ICanProveIt: Proof-of-Learning
SCF #26 Activation Award Other Developer Tooling $50,000 View in SCF
An AI exam generation platform for the creation of universally respected, academic-standard proof-of-learning certificates.
Team

Tim

Pitch Deck URL

https://tims-personal-organization.gitbook.io/icanproveit/pitch-deck

Project Categories

Team bio

Tim O'Brien

LinkedIn Profile

Coder, Builder, Executive in that order. After an 18 year career as an Enterprise Architect for Fortune 500 companies until in 2018, I started on my journey as an Entrepreneur by prototyping my idea based on blockchain and AI, raised funds, and commercializing my product idea. 

Now, after building with blockchain/Web3 and AI for more than six years I still love AI and Blockchain and believe with some safeguards around AI we can build a bright future. I love coding and still code both for recreation and work. I am passionate about Web3 and its power of inclusion and democratization of the financial world. 

Dr. Zagros Madjd-Sadjadi   

LinkedIn Profile

Professor of Economics at Winston-Salem State University and has more than 30 years of economic consulting and teaching experience. He is the former Chief Economist of the City and County of San Francisco and has provided consulting services for various governments and businesses ranging from small to medium-sized enterprises to Fortune 500 firms. 

His work has been cited in the Congressional Record, helped secure state approval for the I-74 corridor in Winston-Salem, and led to the repeal of the Glass-Steagall Act. 
He is the author of half a dozen books, including three textbooks, and over 60 academic articles and book chapters. In addition to economics, Dr. Madjd-Sadjadi teaches business ethics and has developed several modules on the ethical uses of artificial intelligence (AI) in the business world.

Dr. Mihaela Uleru

LinkedIn Profile

President, IMPACT Institute for the Digital Economy - Technology Alchemist Innovating at the nexus AI/IoT/Blockchain Awarded Research Chair and Professor of Artificial Intelligence. Awarded by the PM the Canada Research Chair in Distributed Intelligent Systems
IEEE multiple Awards for Research in Complex Systems
Distinguished Visiting Professorships Awarded in Vienna, Berkeley, Australia, Germany. Over 200 peer reviewed publications and over 300 Keynotes, Workshops and Lectures Top Six "Women to Watch in Crypto and Blockchain" Technology Section 

Technical Architecture Doc

https://tims-personal-organization.gitbook.io/icanproveit/technical-architecture-and-integration

Project URL

https://tims-personal-organization.gitbook.io/icanproveit

Code URL

https://github.com/tuvalusoftware/ICanProveIt-POC

Section

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Product & Architecture

Overview

ICanProveIt is a digital certification platform that uses advanced technologies to issue verifiable, blockchain-based educational certificates. The platform combines AI, blockchain (Stellar), and decentralized identity (DID) to create proof-of-learning certificates that adhere to high pedagogical standards accepted universally by academic institutions. 

ICanProveIt is designed by university professors and academics to not be adversarial to the academic world. 

'Massive Disruptions in the Job market will overflow the capacity of education institutions  and drive learners to jobs for which there is no formal education. 

While ICanProveIt may challenge traditional educational roles it also promises to liberate teaching professionals from administrative burdens, enabling them to focus more on teaching and research. ICanProveIt was designed to be teacher/professor friendly.

Updates on project plan, marketing, new customers are available by clicking on this ink

https://tims-personal-organization.gitbook.io/icanproveit

Problems ICanProveIt Solves

ICanProveIt solves multiple challenges including :

  1. Non-Demonstrable Knowledge: A significant issue is that 98% of our knowledge and capabilities are non-demonstrable and unshareable. ICanProveIt creates a digital, verifiable format that allows individuals to demonstrate and share their learning effectively.
  2. Chaotic Proof-of-Learning Outside Academia: Outside of the academic world, proof-of-learning is often chaotic, pedagogically repulsive, and largely ignored. The platform standardizes the validation process with rigorous academic oversight to restore credibility.
  3. Limited Formal Education Scope: Formal education covers less than 1% of subjects that people learn throughout their lives. ICanProveIt expands the scope by certifying a broader range of knowledge and skills, regardless of how they were acquired.
  4.  Lack of Verifiability: Traditional online learning often lacks a reliable method to verify educational achievements. ICanProveIt solves this by using blockchain technology for immutable record-keeping.
  5.  Education Accessibility:  High costs and geographic barriers often limit educational opportunities. The platform provides affordable, universally accessible educational certification.
  6. Standardization:  There is a disparate recognition of educational certificates across different geographies and institutions. By adhering to globally recognized standards, ICanProveIt ensures its certificates have wide acceptance.
  7. Mass Retraining  Needs Induced by Job Markets Being Disrupted by  AI: The platform also aims to assist those whose jobs have been disrupted by AI, offering a means to retrain and certify new skills in a rapidly changing job market.

 Target Audience 

The platform primarily serves self-learners, educational institutions, and employers. Self-learners benefit from obtaining verifiable credentials for informal learning, institutions can reduce administrative costs and maintain integrity in credential issuance, and employers receive reliable proof of candidates' learning.

 How It Works 

 ICanProveIt embraces continuous learners and recognizes that self-learning has real value to employers, and the employment market. The internet provides us with nearly unlimited opportunities to follow our interests and passions. Learners can pick from blogs and YouTube videos or take free courses from the world's top universities given by the professors famous for their contributions or their teaching abilities. But there is a catch! Without a reputable certificate as proof-of-learning, the learner is unlikely to receive immediate benefits from his learning. No employer is going to hire someone on the basis of the learner claiming to have read a book or taken a free course with nothing to prove it. 

ICanProveIt works in 3 steps 

   1. The Learner follows their normal path to acquiring knowledge by reading books and blogs, watching videos and taking free online courses from universities. 

   2. the learner uploads or provides us with links to their learning material. 

   3. ICanProveIt platform creates an exam by matching the provided learning material against material in a repository curated by academics ensured to be up to date. 

   4. After successfully completing the exam the learner is issued a certificate that can be put on a resume or shared on social media 


AI Integration: AI is used to generate personalized exams based on the content learned by users, ensuring that the assessment is tailored to the individual’s study material.
Blockchain (Soroban): Stellar’s blockchain technology offers a decentralized, fast, and low-cost ledger to store certificate data, making the issuance and verification of certificates secure and efficient.
Soroban Smart Contracts: Utilizing Soroban, Stellar's smart contract platform, allows for complex operations like conditional certificate issuance and automated verification processes. This enhances the scalability and functionality of the certification process.

Highest Pedagogical Testing Standards

In contrast to the typical, rigid model, where learners are each given the same set of study material, followed by the same exam, ICanProveIt tests learners on the specific material they have consumed, including material from YouTube videos, blog posts, traditional or audiobooks etc. All exams are created on the fly from a curated repository of content matched with the learners' uploaded content. In the case of courses that mimic those found at traditional universities that have a generally recognized curriculum, the learner’s uploaded content will not be used for exam creation but instead will be used to inform the learner as to whether they have sufficiently studied enough (assuming that they studied all of the material uploaded) to be successful in the examination. Learners will still be able to take tests on such standardized classes if their material does not completely satisfy this requirement, but required areas are not covered by the uploaded materials and will draw their questions from a set of curated materials that reflect the standards required for passage of the material.

Generating exams that are relevant to employers means following pedagogicalstandards that allow for comparability across subjects. Most online learning certificates are deemed worthless simply because there is little to no information about the test or material studied. Hiring managers are unlikely to dive deeper into the specific areas studied, the source of the information or the reputation of the certificate issuer. ICanProveIt is designed so that all exams generated are relevant to the learning goals and are formulated in a coherent and logical manner that clearly demonstrates the acquired knowledge of the student.

Test Quality Metrics 

Coverage of Source Material - A metric ranging from 0 - 1 that indicates how much of the input text (material studied) is reflected in the quiz. It is calculated by mapping each question to the relevant sentences in the text and comparing the length of the mapped text to the total passage length. This method is based on the pyramid method used in summary annotations.

Coverage of Curated Material - In cases where there is a typical course content, such as is the case for most principles and intermediate courses in various subjects at the world’s universities, the source material coverage metric will be replaced with the curated material coverage metric that covers the entirety of what is normally expected from a student in such a course and that is similarly given a metric ranging from 0 -1 as evidenced in the Coverage of Source Material metric. This prevents students from selectively choosing material that is narrower than what would typically be found in a standardized course. Employers or associations that wish to ensure coverage of specific topics can have standardized courses offered and learners will be notified as to what percentage of curated material is covered by their source material so that they can determine whether they wish to proceed with the standardized examination or whether they wish to read more of the recommended curated material instead.

Structure  - A  1-3 metric assessing if a set of questions flows logically together, i.e. from easy to difficult, or that natural chronological order is used. For example, if the student was being examined on the formation of the universe, the questioning would start with the Big Bang and work towards the creation of our Solar System. This is similar to a measure used in conversational QG, where questions are logically linked for natural conversation (Mulla and Gharpure 2023).

Redundancy - A  1 to 3 metric assessing repetition within an exam, such as identical questions being asked that do not require a differing perspective or adaptation of the student's thought processes. This has been utilized in conversational QG to prevent repetition and ensure natural conversation (Mulla and Gharpure 2023).

Quality Metrics

Ensuring a heightened level of quality regarding the entire test is crucial. However, the individually tailored questions must also meet exceptionally high standards. Questions must be rated on three metrics used to measure the fundamental aspects of a question's quality:

Relevancy - A binary metric which measures whether the question is semantically relevant to the input context.

Fluency - A binary metric used to assess the grammatical correctness and clarity of language in a set of questions. This metric is employed by Mazidi and Nielsen (2014) and Elkins et al. (2023), and is also used in different scales in Mulla and Gharpure (2023).

Answerability - A binary metric which measures whether the question can be answered from the input context. It is not necessary to be able to find a passage from the input that is an answer to the question; it is enough if a student could reasonably answer the question from the context. For example, applying logic explained in the passage to a new situation makes the question ‘answerable’. As above, previous work by Steuer et al. (2021) and Elkins et al. (2023) uses a similar binary metric, and Mulla and Gharpure (2023) suggest similar metrics on different scales. Soroban Integration

Soroban is used to create an immutable record of the hash of Certificates. These records are used later to validate the certificates against being counterfeited or altered. Soroban will also  play an important role in managing our curated documents allowing them to be managed, versioned, and traced. 
Integration with Soraban will require building a microservice, an adapter and a smart contract. A detailed architecture can be found on our project site. https://tims-personal-organization.gitbook.io/icanproveit/technical-architecture-and-integration

Video URL

https://tims-personal-organization.gitbook.io/icanproveit/video-presentations

Section

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Requested Budget in USD ($)

50000

Total Expected Roadmap

May 2024: Prototype Testing and Feedback Integration

  • Deploy Prototype: Deploy the prototype in a controlled environment to test key functionalities.
  • User Acceptance Testing (UAT): Conduct UAT with a selected group of users to validate the prototype's effectiveness and usability.
  • Feedback Integration: Analyze and integrate user feedback to refine and enhance the prototype's features and user interface.

June 2024: Beta Release and Comprehensive Testing

  • Beta Launch: Release the beta version to a broader audience to gather extensive user feedback and understand the application's performance under varied real-world conditions.
  • Load Testing: Perform load testing to ensure the platform can handle the expected user load without performance degradation.
  • Security Testing: Execute rigorous security testing to safeguard all user data and transactions, especially focusing on blockchain functionalities and data integrity.
  • Early Adapters: Engage with 500 early adopters as part of the beta testing phase.
  • Revenue Projections: Anticipate initial revenue generation from early adopters amounting to $100,000.

July 2024: Final Preparations, Launch Readiness, and Venture Capital Funding

  • Performance Optimization: Optimize the software for better efficiency and speed based on insights from previous testing phases.
  • Bug Fixing: Resolve any critical bugs and issues identified during the beta testing to ensure a smooth and stable user experience.
  • Documentation Finalization: Complete all technical and user documentation, ensuring clarity and accessibility for all end-users.
  • Early Adapters: Increase early adopter engagement to 1,500.
  • Revenue Projections: Generate revenue of $400,000 from expanded early adopter activity and initial product offerings.
  • Venture Capital Funding: Secure venture capital funding in the range of $2 million to $4 million to further enhance development and market expansion strategies.

August 2024: Official Launch and Post-Launch Support

  • System Go-live: Officially launch the platform to the public with full marketing support.
  • Marketing and Public Relations: Implement the marketing strategy including press releases, social media announcements, and partnership promotions.
  • Post-Launch Monitoring: Continuously monitor the system for any operational issues that users may encounter, ensuring quick resolutions.
  • Initial User Feedback Collection: Start collecting detailed user feedback on the platform's performance and user experience for further improvements.
  • Customers: Adjust early adopter count to 2,000 as the focus shifts to broader market penetration.
  • Revenue Projections: Target to achieve revenue of $1,500,000 through enhanced market presence and ongoing sales initiatives.

Ongoing Activities Post-August 2024

  • Continual Improvement Cycle: Establish a continuous development cycle to incorporate new features, updates, and enhancements based on user feedback and emerging educational needs.
  • Regular Security Assessments: Conduct regular security assessments and updates to address new threats and vulnerabilities, maintaining the integrity and security of the platform.
  • Performance Reviews: Regularly review system performance and scalability to ensure the platform meets growing user demands and technological advancements.

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Public Entity Name

FuixLabs.com 

Project Type [If End-User Applications]

Deliverables List

Integration of Dominium with Soroban 

See detailed project plan and cost breakdown at our project GitBook site : detailed-project-plan

Dominium is an open source Product that in addition to implementing the DID specification also supports the  W3C VC-EDU  standard and after participating in the JFF https://www.jff.org effort is interoperable with 30 Universities and Schools. Dominium is unique in its ability to handle thousands of transactions per second and has a customer base that includes land title applications, and payment system. 

Integration will be deemed complete when :
1. Integration will be complete when all CRUD events on Certificates and DIDs create an event on Soroban with the hash of the document or certificate. 

 2. All documents added to the Vector database will be tracked by a DID containing metadata referencing the document. 

Date of Completion : May 17, 2024

 

Domain Specific Model for Generation of Tests about Sorabon Blockchain

A domain model that generates exams about Soroban. A domain specific model will be created and used as a proof of concept for a more generalized application.  

The task will be complete when we can upload a document and receive a collection of questions and answers generated from document repository that cover the topics in the uploaded document. 

Date of Completion : May 10, 2024

Exams Grading and Proof-Of-Learning Certificate is Generated. 

Users will have the ability to take an exam and receive a digital certificate with their name and picture. (video verification is out of scope) 

The task will be complete when users receive a correct score for answers from the exam and receive a proof-of-learning certificate. 

Date of Completion: May 10, 2024

Entity Description

In 2017, Tim O'Brien - an ex-Googler, started a boutique blockchain development company called FuixLabs.com, focused on building blockchain infrastructure as a pioneer in developing algorithms and tooling for the blockchain, and implemented multiple AI and GenAI applications. As a sponsor of regional computer olympiads, FuixLabs.com has access to a talent pool of bright and promising graduates who become seasoned developers under the supervision of Tim O’Brien. Fuixlabs has worked as an active member of W3C working group in developing the VC-ED Education Certificate A list of our products includes:   AI driven document generation SAS product.   -AI driven recommender system.    -Worked with W3.org JFF and VC EDU to develop interoperability standards for education certificates. Tested our credentialing tool   -Trade Management system used by Singapore for paperless cross border trade  - Real Estate title and boundary application used by multiple countries in Africa.    - Blockchain IDEs and Tooling  - Protocol neutral turing-complete languages   - Supply Chain Management and Food Traceability Metaverse framework.  - Self Sovereign Identity using a full implementation of the DID specifications.  - Development of aBlockchain wallet   - A Javascript library for building Gated Brand Zones by inspecting Wallets for NFTs.