When things go wrong during a medical procedure, patients' expectations are fairly straightforward: They expect an explanation of what happened, an apology if an error was made, and assurance that something will be done to prevent it from happening to another patient. Patients have a right to full disclosure; it is also therapeutic in relieving their anxiety. But if they have been harmed by our...

Apologies made by physicians for adverse medical events have been identified as a mitigating factor in whether patients decide to litigate. However, doctors are socialized to avoid apologies because apologies admit guilt and invite lawsuits. An "Apology Law," which specifies that a physician's apology is inadmissible in court, is written to encourage patient-physician communication. Building on...

This study was an attempt to shed light on the use of requestive speech act by Iranian nonnative speakers (NNSs) of English and Canadian native speakers (NSs) of English to find out the (possible) similarities and/or differences between the request realizations, and to investigate the influence of the situational variables of power, distance, context familiarity, and L1’s (possible) influence. ...

Failure happens in most social interactions, possibly even more so in interactions between a robot and a human. This paper investigates different failure recovery strategies that robots can employ to minimize the negative effect on people’s perception of the robot. A between-subject Wizard-of-Oz experiment with 33 participants was conducted in a scenario where a robot and a human play a collabo...

In intelligent tutoring systems with natural language dialogue, speech act classification, the task of detecting learners’ intentions, informs the system’s response mechanism. In this paper, we propose supervised machine learning models for speech act classification in the context of an online collaborative learning game environment. We explore the role of context (i.e. speech acts of previous ...