Technology optimism predicts project readiness among Ghanaian postgraduate students in single-university survey

Technology optimism was the only statistically significant predictor of readiness to implement information technology and digitalization projects in a quantitative survey of 72 first-year master’s students at a public university in Ghana. The study, published on 10 September 2026 in Discover Education, found that students’ positive beliefs about technology were associated with greater perceived project readiness, while innovativeness, discomfort and insecurity did not show significant direct relationships with readiness in the fitted model. The research used the Technology Readiness Index framework, which distinguishes two enabling dimensions, optimism and innovativeness, from two inhibiting dimensions, discomfort and insecurity.

Optimism captures beliefs that technology provides benefits such as control, flexibility and efficiency. Innovativeness describes a tendency to experiment with new technologies; discomfort reflects feeling overwhelmed or challenged; and insecurity includes doubts about technology, troubleshooting unfamiliar systems and reliance on others. Student readiness was defined as perceived preparedness, confidence and capability to complete IT or digitalization project tasks from beginning to end within an academic assessment framework.

The researchers distinguished this measure from general digital literacy and technology acceptance. Items for the four Technology Readiness Index dimensions were adapted from the TRI 2.0 scale and contextualized for academic projects, while readiness items were adapted from project-readiness and self-efficacy literature and reviewed for content validity. The target population consisted of 90 first-year Master of Science students enrolled in the “Implementing IT/digitalization Projects” course at University X in Accra.

Researchers used simple random sampling and calculated a minimum sample of 71 based on a 5% margin of error, a 95% confidence level and a 70% sample proportion informed by a pilot of 10 students. Seventy-two students responded. The questionnaire contained demographic questions and 20 items across five constructs, each rated on a five-point Likert scale from strongly disagree to strongly agree.

Participation was voluntary, and three information-technology education experts assessed the adapted items for content validity before data collection. The investigators used partial least-squares structural equation modeling in SmartPLS. The measurement model supported the reliability, convergent validity and discriminant validity of the constructs: Cronbach’s alpha ranged from 0.713 to 0.945, composite reliability ranged from 0.822 to 0.961, and average variance extracted values exceeded 0.5.

Heterotrait–monotrait ratios were below one. Two discomfort indicators had loadings below 0.708 but were retained because each loaded more strongly on its parent construct and did not cross-load elsewhere. Of the four tested paths, only optimism significantly and positively predicted perceived student readiness, with a standardized coefficient of 0.625 and p below 0.001.

Its effect size was large at 0.72, and its 95% bias-corrected bootstrap confidence interval extended from 0.398 to 0.812. The remaining paths were not statistically significant: innovativeness had a positive coefficient of 0.120, while discomfort and insecurity had negative coefficients of −0.021 and −0.163. Their 95% bias-corrected bootstrap confidence intervals included zero, and their effect sizes ranged from 0.00 to 0.02.

The model explained a moderate share of the variance in digitalization readiness, with an R² of 0.556. The reported Q² value was classified as high, while PLSpredict yielded a Q²_predict of 0.517; all indicators had lower prediction errors than their corresponding naive benchmarks. Additional diagnostics used 5,000 bootstrap subsamples.

Variance inflation factors were below 2.5, and the standardized root mean square residual was 0.068, below the study’s stated acceptable threshold of 0.08. The respondent group was predominantly male: about 80% were men, all were over 25, and close to 70% reported experience with IT or digitalization project management. That experience included work as IT project managers, programme managers, coordinators, managers, team leads and technical team members.

These characteristics describe the study sample, but the survey did not directly test whether they altered students’ readiness ratings or the Technology Readiness Index scores. The findings are bounded by the study’s design. Data came from one course at one university, limiting generalization to other institutions, programmes or stages of postgraduate study.

Readiness was measured through questionnaire responses rather than observed performance in completed projects, so the results concern perceived preparedness and modeled associations, not demonstrated project outcomes. The survey does not establish that changing students’ attitudes would improve project performance, and the non-significant results for the other three dimensions do not show that they are irrelevant in every educational or technology-use context.

Subject of Research: Technology readiness among first-year Ghanaian master’s students undertaking IT and digitalization projects

Article Title: An empirical analysis of students’ readiness for implementing it and digitalization projects among information systems graduate students in a public university in Ghana

Article References: Koi-Akrofi, G. Y., Koi-Akrofi, J., Nketia, I. K., & Addison, M. D. (2026). An empirical analysis of students’ readiness for implementing it and digitalization projects among information systems graduate students in a public university in Ghana. Discover Education, 5(1), Article 895. https://doi.org/10.1007/s44217-026-02047-y

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02047-y

Keywords: Technology Readiness Index, student readiness, technology optimism, digitalization projects, postgraduate education, Ghana, PLS-SEM, higher education, empirical, analysis, students, readiness