Background: This study breaks new ground by presenting a new, more sophisticated model of learning engagement that goes beyond the current state of the art embodied in the widely used Affective-Behavioral-Cognitive (ABC) model. This work synthesizes and builds upon neglected lines of research in the structure of affective engagement. It also integrates entirely novel theoretical considerations in the form of activity spaces--the different learning spaces associated with different course-defined activities, which in turn afford different forms of cognitive and behavioral engagement. To empirically test these theoretical notions, data from a sample of 655 students across multiple sections of a course were analyzed using structural equation modeling that linked different elements of learning engagement to academic performance outcomes like exam grades, quizzes, participation, and assignment performance. The model fit and practical implications of the traditional ABC structure was compared to that of the Revised Affective-Behavioral-Cognitive model (ABC +) proposed here. Results: The traditional ABC model evinced substantially more misfit to the data (CFI = 0.97, TLI = 0.94, RMSEA = 0.037, [90% CI 0.017, 0.056, p RMSEA [less than or equal to] 0.05 = 0.86], CD = 0.57) than the revised ABC + model, which fit the data well (CFI = 0.99, TLI = 0.98, RMSEA = 0.022, [90% CI 0.000, 0.041, p RMSEA [less than or equal to] 0.05 = 0.99], CD = 0.68). As predicted, in the ABC + model affective learning engagement separated into positive and negative components, and cognitive and behavioral engagement further separated by activity spaces. Crucially, each of these engagement factors contribute to different academic outcomes in a manner masked in the ABC model. The ABC + components are not interchangeable, and cannot be conflated with one another, but have distinct functions in supporting student performance. Conclusions: The more sophisticated engagement model presented here reveals deeper patterns of student engagement that can better guide the research community and can be used by faculty members and policymakers to improve student engagement and performance.