Lopez, C. E., & Tucker, C. (2018, April), Exploring Human-Co-Robot Interactions: Real-time Feedback or not?    Paper presented at 2018 ASEE Mid-Atlantic Section Spring Conference, Washington, District of Columbia. 10.18260/1-2--29462

\bibitem{asee_peer_29462}
  Lopez, C. E., \& Tucker, C. (2018, April), \emph{Exploring Human-Co-Robot Interactions: Real-time Feedback or not?  }
  Paper presented at 2018 ASEE Mid-Atlantic Section Spring Conference, Washington, District of Columbia.
  10.18260/1-2--29462

Christian Enmanuel Lopez and Conrad Tucker.  "Exploring Human-Co-Robot Interactions: Real-time Feedback or not?  ".  2018 ASEE Mid-Atlantic Section Spring Conference, Washington, District of Columbia, 2018, April.  ASEE Conferences, 2018.  https://peer.asee.org/29462 Internet.  12 Dec, 2024

\bibitem{asee_peer_29462}
  Christian Enmanuel Lopez and Conrad Tucker.
  "Exploring Human-Co-Robot Interactions: Real-time Feedback or not?  ".
  \emph{2018 ASEE Mid-Atlantic Section Spring Conference, Washington, District of Columbia, 2018, April}.
  ASEE Conferences, 2018.
  https://peer.asee.org/29462 Internet.  12 Dec, 2024

@INPROCEEDINGS{asee_peer_29462
author = "Christian Enmanuel Lopez and Conrad Tucker"
title = "Exploring Human-Co-Robot Interactions: Real-time Feedback or not?  "
booktitle = "2018 ASEE Mid-Atlantic Section Spring Conference"
year = "2018"
month = "April"
address = "Washington, District of Columbia"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/29462}
number = {10.18260/1-2--29462}
}

TY  - CPAPER
AB  - Appropriate and timely feedback has the potential to improve the learning process. In traditional learning environments, instructors can provide appropriate and timely feedback to students based on their performance and affective states. However, this type of feedback is challenging to provide when the student to instructor ratio high, such as in Engineering Lab environments. Hence, researchers have started exploring how intelligent systems, such as Collaborative-Robots (i.e., Co-Robots), can be implemented in learning environments to assist students towards the successful completion of a task by providing real-time performance feedback. Nonetheless, the type of feedback provided to students (e.g., positive or negative) can have a direct impact on their affective state and ultimately, their performance on tasks. Hence, providing real-time feedback to students may have a detrimental effect on their performance, if that feedback is not delivered at the appropriate time. Although researchers are making significant advances in improving human-co-robot interactions, determining when to provide feedback that advances students’ learning remains an open research question. In light of this, the authors explored the effects that different types of real-time feedback (i.e., positive and negative) have on students’ performance. Similarly, the effects of not providing real-time feedback are investigated. Furthermore, this work explores how students’ facial expression can be captured by Co-robot systems to better understand when to provide real-time performance feedback to students. This work contributes to advancing the field of human-co-robot interactions as well as the National Academy of Engineering’s grand challenge of personalized learning by demonstrating how a student’s facial expression can be employed by Co-robot systems to provide feedback that improves his/her performance.


AU  - Christian Enmanuel Lopez
AU  - Conrad Tucker
CY  - Washington, District of Columbia
DA  - 2018/04/06
PB  - ASEE Conferences
TI  - Exploring Human-Co-Robot Interactions: Real-time Feedback or not?  
UR  - https://peer.asee.org/29462
DO  - 10.18260/1-2--29462
ER  -