Cultivating an Engaged Workforce: The Interplay of Mentorship, Technical Skill Development, and Learning Flexibility

Abstract

Employee engagement remains one of the most persistent challenges facing modern organizations: industry surveys consistently report that less than a third of employees are actively engaged in their work. This study examined the joint influence of three organizational levers on employee engagement — mentorship quality, technical skill development, and learning flexibility (i.e., the autonomy employees are given over when, how, and what they learn) — within a first-stage moderated mediation framework. A cross-sectional survey was administered to 250 full-time employees drawn, via stratified convenience sampling, from five
functional departments of a mid-sized organization (68% response rate among 368 employees invited). The proposed model was estimated using partial least squares structural equation modeling (PLS-SEM) in SmartPLS 4, with 5,000 bootstrap resamples used to generate bias corrected and accelerated (BCa) 95% confidence intervals. The measurement model showed adequate convergent validity (all outer loadings > .78, AVE > .67, composite reliability > .89) and discriminant validity (HTMT < .48 for all construct pairs). All path coefficients reported below are standardized (β). Mentorship quality was significantly and positively related to employee engagement, both as a total effect (β = .27, SE = .06, 95% CI [.15, .39], p < .001) and, to a smaller degree, as a direct effect controlling for technical skill development (β = .17, SE = .06, 95% CI [.05, .29], p = .005), consistent with partial mediation. Technical skill development significantly mediated the mentorship–engagement relationship (indirect effect = .106, 95% CI [.058, .166]). Learning flexibility showed a significant main effect on technical skill development (β = .12, SE = .06, 95% CI [.00, .24], p = .044), but its interaction with mentorship quality was only marginally significant (β = .13, SE = .07, 95% CI [-.01, .27], p = .061), and the formal index of moderated mediation was not statistically significant (index = .049, 95% CI [-.002, .105]), although conditional indirect effects were significant and numerically larger at higher levels of learning flexibility. Because the design is cross-sectional and relies on single-source self-report data, these findings are interpreted as associational rather than causal. The results support mentorship and perceived technical skill growth as robust, complementary correlates of engagement, while suggesting that learning flexibility’s moderating role warrants further investigation with larger and more heterogeneous samples.
Implications for the design of learning and development (L&D) programs and for future PLS- SEM-based workforce research are discussed.