Willow is a free-text Adaptive Computer Assisted Assessment system, which supports natural language processing and user modeling. In this paper we discuss the benefits coming from extending Willow with recommendations. The approach combines human computer interaction methods to elicit the recommendations with data mining techniques to adjust their definition. Following a scenario-based approach, 12 recommendations were designed and delivered in a large scale evaluation with 377 learners. A statistically significant positive impact was found on indicators dealing with the engagement in the course, the learning effectiveness and efficiency, as well as the knowledge acquisition. We present the overall system functionality, the interaction among the different subsystems involved and some evaluation findings.