Students’ academic programme choices are shaped by a dynamic mix of intrinsic and extrinsic motivations, including personal interest, perceived utility and social expectations (Bergann et al., 2025). Zaini et al. (2021) highlight intrinsic factors such as intellectual curiosity and enjoyment, while extrinsic drivers include career prospects, financial incentives and social prestige. Mwantimwa (2021) adds that alignment between programme choice and personal aspirations enhances academic satisfaction and persistence. These findings underscore the need to recognise motivational diversity when designing institutional support strategies.

Gender significantly shapes programme selection, with global data showing a predominance of female students in disciplines like social sciences and humanities (UNESCO, 2022). Geographic location also plays a role, especially for students from rural or underserved areas. Sadjail et al. (2022) found that such students often choose programmes based on proximity, affordability and job market outcomes rather than disciplinary interest. These patterns reflect ongoing structural inequalities in access to higher education. Collectively, the studies emphasise that programme choice is a socially embedded decision influenced by intersecting demographic factors. Understanding these dynamics is vital for crafting equitable policies and targeted institutional support (Tavares et al., 2022).

Genderism, the systemic privileging of one gender over others, continues to shape access, experiences and outcomes in higher education (Farmer et al., 2019). Despite equity policies, structural biases persist in programme offerings, faculty representation and career pathways (Griffin, 2019). Intersectionality, as conceptualised by Crenshaw (1989), offers a lens to examine how overlapping identities compound educational disadvantage. Recent scholarship extends this framework to higher education contexts, highlighting how institutional policies and social class dynamics reproduce inequalities (Beeckmans et al., 2023; Fernandez et al., 2024). In African contexts, gender disparities are intensified by socio-cultural expectations and institutional constraints. Mokoena and Dlamini (2023) note that female STEM students face implicit bias, limited mentorship and exclusionary cultures, while male students in female-dominated fields encounter stigma and identity conflict (Tshabalala, 2024).

Intersectional analysis shows that gender alone cannot explain disparities in programme selection or success. Nyarko and Boateng (2022) found that rural, low-income female students face barriers like limited resources and early marriage expectations. Institutional factors such as the language of instruction, campus safety and availability of financial aid disproportionately affect marginalised groups. Higher education institutions often struggle to address these layered inequities. Gender mainstreaming efforts lack intersectional sensitivity and overlook how gender, class and ethnicity shape student experiences (Fernandez et al., 2024). As Chikoko (2025) argues, treating gender as a monolith risks missing the nuanced realities of students. Equity frameworks must integrate intersectionality into curriculum, support services and institutional policy.

Effective academic advising is essential for informed programme selection. Karp et al. (2021) advocate for models that combine career exploration, motivational interviewing and personalised support. Yet, Mowreader (2024) notes that only 20% of students receive adequate education-to-career guidance, resulting in misalignment between academic paths and career goals. Lombard (2020) highlights a transition programme like JuniorTukkie, which supports students moving from secondary to tertiary education. These initiatives improve retention and satisfaction, particularly for first-generation and under-resourced students, by fostering inclusive environments and expanding academic support (Bassett, 2023). These findings stress the need for proactive, equity-driven institutional support.

Despite global insights into advising and programme selection, African institutions remain underrepresented in empirical research. Anyichie (2024) calls for localised studies that reflect regional labour markets, particularly the demand for specific skills, employment opportunities and wage prospects, alongside cultural dynamics and institutional realities. Without such evidence, policy interventions risk misalignment with student needs and institutional capacities.

The revised questionnaire preserved essential motivational dimensions originally validated by Ma et al. (2021), including academic ease, career relevance and social influence, each of which demonstrated robust internal consistency (Cronbach’s α > 0.7) in prior applications. Survey items were mapped onto established theoretical frameworks to ensure construct validity, notably the integrative model proposed by Labib et al. (2021), which synthesises elements from EVT, SDT and achievement goal theory.

A stratified random sampling technique was used to ensure equitable representation and valid comparisons, with gender as the primary stratification variable (Creswell, 2014). This method minimised bias and supported balanced subgroup analysis. The target population included undergraduate students enrolled in the Bachelor of Commerce and Economics programmes at the NUL during the 2024–2025 academic year. According to official records, 159 students were registered across these programmes. This cohort was ideal, having recently completed their major selection, offering a timely opportunity to examine motivational factors and gender-based differences in programme choice. To ensure equitable representation and valid comparisons, a stratified random sampling technique was used, with gender as the primary stratification variable (Creswell, 2014).

A structured, self-administered questionnaire was used to assess students’ motivations for academic programme selection. Grounded in SDT (Deci & Ryan, 1985) and EVT (Eccles & Wigfield, 2002), the instrument examined individual agency, perceived value and contextual influences. Items were adapted from validated scales to ensure cultural and linguistic relevance. Key constructs included intellectual curiosity, academic fit, financial expectations, job prospects, parental and peer influence, social prestige and institutional reputation (Ma et al., 2021). Responses were captured on a 5-point Likert scale, supporting descriptive, inferential and factor analyses. Content validity was ensured through expert review and a pilot test with eight students. Participation was voluntary and anonymous, with confidentiality safeguards to reduce bias. The final dataset enabled robust analysis of motivational patterns, demographics and programme choices, informing institutional strategies on guidance, gender equity and development.

Quantitative data from 159 respondents were analysed by using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp, 2021). The analysis included exploratory factor analysis, reliability testing, Pearson correlation and independent samples t-tests to examine motivational dimensions and gender-based differences in programme selection.

Factor analysis was conducted by using principal component extraction with Varimax rotation to identify latent constructs. Factors with eigenvalues greater than 1.0 and item loadings of ≥ 0.40 were retained. Reliability was assessed by using Cronbach’s alpha, with α ≥ 0.70 considered acceptable (Nunnally & Bernstein, 1994). For example, the career-oriented motivation factor comprising job prospects, financial expectations and career planning yielded α = 0.82.

Pearson correlations explored relationships between motivational factors and programme choices, accounting for gender and socioeconomic background. Independent samples t-tests assessed gender differences across seven motivational constructs. Chi-square analysis examined associations between gender and programme choice. Descriptive statistics (means, standard deviations and frequencies) were used to summarise demographic variables and item-level responses, supporting subgroup comparisons and contextual interpretation. These methodological choices were selected to align with the study’s objectives and ensure validity, consistent with established standards in educational research (Field, 2018; Hair et al., 2022).

While the study offers valuable insights into gender-based enrolment motivations, several limitations affect its generalisability. The sample size of 159, although adequate for exploratory analysis, limits statistical power and broader representation (Turhan, 2020). Reliance on self-reported data introduces potential biases, including social desirability and subjective interpretation (Roeygens, 2023; Schunk et al., 2008), common in motivation research in which internal states are difficult to measure objectively. The study focused solely on B. Com and economics students at one institution, excluding other disciplines and geographic contexts. While necessary for feasibility, this limits transferability to wider academic settings (Coker, 2022).

Despite these constraints, the study provides a strong foundation for future research using larger samples, multi-institutional comparisons and longitudinal designs to track motivational shifts over time. Future studies could also incorporate mixed-method approaches to enrich quantitative findings with contextual insights (Sammons & Davis, 2017) and explore intersectional factors such as socioeconomic status or cultural expectations that may shape gendered enrolment decisions (Unterhalter et al., 2020). Such expansions would enhance both the depth and the applicability of motivational research across diverse academic and cultural settings.

Ethical clearance to conduct this study was obtained from the Faculty of Health Sciences Ethics Review Board at the NUL (Ref. No. NUL/STA/2025/02). Participation was voluntary and anonymous.

Table 1 presents a summary of key demographic and academic variables, including sex, age group and programme enrolment to contextualise the study sample.

Table 1 presents the demographic and academic profiles of participants. The sample shows a gender imbalance (64.2% women, 35.8% men), possibly reflecting institutional enrolment patterns. Most respondents (74.2%) are aged 18–23 years, consistent with typical undergraduate cohorts, while mature-age students (24+) represent only 8.8%. Programme-wise, 61% are enrolled in B. Com and 39% in economics, suggesting a preference or institutional emphasis on the B. Com stream.

Table 2 summarises the exploratory factor analysis results, including factor loadings, eigenvalues and explained variance, supporting construct validity and interpretation of motivational dimensions.

Exploratory factor analysis identified seven motivational dimensions, ranging from institutional support to prestige, accounting for 54.1% of the total variance. These findings underscore a multifaceted decision-making process shaped by academic, social and personal factors, offering a foundation for gender-based analysis and strategic institutional alignment.

Table 3 presents the Cronbach’s alpha values for each motivational factor, indicating the internal consistency of the constructs identified.

Reliability analysis confirmed strong internal consistency for Institutional Support, Academic Simplicity, Career Utility and Social Endorsement (α > 0.70), supporting their statistical and conceptual validity in explaining programme selection. In contrast, programme popularity, Intrinsic Interest and Prestige showed weaker reliability (α < 0.70), indicating potential issues with item clarity or construct definition. While core factors are dependable, less stable dimensions require refinement to improve measurement and theoretical alignment in future research.

Table 4 summarises the mean scores and standard deviations for each motivational factor, highlighting their relative prominence in students’ programme selection.

Table 4 shows minimal gender differences across most motivational factors, with no significant variation (p > 0.05) in institutional support, academic simplicity, career utility, social endorsement, programme popularity and prestige. This observation suggests broadly similar motivational orientations between male and female students. However, a significant difference was found for Intrinsic Interest and Future Relevance (p = 0.016), with male students reporting higher mean scores. This finding implies that men may prioritise personal engagement and long-term utility more strongly. The findings highlight the value of gender-sensitive advising, particularly strategies that enhance programme relevance and engagement for female students. Building on these motivational findings, this study examined the association between gender and programme choice, using a chi-square test of independence (Table 5).

Table 5 presents the chi-square test results assessing the association between gender and programme selection. The analysis explores whether male and female students differ significantly in their enrolment patterns for the Bachelor of Commerce and Economics programme.

The chi-square test revealed no statistically significant association between gender and programme choice (χ²[1, N = 200] = 0.884, p = 0.347\chi^2 [1, N = 200] = 0.884, p = 0.347), indicating a comparable distribution of male and female students across the Bachelor of Commerce and Economics programmes. Although female students accounted for a larger proportion of enrolment, this difference was not statistically significant. These results suggest that gender does not exert a decisive influence on programme selection, underscoring the importance of examining individual motivational factors rather than relying on gender-based assumptions.

This study offers a nuanced perspective on gender dynamics in motivational orientations and programme selection within the Faculty of Social Sciences at NUL. While most motivational constructs showed no statistically significant gender differences, Intrinsic Interest and Future Utility emerged as exceptions, with male students reporting significantly higher scores. This result indicates that motivations linked to personal enjoyment, intellectual engagement and long-term career relevance may resonate more strongly with male students.

These findings partially align with Naz et al. (2020), who observed that male students often prioritise extrinsic outcomes such as career advancement and societal recognition, whereas female students are more influenced by relational and intrinsic goals. Watt and Eccles (2008) and Stolk et al. (2021) similarly argue that gendered motivational schemas persist: men tend to associate academic choices with prestige and achievement, while women emphasise personal meaning and social contribution.

In contrast, Turhan’s (2020) meta-analysis reported minimal gender differences across motivational sub-dimensions, underscoring the importance of situating motivational patterns within specific institutional and cultural contexts, including historical perspectives from Lesotho’s higher education landscape (Ntimo-Makara, 2007).

Although chi-square analysis revealed no statistically significant association between gender and programme choice, the observed motivational differences, particularly in intrinsic interest, suggest that gendered patterns may still influence how students engage with academic pathways. This suggestion supports the EVT (Eccles & Wigfield, 2002), which highlights the role of subjective task values, such as attainment and utility, in academic decision-making and their variation across gender lines.

The study’s findings resonate with Southern African literature on educational decision-making. Blake and Mestry (2021) highlight how parental income, education and language shape school choice in Gauteng, reflecting the socioeconomic drivers behind strategic academic engagement, paralleling our findings on career utility and instructional quality. Similarly, Mhlongo and O’Neill (2013) emphasise the role of family expectations and emotional support in programme selection at University of KwaZulu-Natal (UKZN), reinforcing the influence of social endorsement and peer affiliation identified in our factor analysis. Further, Singaram and Sommerville (2018) demonstrate that race, language and financial support affect academic performance and motivation, echoing the observation that intrinsic interest and future relevance, particularly among male students, are shaped by broader demographic contexts. These regional insights affirm that motivational constructs are not isolated psychological traits but are embedded within structural and relational environments (Howard et al., 2020).

Based on the study’s findings, the following strategies are proposed to enhance programme selection support and address motivational disparities within the Faculty of Social Sciences: