How do Experts Adapt their Explanations to a Layperson’s Knowledge in Asynchronous Communication? An Experimental Study

Abstract. Despite a plethora of recommendations for personalization techniques, such approaches often lack empirical justification and their benefits to users remain obscure. The study described in this paper takes a step towards filling this gap by introducing an evidence-based approach for deriving adaptive interaction techniques. In a dialogue experi-ment with 36 dyads of computer experts and laypersons, we observed how experts tailored their written explanations to laypersons ’ communicational needs. To support adaptation, the experts in the experimental condition were provided with information about the layper-son’s knowledge level. In the control condition, the experts had no available information. During the composition of their answers, the experts in both conditions articulated their planning activities. Compared with the control condition, the experts in the experimental condition made a greater attempt to form a mental model about the layperson’s knowledge. As a result, they varied the type and proportion of the information they provided depend-ing on the layperson’s individual knowledge level. Accordingly, such adaptive explanations helped laypersons reduce comprehension breakdowns and acquire new knowledge. These results provide evidence for theoretical assumptions regarding cognitive processes in text production and conversation. They empirically ground and advance techniques for adap-tation of content in adaptive hypermedia systems. They are suggestive of ways in which explanations in recommender and decision support systems could be effectively adapted to the user’s knowledge background and goals. Key words. adaptive instructional explanations, advice-giving and recommender systems, audience design, cognitive processes in writing and written communication, computer