Chemistry education routinely confronts the dual challenge of conceptual abstraction and representational complexity. Pedagogical technologies can improve outcomes, but only when their use is framed by clear didactic conditions that align purposes, content structures, methods, and assessment. This article elaborates a comprehensive set of didactic conditions for effective chemistry instruction and translates them into a methodological foundation suitable for secondary and higher education. Building on research in chemistry education, cognitive load theory, formative assessment, universal design, and active learning, the paper synthesizes how alignment to disciplinary “big ideas,” representational scaffolding across macroscopic, submicroscopic, and symbolic levels, structured inquiry in the laboratory, and data-informed feedback loops interact to foster durable understanding, procedural fluency, and scientific reasoning. The study proposes an operational model that integrates backward design, diagnostic entry assessments, carefully staged practice with fading guidance, and inclusive access pathways supported by educational technologies such as molecular visualization, adaptive homework, learning analytics, and virtual laboratories. The discussion addresses threats to validity and equity, including misconceived tool-led adoption, cognitive overload from multimedia resources, and the risk of tracking students into low-expectation paths. The article concludes with an evaluation framework combining outcome mastery, growth measures, and indicators of metacognitive regulation, providing a roadmap for institutions seeking to scale technology-supported chemistry teaching without sacrificing rigor or inclusivity.  

Chemistry education, didactics, pedagogical technology, representational competence, formative assessment

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