Introductory computer science courses are being increasingly taught using technology-mediated instruction and e-learning environments. The software and technology in such courses could benefit from the use of student models to inform and guide customized support tailored to the needs of individual students. In this paper, we investigate how student motivated engagement profiles developed in educational research can be used as such models to predict student behaviors. These models are advantageous over those learned directly from observing individual students, as they rely on different data that can be available a priori before students use the technology. Using tracked behaviors of 249 students from 7 CS1 courses over the span of 3 semesters, we discover that students with different engagement profiles indeed behave differently in an online, wiki-based CSCL system while performing collaborative creative thinking exercises, and the differences between students are primarily as expected based on the differences in the profiles. Thus, such profiles could be useful as student models for providing customized support in e-learning environments in CS1 courses.