Predictors of Academic Outcomes amongst Secondary Students in Benin City, Nigeria

Predictors of Academic Outcomes amongst Secondary Students in Benin City, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Predictors of Academic Outcomes amongst Secondary Students in Benin City, Nigeria Paul Ehiabhi Ikhurionan, Imuwahen Mbarie, Abieyuwa Peace Omoregie This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9172555/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background: Adolescent academic performance is shaped by multiple factors, including cognitive abilities, and socio-educational context. Executive functions (EFs) are essential for learning, yet their role in academic outcomes among Nigerian adolescents is poorly studied. This study assessed the influence of executive functions, reading habits, parental education, and school type on Mathematics and English performance among secondary school adolescents in Benin City, Nigeria. Method: A descriptive cross-sectional correlational study was conducted among 550 Senior Secondary School 1 students. Sociodemographic data and daily reading hours were collected using structured questionnaires. Executive functions were assessed with TEXI. Academic performance was measured using end-of-term Mathematics and English scores. Data were analyzed using SPSS version 26.0, employing descriptive statistics, Pearson correlations, and independent t-tests, with significance set at p < 0.05. Results: Participants had a mean age of 15.39 ± 1.29 years; 46.4% were male. Public school students comprised 54.2%.. School type (r = 0.166, p < 0.05), parental education and reading hours (Mathematics: r = 0.118; English: r = 0.108, p < 0.05) significantly correlated with performance, whereas EF subscales did not. Conclusion: Executive functions did not predict academic outcomes. School type and reading habits were key determinants in adolescent achievement. Executive Function Academic Performance Adolescents Introduction Academic performance plays a dual role as a key indicator and critical outcome of adolescent development, with far-reaching implications for educational attainment, career trajectories, and socioeconomic mobility (1,2). Beyond creating a sense of fulfilment for the adolescent, it also serves as a key determinant of life opportunities in adulthood. The adolescent stage is however, a period of intense physical, emotional, and cognitive development where the foundations for lifelong learning are consolidated. (3). During this phase, students take on new academic tasks and are constantly required to meet increasing academic demands while adapting to diverse educational environments. Academic achievement during this developmental stage is thus shaped by a multi-complex interplay of cognitive, behavioral, and socio-environmental predictors (4). The interplay of the cognitive and behavioural factors is explained by Executive functions (EF), which is typically assessed by testing working memory, (as the ability to retain and manipulate information for short periods} and inhibition (the ability to suppress impulsive responses). (5–7) In adolescents, EF aid in concentration, sorting out of relevant information when faced with a myriad of information, avoiding distractions and remembering instructions. EF controls thought processes and actions towards a set goal, and are activated from childhood through to adulthood with a decline at old age. (8) Epidemiological data suggest that children with poor EF experience difficulty in language skills, reading and mathematical abilities (9). On a longitudinal scale, weak EF has been identified as an indicator of academic difficulties and unfulfilled academic goals while a well-developed EF increases the likelihood of success and satisfaction in life. (7,9). A bulk of growing evidence reports a strong association between EFs and academic performance. (7,9,10) While cognitive abilities such as working memory and inhibitory control are essential for learning they operate within broader socio-educational contexts shaped by variables such as reading habits, parental education, and school type (11–13). Blair and Raver found that socioeconomic status and school quality significantly predicted literacy and numeracy outcomes, but their study primarily focused on early childhood, thereby limiting its relevance to adolescents. (14) In Nigeria, Angwaomaodoko documented pronounced disparities in academic performance between public and private school students, largely attributable to differences in resource allocation. (15) However, existing research have often been limited in scope by focusing exclusively on cognitive abilities or examining a single subject area, overlooking and under-exploring the combined influence of cognitive, behavioral, and socio-demographic factors on multiple core subjects among the adolescent populations. The absence of such integrated studies in Nigeria is particularly concerning given the socio-economic disparities and the large proportion of adolescents in the national population. (15,16) Understanding these dynamics thus becomes imperative in designing school-based interventions which improve the academic life of the adolescents in resource-variable educational systems. This study seeks to generate multi-level, evidence-based interventions on the outcomes of combined influence of working memory, inhibition, reading hours, school type, and parental education on end-of-term Mathematics and English scores among early and mid-adolescents in Benin City, Nigeria. The inclusion of students from both public and private schools, provides a broader environmental and socio-economic spectrum, revealing the variations in educational context and its potential effect on performance, with potential applicability in similar low- and middle-income settings. Method Study Design and Study Setting We conducted a descriptive cross-sectional study amongst secondary school students attending three senior schools in Benin City, Edo State, Nigeria. Benin City, which is an urban metropolis with a diversity of educational institutions, operates the national 6-3-3-4 academic structure comprising of 6 years in primary school, 3 years in junior secondary school, 3 years in senior secondary school and 4 years in a tertiary institution. The State’s Ministry of Education oversees the registering and monitoring all public and private owned educational institutions, through different boards. Though the private and public institutions operate the same syllabus, there are often variations in the school practice, methods of teaching and school environment and school rules. The study thus included two public and one privately owned secondary school institutions purposively selected to represent to provide a broader scope. Recruitment and Sampling of Participants One week before the study an informative letter and the informed consent form was sent to the students’ parents or legal guardian in order to inform them of the objectives and procedure of the study. We recruited participants 550 participants between the ages of between 13 and 16 years from Senior Secondary School 1 (SSS1). Only students who had a regular school attendance greater than 90% of total school days in the previous term who returned signed informed consent from their parents/ guardians and had no diagnosed neurological or learning disabilities were eligible to be recruited. Exclusion criteria included; having physical impairment that limited the ability to fill the data collection instruments and having a known neurologic or psychological diagnosis significant enough to limit participation. We therefore recruited only healthy adolescents’ who had normal physical, intellectual, auditory, and visual conditions. Students who were absent on the days of data collection were excluded from the study. Data Collection Data were collected over an eight-week period, with the aid of a standardized self-administered questionnaire and academic records of selected participants. The study questionnaires were administered during school hours in group settings under the supervision of trained research assistants. The research assistants were available throughout the duration of the data collection to provide guidance to students who needed assistance in understanding the questionnaire. End of term scores were obtained from the official examination record of each school. Instruments We utilized a structured questionnaire to assess socio-demographic characteristics (such as age, gender, school type (public vs. private), parental education level and reading habits (number of hours spent reading or studying outside of school per day). To assess for EFs, we utilized the Teenage Executive Function Inventory (TEXI), This standardized instrument assessed working memory and Inhibition on two different sub-scales. Each sub-scale consisted of self-report items rated on a Likert scale, with higher scores indicating poorer EF functioning. For the purpose of this study, we adopted the generalized definitions of working memory (defined as the ability to retain and manipulate information for short periods) and Inhibition (refers to the ability to suppress impulsive responses). We assessed academic performance as students’ percentage scores in Mathematics and English from the most recently completed academic term, obtained from the official examination record of each school. Data Analysis Data were analyzed using Statistical Package for Social Sciences (IBM SPSS Statistics for windows, Version 26.0. Armonk, NY: IBM Corp). Continuous data were summarized as means and standard deviations, while categorical data were presented as frequencies and percentages. Independent samples t-tests was used to compare academic scores across gender and school type. Pearson correlation coefficients were used to assess the relationship between study variables. Statistical significance was set at p < 0.05. Results 1. Descriptive Statistics The mean age of the study population was 15.39 (SD = 1.29) years. The study had a population of 255 (46.4%) males and 295 (53.6%) females with a male: female ratio of 0.86:1. Public school students made up 54.2% of the sample, while 45.8% were enrolled in private schools. Table 1 presents the demographic characteristics of the 550 participants. Group Comparisons Independent t-tests revealed that males and female students had comparable performance in both Mathematics and English end of term scores. Private school students scored significantly higher in Mathematics (M = 54.4%, SD = 14.2%) compared to public school students (M = 49.4%, SD = 15.3%); p < 0.001. However, both public (m − 53.80, SD – 16.15%) and private schools (M = 52.46%, SD = 141.74%) had comparable English scores, p = 0.276 (Table 2 ). Table 2 Group comparison of academic performance based on gender and school type Gender Mathematics score English scores Mean (SD) t-test p Mean (SD) t-test p Male 52.67 (15.20) 1.420 0.156 52.20 (16.15) -1496 0.135 Private 50.85 (14.74) 54.03 (11.74) School Type Public 49.41 (15.27) -3.957 < 0.001 53.80 (16.15) 1.120 0.263 Private 54.38 (14.17) 52.46 (11.74) Correlation Analysis Pearson correlation coefficients showed weak positive correlations between the type of school (r = 0.166, p < 0.05), the number of hours spent reading (r = 0.118, p < 0.05), Father’s education (r = 0.088, p = 0.039) and Mother’s education (r = 0.150, p < 0.05) with Mathematics scores. Only the number of hours spent reading (r = 0.108, p < 0.05) was positively correlated with English scores. However, the EF subscale scores did not show significant correlation. The Pearson’s correlation analysis is shown in Table 3 . Table 3 Correlation Matrix (Pearson's r) Variables Maths score English Score Working Memory Score Inhibition Score Gender Age Type of School Reading hours Father’s Education Level Mother’s education level Maths score 1 0.630* -0.009 0.025 -0.061 0.023 0.166* 0.118* -0.088* 0.150* English Score 0.630* 1 -0.032 0.044 0.064 -0.011 -0.047 0.108* 0.040 0.060 Working Memory Score -0.009 -0.032 1 -0.036 -0.051 0.161 0.027 0.024 -0.075 0.003 Inhibition Score 0.025 0.044 -0.036 1 0.036 0.040 -0.081 -0.061 0.031 0.011 Gender -0.061 0.064 -0.051 0.036 1 -0.054 -0.060 0.118* -0.007 0.037 Age 0.023 -0.011 0.161 0.040 -0.054 1 -0.276* -0.056 -0.204* -0.180* Type of School 0.166* -0.047 0.027 -0.081 -0.060 -0.276* 1 0.216* -0.357* 0.446* Reading hours 0.118* 0.018* 0.024 -0.061 0.118* -0.056 0.216* 1 -0.200* 0.255* Father’s Education Level -0.088* 0.040 -0.075 0.031 -0.007 -0.204* -0.357* -0.200* 1 -0.574* Mother’s education level 0.150* 0.060 0.003 0.011 0.037 -0.180* 0.446* 0.255* 0.574* 1 * Significant at p < 0.05 Discussion This study examined the predictors of academic performance in Mathematics and English among adolescents in three secondary schools in Benin City, Nigeria. We found that reading hours per day, type of school and parental education were strongly predictive of academic performance in Mathematics while English scores were predicted by the number of reading hours only. The study found no association between age, gender, working memory scores and inhibition scores and academic outcomes. Our study reported that students who studied regularly were more likely to have better academic performance in mathematics and English. Thus, indicating that reading habits were a direct determinant of academic outcomes. These findings were in close similarity with other findings which reported that academic outcomes were improved by good study habits outside the school premises. (17) Conversely, these findings also indicate that poor study habits were a major determinant of poor academic outcomes. Poor study habits such as cramming, screen distractions have been said to negatively affect academic outcomes. Investigators report that increased screen time worsens EF and academic outcomes as high screen time provides a wide range of cognitive consequences (18). While poor study habits like cramming may offer temporary solutions, its long-term comprehension consequences, anxiety and mental stress outweigh the short-term success.(19) Its distinction from proper studying hovers around consistent, self-directed reading which promotes deep processing and retention, unlike last-minute mass practice (cramming) which undermines performance, especially when it reduces sleep. Regular, purposeful reading rather than sleep-deprived cramming, positively impacts academic performance. These findings agree with the well-established spacing effect of improved learning through distributed study (20,21) and emphasize the importance of adopting well-structured routines for children and adolescents based on academic goals to improve academic performance. The spacing effect explains that “long term memory is enhanced when events are spaced over a period of time, rather than compounded in very close successions” Proper scheduling and constant abiding by reading timetables/schedules promote stronger memory recall and improved academic achievements. Also, we also found school type to be a strong predictor of academic performance, with private schools outperforming public ones. Adolescents in private schools were reported to have a higher end-of term scores in mathematics and English compared to their peers in public schools. These findings align with previous Nigerian studies on the association between school type and academic performance. A comparative analysis in Lagos State showed that private school students performed better in Economics than their public-school counterparts, often credited to superior infrastructure and curriculum implementation [22]. Another study noted that parents perceive public schools as cheaper but of lower quality, preferring private schools for their robustness, which correlates with better academic outcomes [23]. Yet, more nuanced research emphasizes selection bias: students attending private schools often come from higher socioeconomic status (SES) households with better parental education and other supports. Advanced analyses (e.g., using propensity matching and instrumental variables) suggest that once such selection is accounted for, the advantage of private schools diminishes, and low-cost private schools may even underperform relative to public schools [24]. In our study, the strong effect of school type might reflect both the resource advantages of private schools and the socioeconomic and parental education differences that accompany them. Without adjusting for selection, observed performance gaps may overstate a school-type causal effect. Thus, it is imperative that policymakers improve resource quality and teaching in public schools and be cautious when interpreting school-type effects without controlling for background variables. We also observed that higher parental education strongly predicts better academic performance in Mathematics. This finding is consistent with broader literature showing parental education as a key component of socioeconomic status that influences academic achievement through home literacy environment, expectations, and support [11]. In the Nigerian context, studies have similarly highlighted that parental involvement and education are important predictors of student performance, especially in sciences and general secondary schooling [25]. Conversely, some local studies argue that parental involvement per se, rather than formal education level, is the primary mechanism. For instance, in Anambra State, researchers found that direct parental engagement—such as providing guidance for take home school works —is a stronger predictor of performance than mere educational attainment [26]. The stronger signal for parental education in our study might reflect that higher parental education often yields both greater involvement and a more enriched home environment (books available, emphasis on reading and learning). Additionally, in our sample, higher parental education may be a proxy for other beneficial factors like tutoring, exposure to academic language, and support for study routines. Interventions should therefore be geared towards supporting parental educational empowerment (e.g., adult literacy, parental workshops) and encouraging active involvement in children’s learning especially when parental education is low. Our study found no significant association between academic outcomes and age, gender, working memory (WM), or inhibition scores. This is in contrast with some Nigerian studies, which reported age-related differences in Mathematics, and occasional gender disparities, though these effects are inconsistent across regions and subjects [27,28] Inconsistent findings may reflect sample age ranges, cultural factors around gender, and local schooling patterns. Notably, our results diverge from meta-analyses which show that WM is correlated with literacy and numeracy achievements [29], and that inhibition can influence adaptive school behaviors in younger children [30]. Some studies even indicate that WM capacity better predicts long-term academic success than intelligence quotient scores (IQ) [31]. However, a study on adolescents and adults with ADHD did not find cognitive inhibition deficits, suggesting that not all inhibition measures relate to academic outcomes in non-clinical adolescent samples [32]. Strengths, Limitations and Future Research Relying on standard tools, the study covered a wide range of various possible predictors amongst students in varying socio-economic environments. However, the cross-sectional design, may limit the ability to draw causal conclusions about the relationship between EF and academic performance. Additionally, reliance on self-report measures for executive function and reading habits may introduce bias. Future studies should consider longitudinal designs and include performance-based EF tasks to strengthen the validity of findings. Moreover, exploring additional EF components such as cognitive flexibility and planning could offer a more comprehensive understanding of how different cognitive processes relate to academic achievement. Given cultural and contextual differences, further research in diverse Nigerian settings (e.g., rural vs. urban) is also warranted. Conclusion In conclusion, this study adds to the growing body of evidence linking executive function skills to academic performance and underscores their importance in the educational experiences of Nigerian adolescents. Multi-layered interventions aimed at improving working memory and inhibition, particularly among students in public schools or those with limited access to academic support, may contribute to improved academic achievement and cognitive development. Declarations Ethical consideration Ethical approval was obtained from the Health Research Ethics Committee of The University of Benin Teaching Hospital. Permission for the study was obtained from the heads of the schools and verbal accent given by each student before participation in the study. All procedures performed in this study were conducted in accordance with relevant ethical guidelines and regulations. Consent to Participate One week prior to the commencement of the study, an information sheet and informed consent form were provided to the parents or legal guardians of eligible students, detailing the study objectives and procedures. Written informed consent was obtained from parents or legal guardians before participation. In addition, verbal assent was obtained from the students prior to their enrolment in the study. All procedures performed in this study were conducted in accordance with relevant ethical guidelines and regulations. Consent to Publish Declaration Not applicable Funding This research was self-funded by the authors and did not receive any grant or funding from any organization or not-for-profit agency. Competing interests’ Declaration The authors declare no competing interest that might be perceived to influence the result and/or discussion reported in this paper Data availability Declaration The data that support the findings of this study are available from the corresponding author, upon reasonable request. References Horanicova, S., Husarova, D., Madarasova Geckova, A., Lackova Rebicova, M., Sokolova, L., de Winter, A. F., et al. Adolescents' academic performance: what helps them and what hinders them from achievement and success?. Frontiers in psychology . 2024:(15 ) ;1350105. https://doi.org/10.3389/fpsyg.2024.1350105 Adams, B.G., Wiium, N. & Abubakar, A. Developmental Assets and Academic Performance of Adolescents in Ghana, Kenya, and South Africa. Child Youth Care Forum. 2019;(4 8) :207–222 https://doi.org/10.1007/s10566-018-9480-z Mastorci, F., Lazzeri, M. F. L., Vassalle, C., & Pingitore, A. The Transition from Childhood to Adolescence: Between Health and Vulnerability. Children (Basel, Switzerland) . 2024;11(8):989. https://doi.org/10.3390/children11080989 Suleiman, I.B., Okunade, O.A., Dada, E.G. Ezeanya U.C. Key factors influencing students’ academic performance. Journal of Electrical Systems and Inf Technol . 2024;11(41). https://doi.org/10.1186/s43067-024-00166-w Diamond A. (2013). Executive functions. Annual review of psychology . 2013;64:135–168. https://doi.org/10.1146/annurev-psych-113011-143750 Cortés M. A., Moyano M. N., & Quílez R. A. The Relationship Between Executive Functions and Academic Performance in Primary Education: Review and Meta-Analysis. Frontiers in psychology . 2019;(10):1582. https://doi.org/10.3389/fpsyg.2019.01582 Gunzenhauser, C., & Nückles, M. Training Executive Functions to Improve Academic Achievement: Tackling Avenues to Far Transfer. Frontiers in Psychology . 2021;( 12) : 624008. https://doi.org/10.3389/fpsyg.2021.624008 Heiskanen, M. A., Nevalainen, J., Pahkala, K., Juonala, M., Hutri, N., Kähönen, M., et al. Cognitive performance from childhood to old age and intergenerational correlations in the multigenerational Young Finns Study. Journal of neurology . 2024;271(11):7294–7308. https://doi.org/10.1007/s00415-024-12693-7 Spiegiel J., Goodrich J.M., Morris B.M., Jungerseen C. Relations between Executive Functions and Academic Outcomes in Elementary School Children: A Meta Analysis. Psychology Bulletin. 2021;147(4):329-351 DOI:10.1037/bul0000322 Cortes A., Moyano N., Robres A.Q. The Relationship between Executive Functions and Academic Performance in Primary Education: Review and Meta Analysis. Frontiers in Psychology. 2019;(10):1582 DOI:10.3389/fpsyg.2019.01582 Abid, N., Aslam, S., Alghamdi, A. A., & Kumar, T. Relationships among students' reading habits, study skills, and academic achievement in English at the secondary level. Frontiers in psychology . 2023 ;(14): 1020269. https://doi.org/10.3389/fpsyg.2023.1020269 Dubow, E. F., Boxer, P., & Huesmann, L. R. Long-term Effects of Parents' Education on Children's Educational and Occupational Success: Mediation by Family Interactions, Child Aggression, and Teenage Aspirations. Merrill-Palmer quarterly (Wayne State University. Press) . 2009: 55 (3):224–249. https://doi.org/10.1353/mpq.0.0030 Jacobson, L. A., Williford, A. P., & Pianta, R. C. The role of executive function in children's competent adjustment to middle school. Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence . 2011;17(3): 255– 280. https://doi.org/10.1080/09297049.2010.535654 Blair, C., & Raver, C. C. School readiness and self-regulation: a developmental psychobiological approach. Annual review of psychology . 2015;( 66 ):711–731. https://doi.org/10.1146/annurev-psych-010814-015221 Angwaomaodoko E. A. Influence of Socio-Economic Status on Academic Performance: A Comparative Study of Public and Private Schools in Nigeria. 2024. SSRN Electronic Journal DOI:10.2139/ssrn.4850066 PMA 2020/Nigeria. Monitoring young women’s health with PMA 2020. Adolescents and Young Adults Health Brief. 2017. Available at https://www.pmadata.org/sites/default/files/data_product_results/PMA2020-Nigeria-National-R2-Adol-Brief.pdf Assessed 10 th October 2025. Farooq S., Wani S. N., Maqbool A. Unveiling Academic Success: The Role of Study Habits in Secondary School Education. UGC Care Approved Journal. 202:3(26): 0972-3641. DOI:10.5281/zenodo.14038625 Muppalla, S. K., Vuppalapati, S., Reddy Pulliahgaru, A., & Sreenivasulu, H. Effects of Excessive Screen Time on Child Development: An Updated Review and Strategies for Management. Cureus . 2023; 15 (6):e40608. https://doi.org/10.7759/cureus.40608 Gilraine M., Penny J., Cramming: Short- and Long-Run Effects. EdWorkingPaper: 2021;21-444. Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/94pe-5j18 Ebbinghaus H. In: Memory: A contribution to experimental psychology. Ruger HA, Bussenius CE, Hilgard ER, translators. New York: Dover Publications; 1964. (Original work published in 1885). Vlach, H. A., & Sandhofer, C. M. Distributing learning over time: the spacing effect in children's acquisition and generalization of science concepts. Child development . 2012; 83 (4):1137–1144. https://doi.org/10.1111/j.1467-8624.2012.01781.x Akinloye G.M., Adu O., Adu E. A Comparative Analysis of Students Performance in Economics in Private and Public Secondary Schools in Lagos State, Nigeria. . 2015. Journal of Social Sciences 44(2-3):144-151. DOI:10.1080/09718923.2015.11893473 Adebayo F.A. Parents’ Preference for Private Secondary Schools in Nigeria. International Journal of Educational Sciences. 2009; 1(1) DOI:10.1080/09751122.2009.11889969 Pianta, R. C., & Ansari, A. Does Attendance in Private Schools Predict Student Outcomes at Age 15? Evidence From a Longitudinal Study. Educational Researcher . 2018; 47 (7):419-434. https://doi.org/10.3102/0013189X18785632 (Original work published 2018) Bamidele S., Odeyemi D. An Assessment of Parental Involvement on Public Secondary School Adolescents’ Academic Performance in Sciences, in Lagos State Nigeria. Edukasiana Jurnal Inovasi Pendidikan. 2024:3(1):1-14. DOI: 10.56916/ejip.v3i1.472 Ughamadu U., Okaforcha C., IGBOANUGO U.E. Parental Involvement as Predictors Of Students’ Academic Performance In Public Secondary Schools in Anambra State . Journal of Educational Research and Development. 2025;8(2):10 - 18 Olutola A., Ogunjimi M., Daramola D. Assessing the Impact of School Type, Gender and Age on Attitude and Mathematics Achievement of Senior Secondary School Students. Journal of Contemporary Teacher Education. 2021;(V): 43-52 Oladunmoye E.O., EnamuduG.P., Muhammad T.S. Differential Item Functioning estimate of WAEC Mathematics test form based on gender and age among secondary school students. ISAR J Mul Res Stud. 2024;2(5): ISSN (Online)- 2583-9705 Ji, Z., & Guo, K. The association between working memory and mathematical problem solving: A three-level meta-analysis. Frontiers in Psychology . 2023;(14):1091126. https://doi.org/10.3389/fpsyg.2023.1091126 Rhoades B.L., Greenberg M.T., Domitrovich C.E.The contribution of inhibitory control to preschoolers' social–emotional competence, Journal of Applied Developmental Psychology. 2009;30(3):310-320. ISSN 0193-3973 https://doi.org/10.1016/j.appdev.2008.12.012. Siquara G., Santos-Lima C. Working Memory and Intelligent Quotient. Which Best Predicts on School Environment. PSICO. 2018;49(4):365DOI:10.15448/1980-8623.2018.4.27943 Engelhardt, P. E., Nigg, J. T., Carr, L. A., & Fer. reira, F. Cognitive inhibition and working memory in attention-deficit/hyperactivity disorder. Journal of abnormal psychology . 2008; 117 (3):591–605. https://doi.org/10.1037/a0012593 Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 May, 2026 Reviewers agreed at journal 14 May, 2026 Reviews received at journal 14 May, 2026 Reviewers agreed at journal 14 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor invited by journal 27 Mar, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 25 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9172555","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":621352665,"identity":"53932a79-44c3-4c42-9864-51159610872f","order_by":0,"name":"Paul Ehiabhi Ikhurionan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYHACxgMMBgkJQLoBxJMDMtogEgdw60HRYkykFgaQFghIBGpkw6vFnP2MwQGGgrQ8g9uHGx8X1NxJ33C7ue3Bxx0Mcnw3ErBqsezJAWoxyCk2OJfYbDzj2LPcDXcOthvOPMNgLIlDi8EBsJaKxA1nGNukedgO5264kdgmzdvGkLgBl5bzb5C1/DucbgDS8reNoR6nlhsQh0G08LYdTgBrAQYakIHDLzOeFRxIMEhLnHmGsdmYt++w4cwbie2GvW0SQP88wB5i/MkbH3z4k5zYd4b94WOeb4fl+W6kP3vws81Gnu84DoeBCGxSEliVw7WMglEwCkbBKMALAOnnbEK3F6nxAAAAAElFTkSuQmCC","orcid":"","institution":"University of Benin","correspondingAuthor":true,"prefix":"","firstName":"Paul","middleName":"Ehiabhi","lastName":"Ikhurionan","suffix":""},{"id":621352668,"identity":"753d4fa5-1d0f-42b1-b11d-53237d07e7e5","order_by":1,"name":"Imuwahen Mbarie","email":"","orcid":"","institution":"University of Benin","correspondingAuthor":false,"prefix":"","firstName":"Imuwahen","middleName":"","lastName":"Mbarie","suffix":""},{"id":621352670,"identity":"86cfeeeb-1214-4551-8319-d9ff845e287e","order_by":2,"name":"Abieyuwa Peace Omoregie","email":"","orcid":"","institution":"University of Benin","correspondingAuthor":false,"prefix":"","firstName":"Abieyuwa","middleName":"Peace","lastName":"Omoregie","suffix":""}],"badges":[],"createdAt":"2026-03-19 19:25:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9172555/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9172555/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107704871,"identity":"5bf515f9-0c22-4e70-9470-e8627c645316","added_by":"auto","created_at":"2026-04-24 09:01:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":273441,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9172555/v1/54302e3e-8ee4-48b6-9c84-258c5bf91dea.pdf"},{"id":107108168,"identity":"308faf77-35e9-444c-a8a3-ca92b2239475","added_by":"auto","created_at":"2026-04-16 22:15:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15525,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9172555/v1/906d046c83d1c504230d3bc1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictors of Academic Outcomes amongst Secondary Students in Benin City, Nigeria","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcademic performance plays a dual role as a key indicator and critical outcome of adolescent development, with far-reaching implications for educational attainment, career trajectories, and socioeconomic mobility (1,2). Beyond creating a sense of fulfilment for the adolescent, it also serves as a key determinant of life opportunities in adulthood. The adolescent stage is however, a period of intense physical, emotional, and cognitive development where the foundations for lifelong learning are consolidated. (3). During this phase, students take on new academic tasks and are constantly required to meet increasing academic demands while adapting to diverse educational environments. Academic achievement during this developmental stage is thus shaped by a multi-complex interplay of cognitive, behavioral, and socio-environmental predictors (4). The interplay of the cognitive and behavioural factors is explained by Executive functions (EF), which is typically assessed by testing working memory, (as the ability to retain and manipulate information for short periods} and inhibition (the ability to suppress impulsive responses). (5\u0026ndash;7) In adolescents, EF aid in concentration, sorting out of relevant information when faced with a myriad of information, avoiding distractions and remembering instructions. EF controls thought processes and actions towards a set goal, and are activated from childhood through to adulthood with a decline at old age. (8)\u003c/p\u003e \u003cp\u003eEpidemiological data suggest that children with poor EF experience difficulty in language skills, reading and mathematical abilities (9). On a longitudinal scale, weak EF has been identified as an indicator of academic difficulties and unfulfilled academic goals while a well-developed EF increases the likelihood of success and satisfaction in life. (7,9). A bulk of growing evidence reports a strong association between EFs and academic performance. (7,9,10) While cognitive abilities such as working memory and inhibitory control are essential for learning they operate within broader socio-educational contexts shaped by variables such as reading habits, parental education, and school type (11\u0026ndash;13). Blair and Raver found that socioeconomic status and school quality significantly predicted literacy and numeracy outcomes, but their study primarily focused on early childhood, thereby limiting its relevance to adolescents. (14) In Nigeria, Angwaomaodoko documented pronounced disparities in academic performance between public and private school students, largely attributable to differences in resource allocation. (15)\u003c/p\u003e \u003cp\u003eHowever, existing research have often been limited in scope by focusing exclusively on cognitive abilities or examining a single subject area, overlooking and under-exploring the combined influence of cognitive, behavioral, and socio-demographic factors on multiple core subjects among the adolescent populations. The absence of such integrated studies in Nigeria is particularly concerning given the socio-economic disparities and the large proportion of adolescents in the national population. (15,16) Understanding these dynamics thus becomes imperative in designing school-based interventions which improve the academic life of the adolescents in resource-variable educational systems. This study seeks to generate multi-level, evidence-based interventions on the outcomes of combined influence of working memory, inhibition, reading hours, school type, and parental education on end-of-term Mathematics and English scores among early and mid-adolescents in Benin City, Nigeria. The inclusion of students from both public and private schools, provides a broader environmental and socio-economic spectrum, revealing the variations in educational context and its potential effect on performance, with potential applicability in similar low- and middle-income settings.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Study Setting\u003c/h2\u003e \u003cp\u003eWe conducted a descriptive cross-sectional study amongst secondary school students attending three senior schools in Benin City, Edo State, Nigeria. Benin City, which is an urban metropolis with a diversity of educational institutions, operates the national 6-3-3-4 academic structure comprising of 6 years in primary school, 3 years in junior secondary school, 3 years in senior secondary school and 4 years in a tertiary institution. The State\u0026rsquo;s Ministry of Education oversees the registering and monitoring all public and private owned educational institutions, through different boards. Though the private and public institutions operate the same syllabus, there are often variations in the school practice, methods of teaching and school environment and school rules. The study thus included two public and one privately owned secondary school institutions purposively selected to represent to provide a broader scope.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRecruitment and Sampling of Participants\u003c/h3\u003e\n\u003cp\u003eOne week before the study an informative letter and the informed consent form was sent to the students\u0026rsquo; parents or legal guardian in order to inform them of the objectives and procedure of the study. We recruited participants 550 participants between the ages of between 13 and 16 years from Senior Secondary School 1 (SSS1). Only students who had a regular school attendance greater than 90% of total school days in the previous term who returned signed informed consent from their parents/ guardians and had no diagnosed neurological or learning disabilities were eligible to be recruited. Exclusion criteria included; having physical impairment that limited the ability to fill the data collection instruments and having a known neurologic or psychological diagnosis significant enough to limit participation. We therefore recruited only healthy adolescents\u0026rsquo; who had normal physical, intellectual, auditory, and visual conditions. Students who were absent on the days of data collection were excluded from the study.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eData were collected over an eight-week period, with the aid of a standardized self-administered questionnaire and academic records of selected participants. The study questionnaires were administered during school hours in group settings under the supervision of trained research assistants. The research assistants were available throughout the duration of the data collection to provide guidance to students who needed assistance in understanding the questionnaire. End of term scores were obtained from the official examination record of each school.\u003c/p\u003e\n\u003ch3\u003eInstruments\u003c/h3\u003e\n\u003cp\u003eWe utilized a structured questionnaire to assess socio-demographic characteristics (such as age, gender, school type (public vs. private), parental education level and reading habits (number of hours spent reading or studying outside of school per day). To assess for EFs, we utilized the Teenage Executive Function Inventory (TEXI), This standardized instrument assessed working memory and Inhibition on two different sub-scales. Each sub-scale consisted of self-report items rated on a Likert scale, with higher scores indicating poorer EF functioning. For the purpose of this study, we adopted the generalized definitions of working memory (defined as the ability to retain and manipulate information for short periods) and Inhibition (refers to the ability to suppress impulsive responses). We assessed academic performance as students\u0026rsquo; percentage scores in Mathematics and English from the most recently completed academic term, obtained from the official examination record of each school.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using Statistical Package for Social Sciences (IBM SPSS Statistics for windows, Version 26.0. Armonk, NY: IBM Corp). Continuous data were summarized as means and standard deviations, while categorical data were presented as frequencies and percentages. Independent samples t-tests was used to compare academic scores across gender and school type. Pearson correlation coefficients were used to assess the relationship between study variables. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. Descriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean age of the study population was 15.39 (SD\u0026thinsp;=\u0026thinsp;1.29) years. The study had a population of 255 (46.4%) males and 295 (53.6%) females with a male: female ratio of 0.86:1. Public school students made up 54.2% of the sample, while 45.8% were enrolled in private schools. Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic characteristics of the 550 participants.\u003c/p\u003e\n\u003ch3\u003eGroup Comparisons\u003c/h3\u003e\n\u003cp\u003eIndependent t-tests revealed that males and female students had comparable performance in both Mathematics and English end of term scores. Private school students scored significantly higher in Mathematics (M\u0026thinsp;=\u0026thinsp;54.4%, SD\u0026thinsp;=\u0026thinsp;14.2%) compared to public school students (M\u0026thinsp;=\u0026thinsp;49.4%, SD\u0026thinsp;=\u0026thinsp;15.3%); p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. However, both public (m\u0026thinsp;\u0026minus;\u0026thinsp;53.80, SD \u0026ndash; 16.15%) and private schools (M\u0026thinsp;=\u0026thinsp;52.46%, SD\u0026thinsp;=\u0026thinsp;141.74%) had comparable English scores, p\u0026thinsp;=\u0026thinsp;0.276 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGroup comparison of academic performance based on gender and school type\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMathematics score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eEnglish scores\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003et-test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003et-test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.67 (15.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.20 (16.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.85 (14.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.03 (11.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchool Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.41 (15.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.80 (16.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.38 (14.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.46 (11.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCorrelation Analysis\u003c/h3\u003e\n\u003cp\u003ePearson correlation coefficients showed weak positive correlations between the type of school (r\u0026thinsp;=\u0026thinsp;0.166, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the number of hours spent reading (r\u0026thinsp;=\u0026thinsp;0.118, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), Father\u0026rsquo;s education (r\u0026thinsp;=\u0026thinsp;0.088, p\u0026thinsp;=\u0026thinsp;0.039) and Mother\u0026rsquo;s education (r\u0026thinsp;=\u0026thinsp;0.150, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with Mathematics scores. Only the number of hours spent reading (r\u0026thinsp;=\u0026thinsp;0.108, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was positively correlated with English scores. However, the EF subscale scores did not show significant correlation. The Pearson\u0026rsquo;s correlation analysis is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Matrix (Pearson's r)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaths score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnglish Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWorking Memory Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInhibition Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eType of School\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eReading hours\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eFather\u0026rsquo;s Education Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eMother\u0026rsquo;s education level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaths score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.630*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.166*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.118*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.088*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.150*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnglish Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.630*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.108*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking Memory Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInhibition Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.118*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.276*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.204*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.180*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of School\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.166*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.276*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.216*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.357*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.446*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReading hours\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.118*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.118*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.216*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.200*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.255*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFather\u0026rsquo;s Education Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.088*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.204*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.357*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.200*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.574*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother\u0026rsquo;s education level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.150*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.180*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.446*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.255*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.574*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e* Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the predictors of academic performance in Mathematics and English among adolescents in three secondary schools in Benin City, Nigeria. We found that reading hours per day, type of school and parental education were strongly predictive of academic performance in Mathematics while English scores were predicted by the number of reading hours only. The study found no association between age, gender, working memory scores and inhibition scores and academic outcomes.\u003c/p\u003e \u003cp\u003eOur study reported that students who studied regularly were more likely to have better academic performance in mathematics and English. Thus, indicating that reading habits were a direct determinant of academic outcomes. These findings were in close similarity with other findings which reported that academic outcomes were improved by good study habits outside the school premises. (17) Conversely, these findings also indicate that poor study habits were a major determinant of poor academic outcomes. Poor study habits such as cramming, screen distractions have been said to negatively affect academic outcomes. Investigators report that increased screen time worsens EF and academic outcomes as high screen time provides a wide range of cognitive consequences (18). While poor study habits like cramming may offer temporary solutions, its long-term comprehension consequences, anxiety and mental stress outweigh the short-term success.(19) Its distinction from proper studying hovers around consistent, self-directed reading which promotes deep processing and retention, unlike last-minute mass practice (cramming) which undermines performance, especially when it reduces sleep. Regular, purposeful reading rather than sleep-deprived cramming, positively impacts academic performance. These findings agree with the well-established spacing effect of improved learning through distributed study (20,21) and emphasize the importance of adopting well-structured routines for children and adolescents based on academic goals to improve academic performance. The spacing effect explains that \u0026ldquo;long term memory is enhanced when events are spaced over a period of time, rather than compounded in very close successions\u0026rdquo; Proper scheduling and constant abiding by reading timetables/schedules promote stronger memory recall and improved academic achievements.\u003c/p\u003e \u003cp\u003eAlso, we also found school type to be a strong predictor of academic performance, with private schools outperforming public ones. Adolescents in private schools were reported to have a higher end-of term scores in mathematics and English compared to their peers in public schools. These findings align with previous Nigerian studies on the association between school type and academic performance. A comparative analysis in Lagos State showed that private school students performed better in Economics than their public-school counterparts, often credited to superior infrastructure and curriculum implementation [22]. Another study noted that parents perceive public schools as cheaper but of lower quality, preferring private schools for their robustness, which correlates with better academic outcomes [23]. Yet, more nuanced research emphasizes selection bias: students attending private schools often come from higher socioeconomic status (SES) households with better parental education and other supports. Advanced analyses (e.g., using propensity matching and instrumental variables) suggest that once such selection is accounted for, the advantage of private schools diminishes, and low-cost private schools may even underperform relative to public schools [24]. In our study, the strong effect of school type might reflect both the resource advantages of private schools and the socioeconomic and parental education differences that accompany them. Without adjusting for selection, observed performance gaps may overstate a school-type causal effect. Thus, it is imperative that policymakers improve resource quality and teaching in public schools and be cautious when interpreting school-type effects without controlling for background variables.\u003c/p\u003e \u003cp\u003eWe also observed that higher parental education strongly predicts better academic performance in Mathematics. This finding is consistent with broader literature showing parental education as a key component of socioeconomic status that influences academic achievement through home literacy environment, expectations, and support [11]. In the Nigerian context, studies have similarly highlighted that parental involvement and education are important predictors of student performance, especially in sciences and general secondary schooling [25]. Conversely, some local studies argue that parental involvement per se, rather than formal education level, is the primary mechanism. For instance, in Anambra State, researchers found that direct parental engagement\u0026mdash;such as providing guidance for take home school works \u0026mdash;is a stronger predictor of performance than mere educational attainment [26]. The stronger signal for parental education in our study might reflect that higher parental education often yields both greater involvement and a more enriched home environment (books available, emphasis on reading and learning). Additionally, in our sample, higher parental education may be a proxy for other beneficial factors like tutoring, exposure to academic language, and support for study routines. Interventions should therefore be geared towards supporting parental educational empowerment (e.g., adult literacy, parental workshops) and encouraging active involvement in children\u0026rsquo;s learning especially when parental education is low.\u003c/p\u003e \u003cp\u003eOur study found no significant association between academic outcomes and age, gender, working memory (WM), or inhibition scores. This is in contrast with some Nigerian studies, which reported age-related differences in Mathematics, and occasional gender disparities, though these effects are inconsistent across regions and subjects [27,28] Inconsistent findings may reflect sample age ranges, cultural factors around gender, and local schooling patterns. Notably, our results diverge from meta-analyses which show that WM is correlated with literacy and numeracy achievements [29], and that inhibition can influence adaptive school behaviors in younger children [30]. Some studies even indicate that WM capacity better predicts long-term academic success than intelligence quotient scores (IQ) [31]. However, a study on adolescents and adults with ADHD did not find cognitive inhibition deficits, suggesting that not all inhibition measures relate to academic outcomes in non-clinical adolescent samples [32].\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStrengths, Limitations and Future Research\u003c/h2\u003e \u003cp\u003eRelying on standard tools, the study covered a wide range of various possible predictors amongst students in varying socio-economic environments. However, the cross-sectional design, may limit the ability to draw causal conclusions about the relationship between EF and academic performance. Additionally, reliance on self-report measures for executive function and reading habits may introduce bias. Future studies should consider longitudinal designs and include performance-based EF tasks to strengthen the validity of findings. Moreover, exploring additional EF components such as cognitive flexibility and planning could offer a more comprehensive understanding of how different cognitive processes relate to academic achievement. Given cultural and contextual differences, further research in diverse Nigerian settings (e.g., rural vs. urban) is also warranted.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study adds to the growing body of evidence linking executive function skills to academic performance and underscores their importance in the educational experiences of Nigerian adolescents. Multi-layered interventions aimed at improving working memory and inhibition, particularly among students in public schools or those with limited access to academic support, may contribute to improved academic achievement and cognitive development.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Health Research Ethics Committee of The University of Benin Teaching Hospital. Permission for the study was obtained from the heads of the schools and verbal accent given by each student before participation in the study. All procedures performed in this study were conducted in accordance with relevant ethical guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne week prior to the commencement of the study, an information sheet and informed consent form were provided to the parents or legal guardians of eligible students, detailing the study objectives and procedures. Written informed consent was obtained from parents or legal guardians before participation. In addition, verbal assent was obtained from the students prior to their enrolment in the study. All procedures performed in this study were conducted in accordance with relevant ethical guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was self-funded by the authors and did not receive any grant or funding from any organization or not-for-profit agency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026rsquo; Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest that might be perceived to influence the result and/or discussion reported in this paper\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHoranicova, S., Husarova, D., Madarasova Geckova, A., Lackova Rebicova, M., Sokolova, L., de Winter, A. F., et al. Adolescents\u0026apos; academic performance: what helps them and what hinders them from achievement and success?. \u003cem\u003eFrontiers in psychology\u003c/em\u003e. 2024:(15\u003cem\u003e)\u003c/em\u003e;1350105. https://doi.org/10.3389/fpsyg.2024.1350105\u003c/li\u003e\n\u003cli\u003eAdams, B.G., Wiium, N. \u0026amp; Abubakar, A. Developmental Assets and Academic Performance of Adolescents in Ghana, Kenya, and South Africa. \u003cem\u003eChild Youth Care Forum. \u003c/em\u003e2019;(4\u003cstrong\u003e8)\u003c/strong\u003e:207\u0026ndash;222 https://doi.org/10.1007/s10566-018-9480-z\u003c/li\u003e\n\u003cli\u003eMastorci, F., Lazzeri, M. F. L., Vassalle, C., \u0026amp; Pingitore, A. The Transition from Childhood to Adolescence: Between Health and Vulnerability. \u003cem\u003eChildren (Basel, Switzerland)\u003c/em\u003e. 2024;11(8):989. https://doi.org/10.3390/children11080989\u003c/li\u003e\n\u003cli\u003eSuleiman, I.B., Okunade, O.A., Dada, E.G. Ezeanya U.C.\u003cem\u003e \u003c/em\u003eKey factors influencing students\u0026rsquo; academic performance. \u003cem\u003eJournal of Electrical Systems and Inf Technol\u003c/em\u003e. 2024;11(41). https://doi.org/10.1186/s43067-024-00166-w\u003c/li\u003e\n\u003cli\u003eDiamond A. (2013). Executive functions. \u003cem\u003eAnnual review of psychology\u003c/em\u003e. 2013;64:135\u0026ndash;168. https://doi.org/10.1146/annurev-psych-113011-143750\u003c/li\u003e\n\u003cli\u003eCort\u0026eacute;s M. A., Moyano M. N., \u0026amp; Qu\u0026iacute;lez R. A. The Relationship Between Executive Functions and Academic Performance in Primary Education: Review and Meta-Analysis. \u003cem\u003eFrontiers in psychology\u003c/em\u003e. 2019;(10):1582. https://doi.org/10.3389/fpsyg.2019.01582\u003c/li\u003e\n\u003cli\u003eGunzenhauser, C., \u0026amp; N\u0026uuml;ckles, M. Training Executive Functions to Improve Academic Achievement: Tackling Avenues to Far Transfer. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e. 2021;(\u003cem\u003e12)\u003c/em\u003e: 624008. https://doi.org/10.3389/fpsyg.2021.624008\u003c/li\u003e\n\u003cli\u003eHeiskanen, M. A., Nevalainen, J., Pahkala, K., Juonala, M., Hutri, N., K\u0026auml;h\u0026ouml;nen, M., et al. Cognitive performance from childhood to old age and intergenerational correlations in the multigenerational Young Finns Study. \u003cem\u003eJournal of neurology\u003c/em\u003e. 2024;271(11):7294\u0026ndash;7308. https://doi.org/10.1007/s00415-024-12693-7\u003c/li\u003e\n\u003cli\u003eSpiegiel J., Goodrich J.M., Morris B.M., Jungerseen C. Relations between Executive Functions and Academic Outcomes in Elementary School Children: A Meta Analysis. Psychology Bulletin. 2021;147(4):329-351 DOI:10.1037/bul0000322\u003c/li\u003e\n\u003cli\u003eCortes A., Moyano N., Robres A.Q. The Relationship between Executive Functions and Academic Performance in Primary Education: Review and Meta Analysis. Frontiers in Psychology. 2019;(10):1582 DOI:10.3389/fpsyg.2019.01582\u003c/li\u003e\n\u003cli\u003eAbid, N., Aslam, S., Alghamdi, A. A., \u0026amp; Kumar, T. Relationships among students\u0026apos; reading habits, study skills, and academic achievement in English at the secondary level. \u003cem\u003eFrontiers in psychology\u003c/em\u003e. 2023\u003cem\u003e;(14):\u003c/em\u003e 1020269. https://doi.org/10.3389/fpsyg.2023.1020269\u003c/li\u003e\n\u003cli\u003eDubow, E. F., Boxer, P., \u0026amp; Huesmann, L. R. Long-term Effects of Parents\u0026apos; Education on Children\u0026apos;s Educational and Occupational Success: Mediation by Family Interactions, Child Aggression, and Teenage Aspirations. \u003cem\u003eMerrill-Palmer quarterly (Wayne State University. Press)\u003c/em\u003e. 2009:\u003cem\u003e55\u003c/em\u003e(3):224\u0026ndash;249. https://doi.org/10.1353/mpq.0.0030\u003c/li\u003e\n\u003cli\u003eJacobson, L. A., Williford, A. P., \u0026amp; Pianta, R. C. The role of executive function in children\u0026apos;s competent adjustment to middle school. \u003cem\u003eChild neuropsychology : a journal on normal and abnormal development in childhood and adolescence\u003c/em\u003e. \u003cem\u003e2011;17(3): 255\u0026ndash;\u003c/em\u003e280. https://doi.org/10.1080/09297049.2010.535654\u003c/li\u003e\n\u003cli\u003eBlair, C., \u0026amp; Raver, C. C. School readiness and self-regulation: a developmental psychobiological approach. \u003cem\u003eAnnual review of psychology\u003c/em\u003e. 2015;(\u003cem\u003e66\u003c/em\u003e):711\u0026ndash;731. https://doi.org/10.1146/annurev-psych-010814-015221\u003c/li\u003e\n\u003cli\u003eAngwaomaodoko E. A. Influence of Socio-Economic Status on Academic Performance: A Comparative Study of Public and Private Schools in Nigeria. 2024. SSRN Electronic Journal DOI:10.2139/ssrn.4850066\u003c/li\u003e\n\u003cli\u003ePMA 2020/Nigeria. Monitoring young women\u0026rsquo;s health with PMA 2020. Adolescents and Young Adults Health Brief. 2017. Available at https://www.pmadata.org/sites/default/files/data_product_results/PMA2020-Nigeria-National-R2-Adol-Brief.pdf Assessed 10\u003csup\u003eth \u003c/sup\u003eOctober 2025.\u003c/li\u003e\n\u003cli\u003eFarooq S., Wani S. N., Maqbool A. Unveiling Academic Success: The Role of Study Habits in Secondary School Education. UGC Care Approved Journal. 202:3(26): 0972-3641. DOI:10.5281/zenodo.14038625\u003c/li\u003e\n\u003cli\u003eMuppalla, S. K., Vuppalapati, S., Reddy Pulliahgaru, A., \u0026amp; Sreenivasulu, H. Effects of Excessive Screen Time on Child Development: An Updated Review and Strategies for Management. \u003cem\u003eCureus\u003c/em\u003e. 2023;\u003cem\u003e15\u003c/em\u003e(6):e40608. https://doi.org/10.7759/cureus.40608\u003c/li\u003e\n\u003cli\u003eGilraine M., Penny J., Cramming: Short- and Long-Run Effects. EdWorkingPaper: 2021;21-444. Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/94pe-5j18 \u003c/li\u003e\n\u003cli\u003eEbbinghaus H. In: Memory: A contribution to experimental psychology. Ruger HA, Bussenius CE, Hilgard ER, translators. New York: Dover Publications; 1964. (Original work published in 1885).\u003c/li\u003e\n\u003cli\u003eVlach, H. A., \u0026amp; Sandhofer, C. M. Distributing learning over time: the spacing effect in children\u0026apos;s acquisition and generalization of science concepts. \u003cem\u003eChild development\u003c/em\u003e. 2012;\u003cem\u003e83\u003c/em\u003e(4):1137\u0026ndash;1144. https://doi.org/10.1111/j.1467-8624.2012.01781.x\u003c/li\u003e\n\u003cli\u003eAkinloye G.M., Adu O., Adu E. A Comparative Analysis of Students Performance in Economics in Private and Public Secondary Schools in Lagos State, Nigeria. . 2015. Journal of Social Sciences 44(2-3):144-151. DOI:10.1080/09718923.2015.11893473\u003c/li\u003e\n\u003cli\u003eAdebayo F.A. Parents\u0026rsquo; Preference for Private Secondary Schools in Nigeria. International Journal of Educational Sciences. 2009; 1(1) DOI:10.1080/09751122.2009.11889969 \u003c/li\u003e\n\u003cli\u003ePianta, R. C., \u0026amp; Ansari, A. Does Attendance in Private Schools Predict Student Outcomes at Age 15? Evidence From a Longitudinal Study. \u003cem\u003eEducational Researcher\u003c/em\u003e. 2018;\u003cem\u003e47\u003c/em\u003e(7):419-434. https://doi.org/10.3102/0013189X18785632 (Original work published 2018)\u003c/li\u003e\n\u003cli\u003eBamidele S., Odeyemi D. An Assessment of Parental Involvement on Public Secondary School Adolescents\u0026rsquo; Academic Performance in Sciences, in Lagos State Nigeria. Edukasiana Jurnal Inovasi Pendidikan. 2024:3(1):1-14. DOI: 10.56916/ejip.v3i1.472 \u003c/li\u003e\n\u003cli\u003eUghamadu U., Okaforcha C., IGBOANUGO U.E. Parental Involvement as Predictors Of Students\u0026rsquo; Academic Performance In Public Secondary Schools in Anambra State . Journal of Educational Research and Development. 2025;8(2):10 - 18\u003c/li\u003e\n\u003cli\u003eOlutola A., Ogunjimi M., Daramola D. Assessing the Impact of School Type, Gender and Age on Attitude and Mathematics Achievement of Senior Secondary School Students. Journal of Contemporary Teacher Education. 2021;(V): 43-52\u003c/li\u003e\n\u003cli\u003eOladunmoye E.O., EnamuduG.P., Muhammad T.S. Differential Item Functioning estimate of WAEC Mathematics test form based on gender and age among secondary school students. ISAR J Mul Res Stud. 2024;2(5): ISSN (Online)- 2583-9705 \u003c/li\u003e\n\u003cli\u003eJi, Z., \u0026amp; Guo, K. The association between working memory and mathematical problem solving: A three-level meta-analysis. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e. 2023;(14):1091126. https://doi.org/10.3389/fpsyg.2023.1091126\u003c/li\u003e\n\u003cli\u003eRhoades B.L., Greenberg M.T., Domitrovich C.E.The contribution of inhibitory control to preschoolers\u0026apos; social\u0026ndash;emotional competence, Journal of Applied Developmental Psychology. 2009;30(3):310-320. ISSN 0193-3973 https://doi.org/10.1016/j.appdev.2008.12.012.\u003c/li\u003e\n\u003cli\u003eSiquara G., Santos-Lima C. Working Memory and Intelligent Quotient. Which Best Predicts on School Environment. PSICO. 2018;49(4):365DOI:10.15448/1980-8623.2018.4.27943\u003c/li\u003e\n\u003cli\u003eEngelhardt, P. E., Nigg, J. T., Carr, L. A., \u0026amp; Fer. reira, F. Cognitive inhibition and working memory in attention-deficit/hyperactivity disorder. \u003cem\u003eJournal of abnormal psychology\u003c/em\u003e. 2008;\u003cem\u003e117\u003c/em\u003e(3):591\u0026ndash;605. https://doi.org/10.1037/a0012593\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Executive Function, Academic Performance, Adolescents","lastPublishedDoi":"10.21203/rs.3.rs-9172555/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9172555/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eAdolescent academic performance is shaped by multiple factors, including cognitive abilities, and socio-educational context. Executive functions (EFs) are essential for learning, yet their role in academic outcomes among Nigerian adolescents is poorly studied. This study assessed the influence of executive functions, reading habits, parental education, and school type on Mathematics and English performance among secondary school adolescents in Benin City, Nigeria.\u003c/p\u003e\u003ch2\u003eMethod:\u003c/h2\u003e \u003cp\u003eA descriptive cross-sectional correlational study was conducted among 550 Senior Secondary School 1 students. Sociodemographic data and daily reading hours were collected using structured questionnaires. Executive functions were assessed with TEXI. Academic performance was measured using end-of-term Mathematics and English scores. Data were analyzed using SPSS version 26.0, employing descriptive statistics, Pearson correlations, and independent t-tests, with significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eParticipants had a mean age of 15.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 years; 46.4% were male. Public school students comprised 54.2%.. School type (r\u0026thinsp;=\u0026thinsp;0.166, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), parental education and reading hours (Mathematics: r\u0026thinsp;=\u0026thinsp;0.118; English: r\u0026thinsp;=\u0026thinsp;0.108, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) significantly correlated with performance, whereas EF subscales did not.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eExecutive functions did not predict academic outcomes. School type and reading habits were key determinants in adolescent achievement.\u003c/p\u003e","manuscriptTitle":"Predictors of Academic Outcomes amongst Secondary Students in Benin City, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-16 22:15:39","doi":"10.21203/rs.3.rs-9172555/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-15T03:56:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11117202866430708026636931253421681912","date":"2026-05-15T03:43:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T14:27:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39550608364257330556301576615269272121","date":"2026-05-14T09:43:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22071611041050807584778985295477129230","date":"2026-05-12T14:45:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195752060625966371868090057046555648997","date":"2026-05-12T11:26:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296547594894157781451738182873745693659","date":"2026-04-29T10:20:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T07:27:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-27T10:08:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T18:35:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T13:39:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Education","date":"2026-03-25T13:35:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diedu","sideBox":"Learn more about [Discover Education](https://www.springer.com/journal/44217)","snPcode":"44217","submissionUrl":"https://submission.nature.com/new-submission/44217/3","title":"Discover Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"277bc850-0aaf-4ca8-9164-d08b81d7574b","owner":[],"postedDate":"April 16th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-15T03:56:28+00:00","index":75,"fulltext":""},{"type":"reviewerAgreed","content":"11117202866430708026636931253421681912","date":"2026-05-15T03:43:27+00:00","index":74,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T14:27:18+00:00","index":73,"fulltext":""},{"type":"reviewerAgreed","content":"39550608364257330556301576615269272121","date":"2026-05-14T09:43:30+00:00","index":70,"fulltext":""},{"type":"reviewerAgreed","content":"22071611041050807584778985295477129230","date":"2026-05-12T14:45:17+00:00","index":69,"fulltext":""},{"type":"reviewerAgreed","content":"195752060625966371868090057046555648997","date":"2026-05-12T11:26:45+00:00","index":68,"fulltext":""},{"type":"reviewerAgreed","content":"296547594894157781451738182873745693659","date":"2026-04-29T10:20:04+00:00","index":40,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T22:15:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-16 22:15:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9172555","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9172555","identity":"rs-9172555","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}