We address the problem of assessing the contributions of lexicon-based Natural Language Processing (NLP) techniques to measure learner affective and cognitive engagement and thus predict certification in Frenchspeaking MOOCs. Interest in these approaches comes from the fact they are explainable. Our investigation protocol consists of applying machine learning techniques to determine the relationships between lexiconbased engagement indicators and learning outcomes. The lexicon-based approach is compared with trace log features, and we distinguish between specialised linguistically-based approaches with dedicated lexicon resources and more general but deeper text representations. Language quality and its impact on the task are discussed. We investigate this issue in MOOCs imposing or not the use of the forum in their learning activities.