The integration of information and communication technology (ICT) into teaching and learning is now a central expectation of contemporary education systems. Nigeria's national information-technology policy envisaged technology use across all levels of education [1]. Realising that ambition, however, requires more than hardware provision: adoption is also shaped by users' capabilities, beliefs, access to support, and the conditions in which technology is introduced [2]. Student-teachers are therefore a consequential group because the knowledge and dispositions developed during initial teacher preparation can influence whether technology is later used purposefully in classroom practice.

Business Education occupies a strategic position within this agenda because it prepares graduates for digitally mediated office, accounting, marketing, and entrepreneurial work. The technology acceptance model (TAM) identifies attitude as a proximal determinant of behavioural intention, while external variables influence acceptance through perceived usefulness and ease of use [3]. In the present study, digital competence refers to participants' self-reported knowledge and skill; it is related to, but not equivalent to, computer self-efficacy [4]. Attitude refers to an evaluative disposition towards an object or behaviour [5]. Educational extensions of TAM similarly show that capability-related beliefs and perceptions can shape prospective teachers' willingness to use technology [6], [7].

Research in Nigeria has documented student-teachers' competence and attitudes, but studies often report these constructs separately or treat attitude as a single undifferentiated outcome. Evidence specific to Business Education student-teachers in colleges of education in South-West Nigeria remains limited, and it is unclear whether perceived competence contributes uniquely to attitude towards ICT adoption once a broader ICT attitude is considered. This study addresses that gap by estimating construct levels, bivariate associations, and the joint prediction of adoption attitude by self-reported competence and general ICT attitude. Its contribution is contextual and explanatory rather than causal: the analysis clarifies the relative strength of the observed relationships without equating attitude with actual technology use.

As shown in Table 2, digital competence recorded a mean of 2.67 against a five-point midpoint of 3.00, indicating a moderate but slightly below-midpoint level. Attitude towards adoption (M = 2.57) and general attitude (M = 2.61) both fell marginally above the four-point midpoint of 2.50, indicating moderately positive dispositions.

To address the joint prediction, attitude towards adoption was regressed on competence and general attitude. The model was significant, F(2, 146) = 41.21, p < .001, and accounted for 36.1% of the variance (adjusted R² = .35). As shown in Table 4, general attitude was a strong unique predictor (β = .57, p < .001), whereas competence was not (β = .11, p = .104) once attitude was controlled; H04 was rejected on the strength of the overall model.

Three findings are central. First, all three construct means were close to their scale midpoints: self-reported competence was slightly below its midpoint, and both attitude scores were only slightly above theirs. This pattern is consistent with Nigerian evidence that favourable views of ICT may coexist with limited competence, access, or use [13], [16]. The midpoint comparisons are descriptive rather than criterion-referenced, so they cannot establish whether participants met a professionally meaningful standard. Performance-based benchmarks would be needed for that purpose.

Second, digital competence showed only small positive correlations with the two attitude measures. The direction of these relationships is compatible with TAM and social cognitive accounts linking capability-related beliefs with evaluative perceptions [3], [8], and it accords with earlier evidence connecting competence or self-efficacy to prospective technology integration [12], [14]. Their small magnitude, however, indicates that perceived competence explained little of the variation in attitude when considered alone. This should not be taken to mean that competence is unimportant. The 11-item scale assessed perceived knowledge and did not capture the wider pedagogical, professional, ethical, and contextual dimensions included in contemporary teacher digital-competence frameworks [19].

Third, the strongest relationship was between general ICT attitude and attitude towards ICT adoption. General attitude remained strongly associated with the outcome in the regression model, while digital competence did not make a statistically significant unique contribution. This result is theoretically plausible because a broad evaluative disposition may be closer to adoption attitude than perceived skill. It also warrants caution: both variables were attitudinal self-reports administered in the same questionnaire, so their association may partly reflect overlapping content and common-method variance [22]. The model consequently supports covariation between related attitudes; it does not establish mediation, causal ordering, behavioural intention, or actual ICT use.

The practical implication is not to replace competence development with attitude-focused activities, but to design experiences in which the two reinforce one another. Business Education programmes could integrate spreadsheet-based accounting, digital office workflows, online marketing, and entrepreneurship applications into authentic coursework and practicum tasks. Guided low-stakes practice, feedback, reflection on pedagogical value, and visible modelling by teacher educators may help students connect capability with purposeful use. This approach is consistent with evidence that effective preparation integrates technology, pedagogy, practicum, collaboration, and institutional support rather than relying on isolated skills courses [20], [21]. Adequate access, facilitation, and organisational conditions remain necessary because positive dispositions alone do not remove contextual barriers [2], [15].

Several limitations constrain the interpretation and generalisability of the findings. The cross-sectional design precludes temporal and causal inference, all focal variables were collected through one questionnaire, and no observed or logged measure of ICT use was included. The two attitude scales may overlap conceptually, yet no measurement model was reported to establish discriminant validity. The sample was modest and unevenly distributed across programme options, while the number of participating institutions, sampling frame, recruitment procedure, and response rate were not specified. These omissions make representativeness difficult to assess. Future research should validate the measurement structure, combine self-report with performance-based competence and behavioural indicators, recruit stratified multi-institutional samples, and use longitudinal, experimental, or structural models when testing temporal or mediational processes [22].

This study found small positive associations between digital competence and two ICT-attitude measures. General attitude was strongly associated with attitude towards adoption and was the only significant unique predictor in the two-predictor regression model. Because the two attitude scales may share conceptual and measurement content, and because the design was cross-sectional, the results do not show that attitude causes adoption, that competence operates through attitude, or that participants actually use ICT in teaching. Business Education programmes should combine authentic, discipline-relevant digital competence development with teacher modelling, guided practice, reflection, and institutional support. Future research should validate the measurement structure, include performance and behavioural indicators, recruit more representative multi-institutional samples, and use longitudinal or experimental designs to examine temporal and causal processes.

Author Contributions

Festus Oladimeji Olafare: Conceptualization, Methodology, Investigation, Formal Analysis, Data Curation, Writing – Original Draft, Writing – Review & Editing, Visualization, and Project Administration. As the sole author, Festus Oladimeji Olafare conceived the study, designed the methodology, collected and analysed the data, and prepared and approved the final manuscript.

Acknowledgments

The author wishes to thank the management and staff of the participating colleges of education for their cooperation during data collection.

Ethics Approval

The manuscript does not report a formal ethics committee approval, exemption determination, or protocol reference.

Informed Consent

Written informed consent was obtained from all participants before data collection.

Consent for Publication

Not applicable. The article contains no identifiable individual participant information.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request, subject to applicable ethical and confidentiality restrictions.

Competing Interests

The author declares no competing interests.

Generative AI and AI-Assisted Technologies Statement

During manuscript preparation and revision in 2026, the author used Claude (Anthropic) and ChatGPT (OpenAI) for language editing, structural refinement, and reference-format checking. These tools were not used to generate or modify the study data, statistical analyses, reported results, or conclusions. The author independently reviewed and revised all AI-assisted output, verified the references and substantive content, and accepts full responsibility for the accuracy, originality, analysis, and conclusions of the article.