To better prepare future generations, knowledge about computers and programming are one of the many skills that are part of almost all Science, Technology, Engineering, and Mathematic programs; however, teaching and learning programming is a complex task that is generally considered difficult by students and teachers alike. One approach to engage and inspire students from a variety of backgrounds is the use of educational robots. Unfortunately, previous research presents mixed results on the effectiveness of educational robots on student learning. One possibility for this lack of clarity may be because students have a wide variety of styles of learning. It is possible that the use of kinesthetic feedback, in addition to the normally used visual feedback, may improve learning with educational robots by providing a richer, multi-modal experience that may appeal to a larger number of students with different learning styles. It is also possible, however, that the addition of kinesthetic feedback, and how it may interfere with the visual feedback, may decrease a student’s ability to interpret the program commands being executed by a robot, which is critical for program debugging. In this work, we investigated whether human participants were able to accurately determine a sequence of program commands performed by a robot when both kinesthetic and visual feedback were being used together. Command recall and end point location determination were compared to the typically used visual-only method, as well as a narrative description. Results from 10 sighted participants indicated that individuals were able to accurately determine a sequence of movement commands and their magnitude when using combined kinesthetic + visual feedback. Participants’ recall accuracy of program commands was actually better with kinesthetic + visual feedback than just visual feedback. Although the recall accuracy was even better with the narrative description, this was primarily due to participants confusing an absolute rotation command with a relative rotation command with the kinesthetic + visual feedback. Participants’ zone location accuracy of the end point after a command was executed was significantly better for both the kinesthetic + visual feedback and narrative methods compared to the visual-only method. Together, these results suggest that the use of both kinesthetic + visual feedback improves an individual’s ability to interpret program commands, rather than decreases it. 
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                            Curricula for teaching end-users to kinesthetically program collaborative robots
                        
                    
    
            Non-expert users can now program robots using various end-user robot programming methods, which have widened the use of robots and lowered barriers preventing robot use by laypeople. Kinesthetic teaching is a common form of end-user robot programming, allowing users to forgo writing code by physically guiding the robot to demonstrate behaviors. Although it can be more accessible than writing code, kinesthetic teaching is difficult in practice because of users’ unfamiliarity with kinematics or limitations of robots and programming interfaces. Developing good kinesthetic demonstrations requires physical and cognitive skills, such as the ability to plan effective grasps for different task objects and constraints, to overcome programming difficulties. How to help users learn these skills remains a largely unexplored question, with users conventionally learning through self-guided practice. Our study compares how self-guided practice compares with curriculum-based training in building users’ programming proficiency. While we found no significant differences between study participants who learned through practice compared to participants who learned through our curriculum, our study reveals insights into factors contributing to end-user robot programmers’ confidence and success during programming and how learning interventions may contribute to such factors. Our work paves the way for further research on how to best structure training interventions for end-user robot programmers. 
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                            - Award ID(s):
- 2143704
- PAR ID:
- 10525520
- Editor(s):
- Adebisi, John
- Publisher / Repository:
- Plos One
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 18
- Issue:
- 12
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0294786
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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