This paper presents a model which can automatically detect a variety of student speech acts as students collaborate within a computer supported collaborative learning environment. In addition, an analysis is presented which gives substantial insight as to how students' learning is associated with students' speech acts, knowledge that will significantly influence how this model is utilized by running learning software. Within Piagetian theory, the cognitive conflict of ideas between students is seen as beneficial for learning. Which sorts of interpersonal behaviors lead to most effective learning, however, is open to debate, with some researchers arguing that cooperation is most effective and others arguing that interpersonal conflict is a natural part of collaborative learning. We find that, in fact, interpersonal conflict is associated with positive learning, a finding that must be taken into account, in designing interventions that rely upon detectors of students' spee...