A Study on the Role of Affective Feedback in Robot-Assisted Learning
Gabriela Błażejowska1, Łukasz Gruba2, Bipin Indurkhya3
1Nextbank Software, 30-085 Krakow, Poland.
Sensors (Basel, Switzerland)
|February 11, 2023
Summary
This study explored how robots with emotional personalities affect programming education. Affective feedback from robots enhanced learning for novices but decreased robot likeability, suggesting the uncanny valley effect.
Area of Science:
- Robotics in Education
- Human-Robot Interaction
- Affective Computing
Background:
- Robots are increasingly used in computer programming education.
- Affective feedback in intelligent tutoring systems can improve learning efficiency.
- Research on robots with emotional personalities in learning yields mixed results.
Purpose of the Study:
- To investigate the impact of a robot's positive verbal and non-verbal emotive behavior on programming education.
- To explore the effect of affective feedback on student engagement and learning outcomes.
- To examine the influence of robot personality on user perception and likeability.
Main Methods:
- A pilot study involving a robot-assisted programming session with the Miro-E robot.
- Participants programmed the robot's behavior, receiving either affective feedback or neutral responses.
- Emotional states were monitored via facial expressions, with pre- and post-session questionnaires administered.
Main Results:
- Participants generally reacted positively to the robot and the programming task.
- Students with low prior programming experience or interest showed the greatest affective gains.
- The robot's affective expressions negatively impacted its likeability, indicating the uncanny valley effect.
Conclusions:
- Robot-assisted programming with affective feedback can benefit novice learners.
- Careful design is needed to balance affective expression and robot likeability in educational robots.
- The uncanny valley effect remains a significant consideration in developing emotionally expressive educational robots.
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