Robot Motivator: Improving User Performance on a Physical/Mental Task Juan Fasola and Maja J Matarić Interaction Lab University of Southern California Los Angeles, CA, USA
[email protected],
[email protected] ABSTRACT We describe the design and implementation of a socially assistive robot that is able to monitor the performance of a user during a combined mental and physical task, with the purpose of motivating the user to complete the task and to improve performance. A three-condition experimental study was constructed for evaluation of the robot and preliminary results of the robot’s interaction with human participants are presented.
Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics
elapsed to complete a sequence, add a necessary physical component to the game apart from the traditional cognitive/memory component. The robot platform, along with a schematic of the experiment layout, is shown in Figure 1. FeilSeifer and Matarić developed a similar game for studying SAR technology [5]; our work differs from theirs in that the robot does not try to shape the user’s actions during a specific sequence, but instead tries to motivate the user to perform faster on sequences they have completed correctly. Hence, the robot allows the users to retain a certain sense of autonomy while still motivating them to complete the task and improve during the game.
General Terms Performance, Human Factors, Design, Experimentation
Keywords Socially assistive robotics, human-robot interaction, motivation
1. I"TRODUCTIO" The American Alzheimer’s Association reported that more than one million residents in assisted living residences and nursing homes have some form of dementia or cognitive impairment and that number is increasing every day [2]. As with numerous other diseases, there is no cure for dementia but medication and special therapy can improve disease symptoms. Non-pharmacological treatments focus on physical, emotional, and mental activity. Engagement in activities is one of the key elements of good dementia care. Our focus here is on developing and studying the effectiveness of Socially Assistive Robotics (SAR) [1] towards providing affordable customized care for individuals suffering from cognitive changes related to aging and/or Alzheimer’s disease. The work presented in this paper is an experimental implementation of a socially assistive robot whose purpose is to motivate users to complete and improve performance on a mental and physical activity. The overall goal of the work is to evaluate and validate the effectiveness of the technology to gain insight for a future study geared towards the intended elderly population.
2. EXPERIME"T DESIG" 2.1 Experiment Scenario The task in question is a memory game similar to “Simon”, wherein the robot gives the user a sequence of buttons to press, to be remembered and performed correctly. There are three buttons in the game (A, B, and C) used to construct the sequences, which range in difficulty from three to nine buttons in length. The buttons are placed on stands that are placed at positions around the room such that no two are within arm’s reach of one another. The locations of the buttons, along with measuring the time Copyright is held by the author/owner(s). HRI’09, March 11–13, 2009, La Jolla, California, USA. ACM 978-1-60558-404-1/09/03.
(a) (b) Figure 1: (a) Robot platform used in the experiments (b) Experimental setup with locations of buttons (A, B, C), human participant (H), and robot (R) shown.
2.2 Experiment Conditions Three experiment conditions were used to test the effectiveness of different components of the system; each is described below.
2.2.1 Report Condition The baseline condition for the experiment is the Report condition, wherein the robot only serves as game instructor and evaluator. The robot does not try to explicitly motivate the user to improve performance on the task, and hence all desire for improvement must come from the user’s own intrinsic motivation upon receiving the scores (correctness and time elapsed) reported by the robot. The sequences given by the robot increase in difficulty at a constant rate, three at each level, until reaching the maximum sequence length of nine buttons.
2.2.2 Praise Condition The game sequencing in the Praise condition is the same as in the Report condition, but in this condition the robot not only reports the score to the user, but also praises and reassures the user after they correctly repeat a given sequence. For example, upon successful completion of a sequence, the robot might say to the user “Great job!” or “Wow, that was awesome”. Vallerand and
Reid were able to demonstrate that positive verbal feedback about performance can increase intrinsic motivation, yet when always tied to the participant’s own perceived competence [3,p.318-320]. As such, the robot in this condition praises in order to give the user confidence, yet never praises the user when the sequence is incorrect; in those cases it provides reassurance instead (e.g. “Unlucky, it was BCB, not BCA”). To test the ability of the robot to motivate the users, when a sequence is repeated, the robot explicitly challenges the user to improve upon the previous time.
2.2.3 Challenge Condition
have negatively affected the impression of the robot in the Praise and Challenge conditions. However, the participant favored the Challenge condition over the Praise condition, which supports our third hypothesis. Participant 2, on the other hand, did not have a bias against praise from the robot and ranked the conditions in a manner consistent with hypotheses 1-3. Table 1. Participants’ answers to experiment survey. Conditions are denoted as R=Report, P=Praise, C=Challenge. Questions
Participant 1 Participant 2
The Challenge condition is exactly the same as the Praise condition, with the only difference being the way the robot changes the difficulty level of the sequences given to the user. Much research has been done on the notion of “optimal challenge” when performing a task, in which the participant performing the task reaches the appropriate level of difficulty according to individual ability. Csikszentmihalyi’s research suggests that “when one engages in an optimally challenging activity with respect to one’s capacities there is a maximal possibility for task-involved enjoyment” [3,p.29]. He also states that intrinsically motivated activities are those characterized by enjoyment. The goal of this condition is thus to achieve the “optimal challenge” for the user; if the robot can increase the intrinsic motivation of the user for the activity, the user will likely want to continue the activity. The ability of the robot to adapt to the user based on user performance is similar to the way Tapus et al. were able to adapt the behavior of their robot in assisting users during a physical task [4], but our robot does not modify its behavior, but instead modifies the sequences given and hence the task itself in order to adapt to the user’s ability.
The study results are also consistent with our fourth hypothesis, as both subjects reported being motivated by the robot when challenged to improve upon their past performance on a given button sequence, as opposed to ambivalence or annoyance for having to repeat the same sequence. This result demonstrates the potential of socially assistive robotics technology to provide motivation and encouragement to users who must perform mundane or challenging tasks but might not be as motivated to do so without proper guidance. Both participants also reported enjoying the game, which suggests that the game presented, or a variant of it, may be appropriate for elderly users.
2.3 Hypotheses
4. CO"TI"UI"G WORK
The hypotheses for the study were as follows: 1. The users will feel intrinsically motivated to perform the task in the Report condition, but will be easily bored by the initial slow pace and frustrated by the difficulty of later stages. 2. The robot giving praise will increase the user’s intrinsic motivation and enjoyment of the task. 3. The robot’s adaptation to the user’s natural skill level for optimal challenge will increase the user’s intrinsic motivation and enjoyment of the task and reduce frustration. 4. The robot will be able to motivate the user to perform the task as well as motivate them to improve their performance on the task.
Based on the promising preliminary results from the experiment presented here, we plan to conduct future studies with participants from the target elderly population to further evaluate the robot’s effectiveness, during short as well as longer periods of interaction, to also address novelty effects.
3. PRELIMI"ARY RESULTS Two participants were recruited for all three conditions of the study. After all three conditions were finished, each was asked to fill out a short questionnaire regarding the experience with the robot. A summary of the answers provided by the participants is presented in Table 1. Participant 1 found the Report condition most enjoyable, whereas Participant 2 found the Challenge condition most enjoyable, which would have been the natural choice based on our hypotheses. The choice of the Report condition for Participant 1 as most enjoyable may be due to the participant’s annoyance with the robot giving praise, as was mentioned in a post-experiment conversation. Participant 1 felt that robots giving praise seemed somewhat “fake”; that might
Most enjoyable to least
R,C,P
C,P,R
Most frustrating to least
P,R,C
R,P,C
Did you interact with the robot?
Yes
Yes, at first
Did the robot motivate you?
Yes
Yes
Did you enjoy the game?
Yes
Yes
5. REFERE"CES [1] Feil-Seifer, D. and Matarić, M. J. “Defining socially assistive robotics,” in Proc. IEEE International Conference on Rehabilitation Robotics (ICORR’05), Chicago, Il, USA, June 2005, pp. 465–468. [2] American Alzheimer Association, (2007). “About Alzheimer’s Disease Statistics”, American Alzheimer Association. [3] E. Deci and R. Ryan, Intrinsic Motivation and SelfDetermination in Human Behavior. New York: Plenum Press, 1985. [4] Tapus, A., Tapus, C., and Matarić, M., J. “User-Robot Personality Matching and Robot Behavior Adaptationfor Post-Stroke Rehabilitation Therapy”, In Intelligent Service Robotics: Multidisciplinary Collaboration for Socially Assistive Robotics, 1:169-183, Apr 2008. [5] David J. Feil-Seifer and Maja J. Matarić. "Shaping Human Behavior by Observing Mobility Gestures". Poster paper in 1st Annual Conference on Human-Robot Interaction, pages 337-338, Salt Lake City, UT, Mar 2006.
