339 students was selected, while teachers were purposively sampled and principals were included through census sampling, giving a total sample size of 420 respondents. Data were collected using questionnaires and interview guides. Instrument validity was established through expert review, while reliability was tested using the test–retest method. Data analysis was conducted using both descriptive and inferential statistics, including Pearson correlation and t-test, while qualitative data were analyzed thematically. Ethical considerations such as anonymity and confidentiality were observed, where respondents’ identities were replaced with codes. The findings revealed that there was no statistically significant difference between students and teachers of mathematics regarding psychological responses influencing performance (p > .05 across all constructs). This indicated a general consensus that psychological factors such as anxiety, fear, frustration, negative perception, and lack of confidence influence mathematics performance. Furthermore, the results established a statistically significant strong positive relationship between students’ psychological responses and performance in mathematics (r = .614, p = .000). This implies that improved psychological responses are associated with better performance in mathematics, while negative psychological states lead to poor performance. Based on these findings, it was concluded that students’ psychological responses significantly influence performance in mathematics in secondary schools. The study established that learners who demonstrate positive psychological dispositions such as confidence, motivation, and emotional stability tend to perform better in mathematics, whereas those experiencing anxiety, fear, and emotional distress tend to perform poorly. The study therefore recommended that mathematics teachers should adopt supportive and learner-centered instructional strategies that reduce anxiety, fear, emotional distress, and negative attitudes toward mathematics in order to enhance students’ performance in the subject.
Keywords: Self-efficacy, Psychological responses, Mathematics performance, Academic achievement.
References
Abusalih, N., & Hussein, S. (2022). Examined the importance of psychological factors in the mathematics education process and how they influence students’ academic achievement. Multi-Knowledge Electronic Comprehensive Journal for Education and Science Publication, Issue 57.
Ahmed, I., & Ishtiaq, S. (2021). Discussed the significance of reliability and validity in medical research methodologies. Methods, 12(1), 2401–2406.
Andersson, A., Foyn, T., Simensen, A., & Wagner, D. (2023). Explored themes of frustration in mathematics learning and their implications for mathematics teacher education during periods of change. Education Sciences, 13, 816.
Chan, L. L., & Idris, N. (2017). Investigated the validity and reliability of research instruments using exploratory factor analysis and Cronbach’s alpha. International Journal of Academic Research in Business and Social Sciences, 7(10), 400–410.
Creswell, J. W., Klassen, A. C., Plano Clark, V. L., & Smith, K. C. (2011). Provided guidelines and best practices for conducting mixed methods research in health sciences. Bethesda, Maryland: National Institutes of Health, 541–545.
Daches Cohen, L., Korem, N., & Rubinsten, O. (2021). Found that mathematics anxiety is associated with mathematical difficulties and is influenced by emotional regulation and anxiety predisposition. Brain Sciences, 11(12), 1609.
Demedts, F., Reynvoet, B., Sasanguie, D., & Depaepe, F. (2022). Analyzed the relationship between mathematics anxiety and students’ performance in mathematics. Frontiers in Psychology, 13, 979113.
Essuman, S. A., Nyarko, J., & Frimpong, K. (2021). Studied the effects of mathematics anxiety on the academic performance of junior high school students in Ghana. International Journal of Social Sciences and Humanities Invention, 8(9), 6562–6569.
Ginting, S. S. B. (2024). Discussed the role of adversity quotient in enhancing successful mathematics learning. JPP (Jurnal Pendidikan dan Pembelajaran), 31(2), 91–104.
Heo, H., Bonk, C. J., & Doo, M. Y. (2022). Examined how depression, self-efficacy, and resource management affect learning engagement in blended learning during the COVID-19 period. The Internet and Higher Education, 54, 100856.
Holm, M. E., Hannula, M. S., & Björn, P. M. (2017). Investigated mathematics-related emotions among Finnish adolescents across varying performance levels. Educational Psychology, 37(2), 205–218.
Kamau, H. N. (2022). Investigated selected teaching strategies and their influence on students’ mathematics performance in public secondary schools in Bahati Subcounty, Nakuru County, Kenya. The Catholic University of Eastern Africa.
Lee, X., Griffin, A., Ragavan, M. I., & Patel, M. (2024). Explored the relationship between adolescent mental health and academic performance and suggested evidence-based support approaches in educational settings. Pediatric Research, 95(6), 1395–1397.
Luenendonk, M. (2019). Provided definitions, templates, and practical tips for developing interview schedules. Shutterstock.com.
M’kiambi, K. J. (2013). Evaluated the contribution of the SMASSE in-service project to students’ mathematics performance in KCSE examinations in Nkuene Division, Meru County, Kenya.
Mugenda, O., & Mugenda, A. (2019). Presented comprehensive approaches to quantitative, qualitative, and mixed methods research. Nairobi, Kenya: Centre for Innovative Leadership and Governance (CLIG).
Munyi, C. M., & Orodho, J. A. (2015). Discussed techniques for writing research proposals and reports in education and social sciences. Nairobi: Kanezja Publishers.
Mutegi, C. M., Gitonga, C. M., & Rugano, P. (2021). Examined the relationship between mathematics anxiety, attitude, and performance among secondary school students in Kenya. Educational Research and Reviews, 16(6), 226–235.
Odegi, O. E., Juma, R. A., & Okello, L. M. (2021). Investigated teachers’ competence in the use of science instructional resources among pre-primary school teachers in Ndhiwa Sub-County, Homa Bay County, Kenya. International Journal of Novel Research in Education and Learning, 8(4), 32–37.
Orodho, J. A. (2008). Explained techniques for writing research proposals and reports in educational and social sciences. Maseno, Kenya: Kanezja HP Enterprises.
Rahman, M. M., Tabash, M. I., Salamzadeh, A., Abduli, S., & Rahaman, M. S. (2022). Discussed probability sampling techniques for quantitative social science research with conceptual guidelines and examples. SEEU Review, 17(1), 42–51.
Riegel, K. (2021). Conducted a systematic review on frustration in mathematical problem-solving. STEM Education, 1(3), 157–169.
Schoenherr, J., Schukajlow, S., & Pekrun, R. (2025). Reviewed and analyzed emotions in mathematics learning through a systematic review and meta-analysis. ZDM–Mathematics Education, 57(4), 603–620.
Shirima, F. (2020). Introduced research methodology concepts in the context of university student unrest studies. International Knowledge Sharing.
