Improving Mathematics Performance Through After-School Interventions: A Gender-Based Analysis of Low-Achieving Students

Abstract

Despite growing global interest in improving mathematics outcomes, there has been limited empirical research in Nigeria that has rigorously evaluated the impact of structured after-school intervention programs on low-achieving students, particularly through a gender-based lens. This study addresses this gap by examining the effectiveness of after-school mathematics instruction on the performance of senior secondary school students in Oyo State, Nigeria. The researchers adopted a quasi-experimental pretest–posttest control group design with a 2 × 2 factorial structure. The sample consisted of 92 purposively selected low-achieving students (47 males and 45 females) from eight public, co-educational secondary schools, who were randomly assigned to experimental and control groups. Over the course of six weeks, the experimental group received structured after-school mathematics lessons that targeted foundational skills, while the control group continued with conventional classroom instruction. Data was collected using a researcher-developed Mathematics Achievement Test (MAT), which was validated by mathematics education experts and yielded a Cronbach’s alpha of 0.82. Analysis of Covariance (ANCOVA) revealed a statistically significant improvement in the mathematics achievement of students in the intervention group (F(1, 87) = 114.88, p < 0.05), with a large effect size (Partial η² = 0.569). Although no significant interaction effect between gender and treatment was observed (F(1, 87) = 0.208, p > 0.05). This study contributes to the limited literature on gender-responsive after-school interventions in sub-Saharan African contexts. Findings support the implementation of targeted support programs to enhance mathematics outcomes for struggling learners, regardless of gender.

1. Introduction

Mathematics, characterised by precision, abstraction, and logical reasoning, is central to scientific and technological progress, while fostering critical thinking and problem-solving skills essential for personal and societal development (Cresswell & Speelman, 2020; Yadav, 2019). Yet, mathematics underachievement persists globally, exacerbated by math anxiety or phobia, negative attitudes, and reliance on teacher-centred pedagogies among others (Ariyo & Adeleke, 2018; Garba & Hamman-Tukur, 2015; Haase & Krinzinger, 2019). Inequitable access to qualified teachers and punitive grading practices, such as awarding zeros for incomplete work, further demotivate learners and compromise educational fairness (Paul, 2018; T. R. Opesemowo, 2024). These challenges highlight systemic issues in assessment and instruction that hinder engagement, resilience, and mastery. Parental involvement is beneficial in mitigating anxiety and enhancing performance (Deringöl, 2022; Ekeh & Onuike, 2025; Adewuyi & Dwarika, 2023), while persistent gender disparities in mathematics achievement underscore the need for equity-focused interventions in STEM (Smith & Evans, 2024; Xie & Liu, 2023).

After-school mathematics intervention programs have effectively addressed these challenges by providing extended opportunities for practice, targeted remediation, and collaborative learning environments (Ulya, 2024; Adewuyi & Opesemowo, 2024). Research confirms that such programs enhance learners’ mathematical skills and overall academic performance, particularly among low-achieving students (Grigoroiu et al., 2024; Leonano et al., 2024; O. A. G. Opesemowo & Adewuyi, 2024). Successful interventions often incorporate small-group instruction (van de Pol et al., 2019), differentiated remediation (Christensen et al., 2023; Cureton, 2023), and supportive learning environments that build resilience (Cromer et al., 2019), confidence, reinforce problem-solving abilities, and close achievement gaps (Jusko et al., 2025; Kwon, 2025). A meta-analysis by Lynch et al. (2023) confirmed their effectiveness in narrowing persisting gaps, while Fien et al. (2018) demonstrated significant gains among low-achieving students in structured after-school programs.

Building on this foundation, the present study examines the intricate interplay of cognitive, affective, and contextual factors that impede mathematics achievement. It focuses on the role of after-school interventions in enhancing performance for low-achieving students, with a particular emphasis on gender dynamics. Addressing the research gap, this study explores the overall effectiveness of such interventions and whether gender moderates their impact. In doing so, it aligns with international efforts to promote equity in STEM (Science, Technology, Engineering, and Mathematics) and the broader goals of Sustainable Development Goal 4 (SDG 4), which aims to provide inclusive and equitable quality education for all by 2030 (UNESCO, 2022). Specifically, the study aims to: (i) examine the effect of after-school intervention on mathematics achievement between low-achieving students who receive after-school intervention and those who do not, (ii) investigate main effect of gender on the mathematics achievement of gender on mathematics achievement of low-achieving students and (iii) assess the interaction effect between teaching method and gender on the mathematics achievement of low-achieving students.

2. Research Hypotheses

This study is guided by the following null hypotheses, which are tested at a significant level of 0.05.

H₀₁. 

There is no significant effect in mathematics achievement between low-achieving students who receive after-school intervention and those who do not.

H₀₂. 

There is no statistically significant main effect of gender on the mathematics achievement of low-achieving students.

H₀₃. 

No statistically significant interaction effect between teaching method and gender on the mathematics achievement of low-achieving students.

3. Theoretical Lens

Every rigorous study requires a carefully articulated theoretical foundation that guides its design, analysis, and interpretation. For this study, Vygotsky’s socio-constructivist perspective provides the conceptual lens through which after-school mathematics interventions are examined. Although Vygotsky’s seminal work dates back almost a century, it remains influential in contemporary education research, particularly in contexts concerned with equality, scaffolding, and collaborative learning. Importantly, this study does not adopt Vygotsky’s ideas as a rigid framework, but rather as a flexible perspective that evolves across diverse cultural and educational landscapes (Bøttcher & Dammeyer, 2025).

By situating Vygotsky within the international discourse on inclusive education and learning recovery, the framework helps to position this study within the pressing debates of our time, namely, how to close persistent learning gaps, reduce inequities, and promote SDG 4. Vygotsky’s theories on inclusive education and learning recovery. This study aims to contribute to the dialogue on addressing educational disparities and advancing sustainable development, considering Vygotsky’s ideas as adaptable and relevant to various cultural and educational settings. This framework provides a valuable lens for exploring innovative approaches to promoting equity and collaboration in education. Ultimately, this research aims to gain new insights and develop strategies for bridging learning gaps, reducing inequalities, and achieving SDG 4 globally.

3.1. Constructivist Learning Theory (Vygotsky & Cole, 1978) and Vygotsky’s Global Perspective

Constructivism asserts that learners actively construct knowledge through experiences and social interaction. The Zone of Proximal Development (ZPD) is a central concept in Vygotsky’s theory. The ZPD concept emphasises that optimal learning occurs when instruction is scaffolded beyond the learner’s ability. From this perspective, learning is a socially mediated process in which cognitive growth occurs via interaction with more knowledgeable others, whether teachers, peers, or instructional tools. This socio-cultural dimension underlines the importance of context, collaboration, and dialogue in shaping understanding.

Also central to Vygotsky’s theory is scaffolding, which involves providing temporary, adaptive instructional support that gradually withdraws as competence develops. In after-school mathematics interventions, scaffolding plays a crucial role by transferring responsibility from the teacher to the learner through guided practice, strategic questioning, and structured problem-solving. Such practices ensure that students are neither overwhelmed by complexity nor disengaged by simplicity, enabling them to build confidence, autonomy, and deeper conceptual understanding (Cho & Kim, 2020; Moschkovich, 2015). After-school mathematics programs provide an ideal setting for applying constructivist principles due to smaller group sizes, flexible pacing, and personalised attention. Teachers can diagnose specific learning gaps and tailor activities to align with each learner’s ZPD.

Another key component of Vygotsky’s theory is the Peer-Assisted Learning (PAL), a practice consistent with Vygotsky’s emphasis on social interaction, which enables students to internalise skills through collaboration with more knowledgeable persons, fostering both academic and socio-emotional growth (Tzuriel, 2021). Constructivist-oriented after-school interventions also emphasise active engagement with authentic mathematical tasks. Rather than relying on rote practice, students work on real-world problems, which strengthen their conceptual understanding and facilitate transfer to new situations. This aligns with Duan’s (2022) assertion that deep learning in mathematics requires amalgamating new knowledge into cognitive frameworks through purposeful activity.

From a global perspective, Vygotsky’s constructivist framework, particularly its focus on social mediation and the ZPD, offers a robust theoretical basis for designing after-school and remedial mathematics interventions across diverse educational contexts. Internationally, such programmes adopt diagnostic teaching, guided questioning, collaborative problem solving, and graduated withdrawal of support, reflecting the pedagogical essence of constructivism. Meta-analytic evidence has confirmed that constructivist strategies such as scaffolding, formative feedback, and peer collaboration enhance conceptual understanding, learner confidence, and self-efficacy (Stott et al., 2019).

Empirical studies further demonstrate that constructivist-based after-school programmes improve number sense, engagement, and mathematical progression across varied educational systems. Initiatives incorporating small-group, activity-based learning and game-oriented number tasks consistently report gains in problem-solving ability, motivation, and sustained interest in mathematics (Bermejo et al., 2021; Romdhon et al., 2024). The effectiveness of these interventions depends significantly on design factors such as group size, feedback mechanisms, and task authenticity (Bowie & Graven, 2024). These interactive, socially mediated tasks support inclusive and equitable pedagogy, aligning with global education priorities articulated in UNESCO’s (United Nations Educational, Scientific and Cultural Organisation) Global Education Monitoring Report and the OECD’s (Organisation for Economic Co-operation and Development) Education 2030 Framework.

However, implementing constructivist-oriented after-school programmes in resource-constrained contexts, such as Nigeria, presents unique challenges. A limited infrastructure gap, inadequate funding, high student-teacher ratios, and inconsistent teacher training often hinder effective scaffolding and sustained learner engagement. Despite these constraints, such programmes remain essential for addressing learning gaps, promoting equity, and realising the transformative goals for SDG 4 within low-resource educational systems.

Constructivist-based after-school interventions, therefore, serve as catalysts for aligning learners’ abilities with curriculum expectations by fostering active engagement and knowledge construction. They promote learner-centred approaches that build upon prior knowledge and experiences, enhancing cognitive, affective, and psychomotor outcomes (Chellammal, 2016; Mir & Jain, 2016). These environments also reduce anxiety and create low-stakes opportunities for learners to confront misconceptions without fear of formal assessment. Through personalised scaffolding and collaborative activities, students co-construct understanding, articulate reasoning, and build positive mathematical identities that endure beyond the classroom.

Furthermore, constructivist frameworks accommodate differentiated pacing, allowing struggling learners to reinforce foundational concepts and enabling advanced learners to extend their problem-solving skills. The inclusion of real-life mathematical applications increases learners’ intrinsic motivation and engagement. Empirical evidence suggests that these interventions enhance academic performance and essential non-cognitive skills, including resilience, self-efficacy, and perseverance (Merino et al., 2020; Wills & Hofmeyr, 2019). When effectively implemented, constructivist-based programmes strengthen retention, develop foundational numeracy, and nurture self-regulation skills vital for success in the 21st-century knowledge economy (Masengesho & Andala, 2024).

3.2. Critiques of Vygotsky’s Work

Although Vygotsky’s socio-constructivist perspective continues to significantly influence education, it has been subject to essential critiques. One concern is the historical and socio-political context in which his ideas were developed. Rooted in the collectivist and Marxist traditions of the Soviet Union during the 1920s and 1930s, Vygotsky’s framework may not transfer seamlessly to culturally diverse and globalised education systems (Kozulin, 2003). Recent scholarship cautions that uncritical applications can lead to cultural misalignment, underscoring the need for contextual adaptation (Chen, 2025).

A second critique addresses the conceptual status of the theory. Rather than a tightly specified framework, Vygotsky’s work is often seen as a broad perspective, leaving concepts like the ZPD open to wide interpretation (Bøttcher & Dammeyer, 2025). This openness fosters innovation and introduces ambiguity, since scaffolding and mediation practices are inconsistently defined across studies and regions. Ertugruloglu et al. (2023) provide a thematic review that demonstrates this variation, showing that scaffolding is interpreted differently in terms of purpose, delivery, and outcomes.

Third, critics argue that the framework gives limited attention to learner agency and cultural diversity. Although Vygotsky emphasised interaction with more knowledgeable others, he focused less on self-directed learning, motivation, and the role of cultural capital. Contemporary research suggests that agency, goal-setting, and socio-cultural resources have a significant influence on the effectiveness of scaffolding and mediation (Wood & Pitt, 2025). Another limitation concerns the operationalisation of constructs. Although ZPD and scaffolding are conceptually powerful, they are challenging to measure reliably. The boundaries of the ZPD and scaffolding strategies vary across studies, resulting in inconsistencies in empirical applications (Dominguez & Svihla, 2023). Kolly-Shamne (2022) further notes methodological paradoxes in defining ZPD derivatives, which complicates their rigorous use.

Finally, critics emphasise the need to reevaluate Vygotsky’s work in light of digital and postdigital learning environments. His theories predate online learning, artificial intelligence, and global digital platforms. Recent scholarship demonstrates how technology reconfigures teacher and peer roles, expands opportunities for scaffolding, and introduces new forms of mediation unforeseen by Vygotsky (Rigopouli et al., 2025). These shifts suggest that socio-constructivism must be extended to capture learning in blended, AI-enhanced, and cross-cultural contexts.

Acknowledging these critiques, this study applies Vygotsky’s work not as a static or universal model, but as a flexible and evolving lens, aligning it with contemporary challenges in equity, remediation, and inclusive pedagogy. It responds to international calls such as the Education 2030 Framework for Action (UNESCO, 2022), which emphasises adapting classical theories to meet priorities like post-COVID learning recovery and the advancement of SDG 4 (Quality Education).

3.3. Application and Justification of Vygotsky’s Perspective

In light of these critiques, this study adopts Vygotsky’s socio-constructivist perspective as a context-sensitive framework. After-school mathematics interventions provide a practical context for applying these principles, as they foster scaffolding, peer collaboration, and formative assessment aligned with learners’ developmental readiness. Such interventions support struggling students in strengthening their foundational mathematical skills, building confidence, and closing persistent learning gaps. Positioned within the global education agenda, these practices resonate with the goals of the Education 2030 Framework for Action (UNESCO, 2022) and SDG 4, which emphasise inclusivity, equitable access, and the elimination of gender disparities.

The justification for using Vygotsky’s perspective lies in its continued adaptability and empirical relevance. It aligns with pressing global issues such as educational equity, post-COVID learning recovery, and targeted remediation for low-achieving students. It also provides enduring conceptual tools, such as ZPD, scaffolding, and social mediation, which remain central in recent empirical studies when applied with contextual adaptations (Dominguez & Svihla, 2023; Rigopouli et al., 2025). This study advances the framework by clarifying how these constructs can be operationalised, particularly regarding scaffolding, formative feedback, and features such as fading, contingency, and transfer of responsibility. It reinterprets and extends socio-constructivist insights to meet the demands of equity-driven and evidence-based mathematics education today.

3.4. Appraisal of Literature Gaps

While existing studies affirm the value of constructivist approaches in after-school mathematics interventions, several critical gaps remain in the international literature. Few large-scale randomised controlled trials have examined their long-term effectiveness; gender-responsive analyses are scarce despite global concerns about equity in STEM; and limited attention has been paid to teacher training, implementation fidelity, and cost-effectiveness issues. Addressing these gaps is crucial for developing evidence-based, scalable strategies that advance SDG 4, particularly by ensuring quality education for all and eliminating disparities in learning outcomes. The present study addresses these gaps by implementing a constructivist-informed after-school intervention, assessing its impact on low-achieving students, and examining gender-based differences in outcomes. It contributes to scholarly debates on constructivist pedagogy and global policy efforts aimed at fostering equitable, high-quality mathematics education.

4. Method

4.1. Study Design

This study employed a quasi-experimental pretest-posttest control group design, structured within a 2 × 2 factorial framework, to examine the effect of after-school intervention programs on mathematics achievement among low-achieving students, with gender as a moderating variable.

4.2. Population and Sample

The target population consisted of Senior Secondary School One (SSS 1) students in a public co-educational secondary school in Oyo State, Nigeria. The researchers used a multistage sampling technique to select participants. In the first stage, we purposively selected eight co-educational schools based on the availability of qualified mathematics teachers and existing after-school programs. In the second stage, two of the eight co-educational schools were randomly selected, which formed the control and experimental groups. The next stage witnessed the purposive selection of 92 low-achieving students (47 males and 45 females) who were identified based on their previous-term mathematics scores.

The unit of randomisation was the individual student. Each identified low-achieving student was randomly assigned to either the experimental or control group to ensure internal validity and reduce selection bias. Individual-level randomisation was preferred over cluster randomisation to minimise confounding effects associated with teacher or school-level variability and to allow for more precise estimation of treatment effects within the selected schools.

The study adopted the cut-off scores based on the West African Examinations Council (WAEC) standard grading system. The WAEC, which conducts standardised examinations across the West African sub-region, defines its grading scale as follows: A1—Excellent (75–100%); B2—Very Good (70–74%); B3—Good (65–69%); C4—Credit (60–64%); C5—Credit (55–59%); C6—Credit (50–54%); D7—Pass (45–49%); D8—Pass (40–44%); and F9—Fail (0–39%). The study identified low-achieving students as those who scored within the failure range (0–39%) on the previous term’s mathematics achievement test.

The intervention spanned six weeks, comprising three weekly sessions, each lasting 45 min, for a total of 12 instructional hours. During this period, we provided the experimental group with a structured after-school mathematics instruction strategy to address core foundational skills, including number sense, algebraic thinking, geometry, and problem-solving techniques. The lessons incorporated interactive teaching methods, including manipulatives, visual aids, peer collaboration, and formative assessments to foster conceptual understanding and sustained engagement. Instruction was guided by a curriculum-aligned intervention manual developed by the researcher, ensuring uniform delivery across all participating schools. Additionally, the intervention emphasised student-centred learning, with opportunities for real-time feedback, clarification of misconceptions, and regular review exercises to reinforce previously learned concepts. We trained teachers to apply differentiated instruction techniques to accommodate the different ability levels of low-achieving students. In contrast, the control group followed the regular mathematics curriculum during standard school hours and received no additional instructional support beyond typical classroom teaching. These students did not participate in the after-school sessions and had no exposure to the targeted instructional materials or enrichment strategies used in the experimental group.

4.3. Data Collection

Data for the study were collected using the Mathematics Achievement Test (MAT), a self-developed instrument designed to assess students’ mastery of key concepts in the Senior Secondary School One (SS1) mathematics curriculum. The MAT consisted of 40 multiple-choice and structured-response items covering content areas such as algebra, geometry, number and numeration, and basic statistics. We designed the items in compliance with Bloom’s taxonomy to reflect both lower- and higher-order cognitive skills (Bloom et al., 1956). To ensure content and face validity, the draft instrument was subjected to rigorous expert appraisal by three experienced mathematics educators and two assessment specialists from Nigerian universities. These experts evaluated the test items for clarity, relevance, curriculum alignment, and cognitive demand. Based on their feedback, we revised several items and eliminated some to enhance the instrument’s appropriateness and precision.

We established the instrument’s reliability through a pilot test conducted with 30 SSS1 students from schools outside the main study but with similar characteristics. The results were analysed using Cronbach’s alpha method, which yielded a reliability coefficient of 0.82, indicating high internal consistency and suitability of the instrument for measuring mathematical achievement among the target population. During the primary data collection phase, we administered the MAT pretest and posttest under standardised conditions to the experimental and control groups. Trained research assistants administered the test to ensure uniformity in timing, instructions, and supervision. We conducted the pretest one week prior to the intervention’s commencement and administered the posttest during the week following the conclusion of the six-week instructional program. To maintain the integrity of the results, we coded and scored all scripts using a standardised marking scheme developed alongside the MAT, and two independent raters double-checked the scoring to reduce potential bias and ensure accuracy.

4.4. Data Analysis Procedure

The coded data was analysed using SPSS (Statistical Package for the Social Sciences) version 25. We used descriptive statistics, including mean and standard deviation, to summarise both groups’ pretest and posttest scores. To evaluate the effect of the intervention on mathematics achievement and the potential moderating role of gender, ANCOVA (Analysis of Covariance) was employed. This statistical technique adjusted for pre-existing differences by using pretest scores as covariates, thus improving the precision of the treatment effect estimation. The researchers also examined the interaction effects between treatment and gender to determine whether gender influenced the effectiveness of the after-school intervention.

5. Results

Data was analysed using descriptive and inferential statistics to examine the impact of the intervention on students’ mathematics performance. An Analysis of Covariance (ANCOVA) was employed to compare posttest scores between the experimental and control groups while controlling for pretest performance. Prior to conducting ANCOVA, preliminary diagnostics were performed to ensure that the data satisfied the statistical assumptions underlying the procedure (Field, 2018; Warner, 2012). Normality of the dependent variable within each group was verified using skewness and kurtosis indices (Ghasemi & Zahediasl, 2012). The assumption of linearity between the covariate (pretest scores) and the dependent variable (posttest scores) was confirmed by demonstrating consistent relationships across groups (Laerd, 2015). Homogeneity of regression slopes was tested using univariate ANOVA and found to be non-significant, indicating that the covariate outcome relationships were equivalent across treatment conditions (Maxwell et al., 2017). Levene’s test confirmed the homogeneity of variances, while the study design guaranteed independence of observations, as each participant belonged to only one group (Warner, 2012). The non-significant results from these diagnostic checks confirmed that all ANCOVA assumptions were satisfied, thereby ensuring the validity of the results.

Table 1. Demographic Variables.

Variables	Groups	Number	Mean	SD
Gender	Male	47 (51.09%)	1.98	1.01
	Female	45 (48.91%)	1.84	0.99
Treatment	Experiment	50 (54.35%)	1.52	0.51
	Control	42 (45.65%)	1.45	0.50

presents the distribution of participants based on gender and treatment groups, along with their corresponding mean scores and standard deviations. Mathematically, the mean is

$$\overline{X}={\displaystyle \frac{{\sum }_{k=1}^{n_{ij}}{X}_{ijk}}{n_{ij}}}$$

Represent the mean score of group $j$ under variable $i$, where

$i$ indexes the demographic variables (e.g., Gender, Treatment);

$j$ indexes the group within the variable (e.g., Male, Female);

$n_{ij}$ is the number of participants in group $j$;

$X_{ijk}$ is the $K$ observation in that group.

The standard deviation (SD) for each group is

$$SD=\sqrt{{\displaystyle \frac{{\sum }_{K=1}^{n_{ij}}{\left(X_{ijk}-{\overline{X}}_{ij}\right)}^2}{n_{ij}-1}}}$$

A total of 92 low-achieving students participated in the study. In terms of gender, the sample comprised 47 male students (51.09%) and 45 female students (48.91%). The mean score for male participants was 1.98 (SD = 1.01), slightly higher than that of female participants, whose mean score was 1.84 (SD = 0.99). Although the differences in mean scores between genders are small, this variation may reflect minor performance differences before the intervention. Regarding treatment allocation, 50 students (54.35%) were assigned to the experimental group, while 42 students (45.65%) constituted the control group. The experimental group recorded a mean score of 1.52 (SD = 0.51), marginally higher than the control group’s mean score of 1.45 (SD = 0.50). The relatively low standard deviations in both groups suggest a narrow spread of scores, indicating that the participants’ performance levels within each group were homogeneous at baseline.

To determine the effect of the after-school mathematics intervention on students’ performance, the researchers conducted an Analysis of Covariance (ANCOVA), using the posttest mathematics scores as the dependent variable, treatment and gender as the independent variables, and pretest scores as the covariate. The analysis also tested the interaction effects between treatment and gender.

5.1. Corrected Model

Table 2. Analysis of Covariance (ANCOVA) of Students’ Achievement in Mathematics by Treatment and Gender.

Source	Type III SS	df	Mean Square	F	Sig.	Partial Eta Squared
Corrected Model	1270.979	4	317.745	31.136	0.000	0.589
Intercept	614.046	1	614.046	60.170	0.000	0.409
Pretest Score	161.218	1	161.218	15.798	0.000	0.154
Gender	12.238	1	12.238	1.199	0.277	0.014
Treatment	1172.395	1	1172.395	114.883	0.000	0.569
Gender × Treatment	2.127	1	2.127	0.208	0.649	0.002
Error	887.847	87	10.205
Total	24,138.000	92
Corrected Total	2158.826	91
R2 = 0.589
(Adjusted R2 = 0.570)

Note. df = degree of freedom.

presents the ANCOVA results for the corrected model, incorporating pretest score, gender, treatment, and the gender–treatment interaction. The model explains a significant proportion of variance in posttest mathematics achievement, F(4, 87) = 31.136, p < 0.001, with R² = 0.589, indicating that 58.9% of the variance is attributable to the covariate and independent variables. The adjusted R² = 0.570 confirms the model’s robustness, accounting for potential overestimation due to sample size, and supports the substantial explanatory power of the predictors in students’ posttest performance.

5.2. Effect of Pretest Score (Covariate)

The covariate (pretest score) significantly influenced posttest performance, F(1, 87) = 15.798, p < 0.001, with a moderate effect size (partial η² = 0.154). This confirms that baseline academic ability influenced outcomes, justifying its inclusion in the model to control for initial differences.

5.3. Effect of Treatment

The analysis revealed a statistically significant main effect of treatment, F(1, 87) = 114.883, p < 0.001, with a large effect size (partial η² = 0.569). This result indicates that the structured after-school mathematics intervention had a strong impact on students’ mathematics achievement. Students in the experimental group outperformed their peers in the control group, who received only regular classroom instruction. This finding negates H₀₁, meaning that after-school intervention does not significantly improve mathematics performance among low-achieving students.

5.4. Effect of Gender

The main effect of gender was not statistically significant, F(1, 87) = 1.199, p = 0.277, partial η² = 0.014. This suggests that gender did not significantly influence the posttest mathematics performance of students. Although female students had a slightly higher mean score, the difference was not statistically meaningful. This result supports H₀₂, which predicted no statistically significant main effect of gender on the mathematics achievement of low-achieving students.

5.5. Interaction Effect of Gender and Treatment

The interaction between gender and treatment was also not statistically significant, F(1, 87) = 0.208, p = 0.649, partial η² = 0.002. This indicates that the effectiveness of the after-school intervention was consistent across gender. Thus, H₀₃ was retained, confirming that there is no statistically significant interaction effect between the teaching method and gender on the mathematics achievement of low-achieving students.

6. Discussion of Findings

The present study adds fresh insight into the evidence based on after-school mathematics interventions. It has been shown that such programmes improve performance among low-achieving junior secondary students and that their impact is transformative, extending beyond immediate academic gains. The intervention demonstrated that structured support outside regular instructional hours can reconfigure how students engage with mathematics, fostering persistence, confidence, and a deeper conceptual understanding. The shift from traditional classroom teaching to learner-centered scaffolding represents a significant transformation in educational practices. This approach emphasises collaboration between teachers and students, allowing for a more personalised and engaging learning experience. Students can consolidate their knowledge and alter their learning trajectories by integrating scaffolding techniques. This finding supports earlier work that highlights the importance of formative assessment and targeted support (Moyosore, 2015). Still, it extends the conversation by illustrating how interventions can function as equity-driven strategies to reduce mathematics deficits and systematically promote inclusive education on a large scale.

While the intervention produced strong effects, it is essential to acknowledge that alternative explanations, such as increased attention or motivation associated with the Hawthorne effect, may have contributed to the observed gains to some extent. Nonetheless, the consistency of improvement across schools and alignment with previous studies suggest that the positive outcomes largely reflect the efficacy of the structured constructivist approach rather than temporary behavioural shifts. These results indicate that a structured constructivist approach can successfully address mathematics deficits and promote inclusive education on a broader scale.

A novel dimension of this study is its examination of gender effects within constructivist-inspired interventions. The absence of significant gender differences challenges enduring assumptions about males’ advantage in mathematics and aligns with contemporary findings that disparities often diminish in supportive learning environments (Babatimehin et al., 2025; Cheryan et al., 2017; Ibrahim & Shuaibu, 2024; Lesperance et al., 2022; Maskos et al., 2025; Nnajiofor, 2025; Yoo, 2018; Zhu et al., 2018). This result underscores that performance gaps are less likely to reflect innate ability and more strongly shaped by contextual variables such as access to remedial support, the nature of pedagogy, and socio-cultural expectations. By reinforcing that well-designed after-school interventions create conditions where both male and female learners benefit equally, the study highlights the potential of inclusive instructional models to neutralise historical disparities in STEM outcomes (O. A. G. Opesemowo, 2025a, 2025b).

From a policy perspective, the study contributes to ongoing international debates by situating after-school mathematics programmes within the Education 2030 Framework for Action (UNESCO, 2022). These findings demonstrate that such interventions are not merely remedial add-ons but integral mechanisms for promoting equitable, high-quality education, particularly in resource-constrained settings. Evidence from this study, together with related scholarship, confirms that when programmes combine scaffolding, feedback, and structured practice, they do more than bridge performance gaps; rather, they reorient learners’ trajectories and strengthen their long-term capacity to succeed (Betts et al., 2024; Stott et al., 2019; Yazdani, 2025). The moderate-to-large effect sizes observed further suggest that interventions are robust and can significantly supplement prior knowledge while reshaping outcomes. Consistent with Winarno and Al Azies (2024), this study emphasises the importance of integrating after-school interventions into education systems, complemented by personalised learning plans and continuous formative assessment. Doing so provides empirical grounding for policy and practice, ensuring no learner is left behind in pursuing SDG 4.

7. Conclusions

This study examined the effectiveness of after-school intervention programs in enhancing mathematics achievement among low-achieving junior secondary school students in Oyo State, Nigeria, with a focus on gender differences. The findings reveal that structured after-school instruction significantly enhanced students’ mathematics performance, indicating that such interventions are viable strategies for addressing persistent learning deficits. While we reported no statistically significant gender differences, the slight performance advantage observed among female students suggests that the intervention benefited both genders equitably. Moreover, the absence of significant interaction effects between gender and treatment reinforces the argument that well-structured pedagogical strategies can close achievement gaps and support inclusive education goals. These findings contribute to the growing body of evidence supporting extended learning time and targeted instructional support as active tools for improving learning outcomes in mathematics, especially for low-achieving students.

8. Recommendations

Based on the study’s findings, several recommendations are proffered. Education authorities should institutionalise after-school mathematics programs in schools with high proportions of low-achieving students, integrating them into school improvement frameworks. Teachers require training in evidence-based strategies, such as scaffolding, formative assessment, and differentiated instruction, with a focus on gender-inclusive approaches to ensure equitable participation and engagement. Continuous professional development should strengthen teachers’ capacity for learner engagement and emotional support. Robust monitoring and evaluation systems must track program impact, enabling data-driven improvements. Finally, parental and community involvement should be encouraged to boost student motivation, attendance, and accountability, thereby enhancing the overall effectiveness of interventions.

9. Significant Contribution to Knowledge

A significant contribution is knowledge concerning after-school mathematics education interventions and socio-constructivist pedagogy. First, it extends the application of Vygotsky’s socio-constructivist perspective by reinterpreting it as a flexible and evolving lens rather than a fixed framework. In contrast to much of the literature that either uncritically applies Vygotsky’s ideas or dismisses them as historically situated, this study explicitly addresses critiques of universality, measurement, learner agency, and cultural context. As a result, it provides a theoretically grounded yet contextually adaptive model for designing mathematics interventions in diverse and under-resourced educational settings.

Second, the study proposes empirical evidence on the effectiveness of structured after-school mathematics interventions for low-achieving junior secondary students. Demonstrating significant improvements in learners’ mathematics achievement, self-confidence, and engagement contributes to the growing international perception that extended learning opportunities are essential for tackling persistent achievement gaps. The study shows that such interventions can neutralise traditional gender disparities, thereby adding to the literature on gender equity in STEM education.

Third, the research contributes to the policy–practice interface by situating after-school interventions within the global agenda of the Education 2030 Framework for Action and SDG 4.

This study offers actionable insights that can inform policymakers, educators, and curriculum designers, demonstrating how constructivist after-school programs align with international demands for equity, remediation, and inclusion. The findings are particularly pertinent in the post-COVID era, where learning recovery and remediation remain urgent global concerns.

Finally, the study advances methodological knowledge by addressing long-standing operationalisation challenges in Vygotskian constructs. Clarifying scaffolding processes, features explicitly such as fading, contingency, and transfer of responsibility, provides a more robust approach for evaluating and replicating socio-constructivist interventions in empirical research. These contributions establish the study as a meaningful advancement in mathematics education theory, practice, and policy. It not only validates after-school interventions as a strategy for improving outcomes among low-achieving students but also reframes Vygotsky’s socio-constructivism in ways that are globally relevant, equity-driven, and aligned with the imperatives of sustainable development.

10. Limitations and Directions for Future Study

This study has several limitations. It was restricted to public co-educational secondary schools in Oyo State, limiting the generalisability of findings to other settings. The quasi-experimental design lacked complete randomisation, which may have introduced bias, while the six-week duration may not adequately reflect long-term learning outcomes. Focusing solely on mathematics excluded insights from other subject areas where similar interventions could be explored. Additionally, contextual factors such as home environment and access to learning resources were not examined, which may have influenced students’ engagement and performance. Implementation fidelity and teacher variability also present notable constraints. Differences in teachers’ instructional delivery, adherence to the intervention protocol, and pedagogical enthusiasm may have affected the consistency of treatment across schools. Future research should therefore incorporate continuous monitoring, professional support, and structured training to enhance fidelity in implementation. Subsequent studies should employ fully randomised controlled designs, extend intervention periods, and include diverse schools and subjects to improve external validity. Moreover, adopting longitudinal or mixed-methods designs would provide richer insights into how sustained after-school participation influences learners’ behavioural and attitudinal shifts over time. Such designs can integrate quantitative achievement measures with qualitative accounts of motivation, self-efficacy, and engagement, offering a holistic understanding of programme impact. Examining contextual variables, classroom interactions, and fidelity mechanisms remains essential for enhancing the reliability, scalability, and long-term effectiveness of future constructivist-based educational interventions.