Robotic Teacher Assistant

Research development


The Robotic Teacher Assistant project addressed two key challenges. First, the growing workload on teachers, including class management, material preparation, and assignment marking, necessitated a sustainable, scalable support system. Second, facilitating student engagement, particularly for those hesitant to ask questions due to shyness or language barriers. This project sought a solution to bridge these gaps, ensuring effective and inclusive classroom interactions.


Our solution, the Robotic Teacher Assistant, seamlessly integrates advanced robotics and AI to support educators and students. This interactive robot, powered by AI tools like DialogFlow and cloud platforms including AWS and Google Cloud, assists in querying, delivering lectures, and conducting quizzes. Its ability to fetch real-time student queries from a web application and provide accessible post-lecture assistance makes it a groundbreaking tool in educational technology.


The Robotic Teacher Assistant project, jointly undertaken by CQUniversity and Acme Robotics Pty Ltd, was an innovative venture aimed at integrating advanced robotics and AI into the educational landscape. Spearheaded by Michael Cowling, Associate Professor in ICT at CQUniversity, the project focused on developing robotic assistants to alleviate the increasing workload of teachers and enhance student engagement in the learning process.

Challenges: The project targeted two significant challenges in the contemporary educational domain. Firstly, the mounting workload on teachers, who are burdened with extensive classroom hours, learning material development, and assignment assessments. Secondly, the project aimed to overcome barriers in student-teacher interaction. Factors like shyness, perceived relevance of questions, and language proficiency often hinder students, especially international ones, from actively engaging in classroom discussions.

The Robotic Solution: To address these challenges, we developed an interactive robotic assistant capable of performing multiple functions. Key features included:

  • Query Assistance: The robot collects student queries via a web application developed using PHP, MySQL, and JavaScript, hosted on AWS. It then presents these queries to the teacher, recording responses in both audio and text formats.
  • Lecture Delivery: Utilizing Google’s text-to-speech engine, the robot delivers lectures based on curated materials stored in a MySQL database.
  • Interactive Quizzes: The robot facilitates quizzes, with the web application enabling students to participate and receive instant feedback and results.

Technological Integration: The project harnessed various third-party software and platforms, such as DialogFlow, Amazon Web Services, Google Cloud Platform, IBM Cloud Services, and Zora Software for Nao Robots. This blend of technologies ensured a robust and efficient system.

Impact and Future Potential: The Robotic Teacher Assistant stands as a testament to the potential of AI and robotics in transforming educational methodologies. It not only eases the teacher’s workload but also empowers students to engage more confidently in their educational journey. The project’s success paves the way for further exploration and implementation of similar technologies in diverse learning environments.


Designed to alleviate teachers’ workload, the robot aids in classroom interaction, query resolution, and educational content delivery.

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