Determining how best to support culturally diverse student populations with varying levels of background schema (i.e., prior knowledge) as they look to succeed at mastering the fundamentals of chemistry is a venture of great patience and care. Creating, implementing, and investigating dynamic (adaptive) learning experiences requires more than just time and attention, though. Organizing a well-rounded team with adequate resources (monetary or otherwise) under a common goal is a fundamental starting point, and learning engineering (LE) provides a basis (i.e., fundamental process and practice) by which the aforementioned can be understood and executed. Moreover, by combining LE with openly-licensed resources and institutionally-funded technologies, teams can not only reduce students’ financial strain, but also leverage well-supported technology (at no extra cost) to exercise best practices in teaching and learning and promote student progress through built-in learning management system (LMS) features, such as Canvas Mastery Paths (MP). This study proposes that by engaging in course design / redesign in alignment with the LE process in conjunction with a minimally-adaptive (deterministic) instructional system (Canvas MP), project teams can enhance student learning in marked (statistically significant) ways and maintain a sustainable, stepped plan for continual course improvement.