The Robot Self-Efficacy Scale: Robot Self-Efficacy, Likability and Willingness to Interact Increases After a Robot-Delivered Tutorial

Abstract

An individual's self-efficacy to interact with a robot has important implications around the content, utility and success of the interaction. Individuals need to achieve a high level of self-efficacy in human robot-interaction in a reasonable time-frame for positive effects to occur in shortterm human-robot scenarios. This trial explored the impact of a 2-minute automated robot-delivered tutorial designed to teach people from the general public how to use the robot as a method to increase robot self-efficacy scores. This trial assessed scores before (T1) and after (T2) an interaction with the robot to investigate changes in self-efficacy, likability and willingness to use it. The 40 participants recruited had on average very low level of robotic experience. After the tutorial, people reported significantly higher robot self-efficacy with very large effect sizes to operate a robot and apply the robot to a task (η <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> = 0.727 and 0.660). Significant increases in likability and willingness to interact with the robot were also found (η2p = 0.465 and 0.480). Changes in likability and self-efficacy contributed to 64% of the variance in changes to willingness to use the robot. Initial differences were found in robot self-efficacy for older people and those with less robotics and programming experience compared with other participants, but scores across these subgroups were similar after completion of the tutorial. This demonstrated that high levels of self-efficacy, likeability and willingness to use a social robot can be reached in a very short time, and on comparable levels, regardless of age or prior robotics experience. This outcome has significant implications for future trials using social robots, since these variables can strongly influence experimental outcomes.