2332 at an acute scale. The definitive closure of the division’s smelter—driven by environmental sustainability imperatives and decarbonization pressures—forced workforce reconversion, with 14 workers relocated to the Fire Refining Area. This organizational disruption coincides with technological modernization through two capital projects: an Advanced Rotary Furnace (ARF), a 300-ton unit replacing traditional reverberatory technology with integrated DCS control systems, enhanced energy efficiency, and nitrogen agitation for improved chemical homogenization; and an Emissions Treatment Plant (ETP), addressing environmental compliance through combustion gas processing and heat recovery. Together, these projects represent a fundamental shift from experience-based manual operations to digitally-mediated process control. The fire refining workforce—60 workers averaging 44.8 years of age (range: 23–62) with 13.1 years of mean tenure—embodies the tension between accumulated expertise and technological transition. This mature, experienced workforce must now adopt new technologies, digital control systems, and collaborative methodologies, while the organization must prepare them rather than replace them. Preliminary diagnostic findings using a validated hierarchical productivity model revealed that these workers operate at only 40.6% of their theoretical productive potential—a deficit rooted in attitudinal rather than aptitudinal factors. The workforce demonstrates technical competence but motivational disengagement, with reconverted workers maintaining capabilities but having lost organizational purpose. Without proactive intervention, the organization risks crystallizing into what diagnostic narratives revealed as “resigned mediocrity rather than operational excellence.” Organizational change scholarship establishes that workforce adaptation depends not merely on training provision but on psychological and contextual factors: shared commitment and collective efficacy beliefs (Weiner, 2009), the interaction between implementation climate and innovation-values fit (Klein & Sorra, 1996), and individual dispositional, contextual, and process-related antecedents that shape reactions to change (Oreg et al., 2011). Simultaneously, adaptive learning research demonstrates that instructional effectiveness requires systematic understanding of learner characteristics, content architecture, and the interpretive layer through which workers perceive their capacity to learn (Martin et al., 2020). Yet a persistent integration gap separates these bodies of knowledge. Organizations rarely diagnose readiness factors before designing learning interventions, defaulting instead to uniform training programs that ignore variation in worker profiles, treat demographic proxies like age as resistance predictors, and overlook supervisors’ pivotal role in shaping learning climates. MacMahon et al. (2024) captured this misalignment as the “streetlamp effect”—organizations search for answers in formal training because it is visible and measurable, while the contextual factors that determine learning effectiveness go unrecognized. Within just transition frameworks, Standing’s (1997) concept of “skill reproduction security”—the opportunity to gain and retain skills through employment training—remains underdeveloped in both research and practice, as De Ruyter and Bentley (2024) emphasize. The present study operationalizes this concept by developing an integrated methodology where cultural diagnosis precedes and directly informs adaptive learning system design. Rather than treating workforce preparation as a byproduct of technology implementation, this approach positions human factors integration at the earliest design stage—addressing a gap that recent Mining 4.0 reviews have explicitly identified (Lund et al., 2024). The context of the studied division, where experienced workers face simultaneous organizational disruption and technological modernization, provides an empirical testing ground for this diagnostic-before-design approach. 2. OBJECTIVES AND SCOPE This study addresses the integration gap between organizational change diagnosis and adaptive learning design by pursuing three objectives. First, to conduct comprehensive cultural diagnosis of a fire refining workforce (n=60) preparing for ARF technology implementation, using a validated productivity model that captures psychological dimensions beyond technical competency. Second, to translate diagnostic findings into adaptive learning system architecture, demonstrating how empirical workforce profiles can inform differentiated instructional design rather than uniform training approaches. Third, to challenge assumptions that demographic characteristics—particularly age—determine change readiness, redirecting organizational attention toward modifiable contextual factors such as supervisory relationships and commitment quality. These objectives directly engage the Congress theme of delivering minerals through trust, transformation, and technology. The study addresses the Transformation dimension by developing a
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