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A dialogue is successful when there is alignment between the speakers atdifferent linguistic levels. In this work, we consider the dialogue occurringbetween interlocutors engaged in a collaborative learning task, where they arenot only evaluated on how well they performed, but also on how much theylearnt. The main contribution of this work is to propose new automatic measuresto study alignment; focusing on verbal (lexical) alignment, and behavioralalignment (when an instruction given by one was followed with concrete actionsby another). A second contribution of our work is to study how spontaneousspeech phenomena are used in the process of alignment. Lastly, we make publicthe dataset to study alignment in educational dialogues. Our results show thatall teams verbally and behaviourally align to some degree regardless of theirperformance and learning, and our measures capture that teams that did notsucceed in the task were simply slower to collaborate. Thus we find that teamsthat performed better, were faster to align. Furthermore, our methodologycaptures a productive period that includes the time where the interlocutorscame up with their best solutions. We also find that well-performing teamsverbalise the marker "oh" more when they are behaviourally aligned, compared toother times in the dialogue; showing that this marker is an important cue inalignment. To the best of our knowledge, we are the first to study the role of"oh" as an information management marker in a behavioral context (i.e. inconnection to actions taken in a physical environment), compared to only averbal one. Our measures contribute to the research in the field of educationaldialogue and the intersection between dialogue and collaborative learningresearch.

Studying Alignment in a Collaborative Learning Activity via Automatic Methods: The Link Between What We Say and Do