Child–Robot Interactions Using Educational Robots: An Ethical and Inclusive Perspective
This paper presents the Qui-Bot H2O project, which develops four educational sustainable robots and associated software to teach chemistry, robotics, and computational thinking to students aged 3 to 18. The study evaluates human-robot interaction, ethical considerations in the classroom, and strategies to increase the representation of girls in STEM fields. Results from student and teacher testing demonstrate high satisfaction and engagement with the educational robots.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Educators, researchers, and academic institutions interested in implementing educational robotics and fostering gender equity in STEM.
What the document contains
The paper covers the hardware and software design of four educational robots, methodologies for integrating robotics and chemistry into school curricula, an ethical code for classroom robotics, and evaluation results from testing with 212 students.
The document does not provide commercial pricing details for mass manufacturing, nor does it establish binding legislative regulations or governmental mandates for school robot deployment.
- Educational robots can successfully integrate computational thinking with chemical experiments across various school ages.
- The use of open-source robotics helps reduce the digital and robotics divide in educational settings.
- Intentional software and hardware design can help reduce gender stereotypes and engage more girls in STEM fields.
- Students across primary and secondary education reported very high satisfaction and motivation when interacting with the Qui-Bot systems.
- Humanoid educational robots generate higher empathy and more intuitive interaction than non-humanoid automated systems.
· Introduction · Materials and Methods · Ethical Code · Results · Qui-Bot's Social, Economic, and International Impact · Discussion · Conclusions
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
2/5Clear responsibility for AI outcomes
the teacher in charge of directing the activity must be careful not to commission any work outside the center since this could accentuate the access divide.
3.1.1. Access Divide
screening score · 2026-10-24
Fairness
3/5Non-discrimination and equitable treatment
The design of the robots and activities was realized by considering gender equality and by performing activities in the classroom in accordance with a correct ethical code.
1. Introduction
screening score · 2026-10-24
Human Dignity
3/5Respect for the inherent worth of persons
Three main general points comprise the backbone of the code: (i) fighting the digital and robotics divide, (ii) breaking stereotypes and gender biases, and (iii) tackling the dehumanization of education.
3. Ethical Code
screening score · 2026-10-24
Human Oversight
1/5Humans remain in control of consequential decisions
the manual mode allows students to program the robot’s movements at a high level by using internal pre-programmed functions.
2.4. MultiArm Qui-Bot
screening score · 2026-10-24
Privacy
0/5Protection of personal data and private life
n/a
screening score · 2026-10-24
Transparency
3/5Openness about how AI systems work and are used
A technical description of the robot’s construction (sensors, motors, pieces, and 3D design) with HRI features was provided for potential users, with the software to interact with the robots by using a web page.
1. Introduction
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
n/a
screening score · 2026-10-24
Impact Assessment
3/5Required assessment of an AI system's risks/impacts before or during use
Our educational robots were used to measure the backgrounds, impact, and interest of students, as well as their satisfaction after interacting with them.
Abstract
screening score · 2026-10-24