Recently, the Interactive-Constructive-Active-Passive (ICAP) framework has been gaining increasing prominence in cognitive and learning sciences. The ICAP theory asserts that students learn more deeply when they are cognitively engaged in generative and collaborative learning. Indeed, prior studies have established the value of the ICAP framework for predicting student learning. However, the framework has yet to become widely used by practitioners, possibly due to the lack of accessible resources for applying the framework instruction design. This study sought to fill that gap by implementing and validating the ICAP instructional rubric instrument to rate the design of college chemistry courses at a large public university in the southwest and exploring its relationships with several metrics of student performance via multiple regression analysis: a) level of participation; b) final exam grades; c) course grades; d) course retention; and e) course attrition. This study analyzed data from the university’s learning management system and included student-level controls such as markers of prior academic performance (i.e., GPA and SAT scores) as well as student demographics. The findings of this study suggest that the ICAP framework may be a useful tool for instructors to improve course design. In addition, the ICAP framework’s predictive claims on student deeper learning were further validated by the results of this study.