  Transparency is an important aspect of human-robot interaction (HRI), as it
can improve system trust and usability leading to improved communication and
performance. However, most transparency models focus only on the amount of
information given to users. In this paper, we propose a bidirectional
transparency model, termed a transparency-based action (TBA) model, which in
addition to providing transparency information (robot-to-human), allows the
robot to take actions based on transparency information received from the human
(robot-of-human and human-to-robot). We implemented a three-level (High, Medium
and Low) TBA model on a robotic system trainer in two pilot studies (with
students as participants) to examine its impact on acceptance and HRI. Based on
the pilot studies results, the Medium TBA level was not included in the main
experiment, which was conducted with older adults (aged 75-85). In that
experiment, two TBA levels were compared: Low (basic information including only
robot-to-human transparency) and High (including additional information
relating to predicted outcomes with robot-of-human and human-to-robot
transparency). The results revealed a significant difference between the two
TBA levels of the model in terms of perceived usefulness, ease of use, and
attitude. The High TBA level resulted in improved user acceptance and was
preferred by the users.
