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<summer program project phase>

WISER Education Challenge

Build an Innovative Quantum Education Resource

WISER works to expand access to quantum, AI, engineering, and advanced computing education through expert-led learning, hands-on projects, and career-connected opportunities.

Although quantum hardware and software continue to advance, accessible and technically accurate educational content remains limited. Learners often struggle to connect mathematical theory, quantum algorithms, and practical implementation.

This challenge invites participants to reimagine how quantum computing is taught and learned.

The Challenge

Design and develop an educational resource that teaches one or more quantum-computing concepts through engaging, interactive, and technically accurate content.

The resource should begin with the fundamentals, use a clear pedagogical approach, and gradually introduce the relevant technical concepts.

Possible topics include:

  • Variational Quantum Algorithms

  • Quantum Computing and AI

  • Quantum Machine Learning

  • Quantum Error Correction

  • Quantum Computing for Chemistry

  • Quantum Cryptography and Cybersecurity

Teams are encouraged to identify a specific learning gap and design a resource that addresses it effectively.

Possible Project Formats

Submissions may include:

  • Interactive Jupyter Notebook tutorials

  • Browser-based learning applications

  • Quantum circuit visualizers

  • Educational games

  • AI-based quantum tutoring assistants

  • Adaptive quizzes

  • Lecture videos or animations

  • Virtual laboratory activities

  • Coding tutorials

  • Quantum concept visualizations

Required Deliverables

Your final GitHub repository should include:

  • All source code and project assets

  • Installation and execution instructions

  • Target audience

  • Learning objectives

  • Educational methodology

  • Technologies used

  • A 5–10 minute demonstration video

  • A brief user guide

  • Future improvements and scalability plans

Optional Advanced Tasks

Teams may also:

  • Include automated assessments.

  • Support multiple languages.

  • Demonstrate measurable learning outcomes.

  • Create a resource that educators can adopt with minimal setup.

Platforms & Tools

Participants may use any suitable technology, including:

  • Quantum SDKs and simulators

  • AI and large language models

  • Retrieval-augmented generation

  • Interactive visualizations

  • AR or VR technologies

  • Gamification frameworks

  • Web-development tools

  • Educational platforms

The final resource should be easy to access, reproduce, evaluate, and reuse.

Judging Criteria

Projects will be evaluated based on:

  • Educational impact

  • Technical accuracy

  • Creativity

  • User engagement

  • Implementation quality

  • Documentation and reproducibility

  • Potential for adoption

  • Scalability

Judges will especially value projects that make difficult concepts easier to understand without sacrificing technical correctness.

Data, Attribution and AI Use

Teams may use open educational datasets, graphics, software libraries, and other resources when properly licensed and attributed.

Any use of generative AI or coding assistants must be clearly documented. Teams must be able to explain, verify, and defend all submitted work.

Team & Deadline

  • Maximum team size: 3 participants

  • Final submission deadline: August 7, 2026

  • No deadline extensions will be offered.

Join the Network

We are always on the lookout for pioneering researchers and quantum technologists.
Apply Now
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