Autonomous Systems for Kindergarten and Primary School Teachers
Project Overview
The project is an output from a course in my Masters program, Making Autonomous Systems. The goal of the project was to design AI technologies that foster high-performing and meaningful work experiences. This project was a group project consisted of 2 Master's students.
Duration: April - August 2025
User Group
1 Kindergarten Teacher and 3 Primary School Teachers
24 years old and above
From in and outside of Germany
From early-career to highly experienced educators. Represent a range of digital familiarity.
The everyday practices of the Kindergarten teacher include focusing on emotional development, routine building and creative learning through play.
The everyday practices of the Primary school teachers include planning and delivering lessons across core subjects (e.g. math, science) track learning process and observing students.
Context and Problem
Performance
Participants view a successful performance when they see the students happy and learning.
Success in performance can be measured in students' test results and feedback from parents.
Performance is affected by how students' needs and behavior are managed.
Time-consuming preparation affects performance.
Meaning
Meaningful work is being a companion and support for the students - assisting for life.
Strong relationship is built on trust and understanding.
Collaboration with peers help them better their skills in teaching, and affects their meaningfulness of work.
Meaningful moments boost their self-esteem.
Increased autonomy makes teaching fun
Metholodogy
Human-Centered Design (ISO 9241-210:2019)
Understand & describe user context
Define user requirements
Draft design solutions
Test & evaluate solutions
Outcome
Performance
Design Prototype for Performance: https://www.youtube.com/watch?v=778nD3zKnEU
Evaluation
The design was seen as effective in supporting classroom management by helping teachers understand and adapt to student behavior. It also enhanced student and parent engagement by boosting excitement, increasing awareness, and building confidence. In terms of portfolio quality, it improved efficiency and provided clearer insights into each student’s learning journey. However, challenges included privacy concerns, potential distractions, reduced reliance on teachers’ own judgment, difficulties for non-tech-savvy educators, and risks of conflict with AI.
Meaning
Design Prototype for Meaning: https://www.youtube.com/watch?v=W_JluBiMAbQ
Evaluation
Participants highlighted that the solution supported more meaningful interactions by freeing up time for direct engagement with students and peers. It also encouraged self-reflection and professional growth, helping teachers refine their methods and improve their practice. In addition, the system fostered stronger social relationships by enabling teachers to focus on life skills and bonding beyond academics, while also promoting autonomy in planning and decision-making. Finally, it contributed to self-esteem and recognition, as teachers felt their role and authority were reinforced through the assistant’s support.
The main concerns center on an over-reliance on Melodi (the robot) for emotional and social cues, which risks diminishing the teacher’s competence and authority. Instances where Melodi acted independently—such as correcting the teacher or appearing as a higher authority—were seen as potentially undermining teacher self-esteem and professional confidence.
Lesson Learned
We learned that when designing AI solutions, it’s not enough to focus only on efficiency and performance, the technology also needs to support human connection and trust.
The real value comes when AI enhances, rather than replaces, the meaning people find in their interactions.