Peer Review Report For: Towards Sustainable Vocational Education: An Explainable Green AI Ecosystem for Workforce Readiness [version 1; peer review: 2 approved with reservations]

Abstract

Background Vocational education increasingly requires the integration of artificial intelligence-supported learning and sustainability competencies to prepare students for technology-intensive and environmentally responsible workplaces. However, limited empirical evidence exists on learning ecosystems that combine explainable artificial intelligence, sustainability oriented competency development, and workforce readiness. This study developed and examined an Explainable Green Artificial Intelligence Ecosystem for sustainable vocational education. Methods A sequential explanatory mixed-methods design was employed with 236 vocational students assigned to experimental (n = 118) and control (n = 118) groups. The quantitative phase used a non-equivalent control group pretest posttest quasi experimental design, Partial Least Squares Structural Equation Modeling, Random Forest, Extreme Gradient Boosting, and SHapley Additive exPlanations analysis. Semi-structured interviews were subsequently conducted and analyzed thematically to contextualize the quantitative findings. Results Students receiving the Explainable Green Artificial Intelligence Ecosystem demonstrated greater improvements than those receiving conventional instruction. The experimental group showed large effect sizes for workforce readiness (t = 15.872; d = 1.41), green competencies (t = 14.629; d = 1.36), learning engagement (t = 16.204; d = 1.53), and artificial intelligence literacy (t = 15.311; d = 1.44). Green competencies were the strongest structural predictor of workforce readiness (β = 0.618, p < 0.001). Extreme Gradient Boosting achieved the strongest predictive performance (accuracy = 0.914; R 2 = 0.846), while explainability analysis identified green competencies, learning engagement, and artificial intelligence literacy as the leading predictors of workforce readiness. Qualitative findings indicated improved perceptions of artificial intelligence transparency, adaptive learning, sustainability awareness, human artificial intelligence collaboration, and workforce preparedness. Conclusions The Explainable Green Artificial Intelligence Ecosystem was associated with improved sustainability-oriented competencies and workforce readiness in vocational education. The findings indicate that combining explainable artificial intelligence-supported learning with green competency development may support preparation for sustainable and technology-integrated workplaces.