not approved
[selfdriven|5] Path to Decentralised Self-Driven Learning Communities (Sociological Research/Systems Theory)
Current Project Status
Unfunded
Amount
Received
₳0
Amount
Requested
₳32,000
Percentage
Received
0.00%
Solution

Examination of social dynamics, educational principles, and community engagement of DAOs and Web3 communities identifies root causes of shortcomings, social challenges and governance deficiencies.

Problem

The Cardano ecosystem lacks a solid theoretical and sociological foundation for achieving and building decentralisation in aspects of education, organisation and learning communities.

Impact Alignment
Feasibility
Value for money
[selfdriven|5] Path to Decentralised Self-Driven Learning Communities (Sociological Research/Systems Theory)

Please describe your proposed solution.

Through this research, deep examination of social dynamics, educational principles, and community engagement can identify the root causes of shortcomings as well as micro- and macro-sociological challenges and deficiencies. It enables the development of comprehensive frameworks, strategies, and recommendations to guide the community in realising their social impact goals and establishing a strong educational foundation within the Cardano ecosystem, fostering sustainable growth and positive social outcomes.

The theoretical foundation of the study consists of the sociological systems theory (Luhmann) and the structuration theory (Giddens). The analysis is accompanied by socio-philosophical implications on the topics of decentralisation and democracy as well as educational aspects in the area of the foundation of communal values and open societal principles. Through the theoretical foundation, communities are to be empowered in the long term to develop their own self-driven learning and development path and to build robust community structures guided by the maxims of decentralisation.

Please define the positive impact your project will have on the wider Cardano community.

The concept of a Path to Decentralized Self-Driven Learning Communities, when infused with the latest technological advancements such as Self-Sovereign Identity (SSI) and Decentralized Identifiers (DIDs) heralds a transformative era in education. This paradigm shift allows for the creation of learning environments where individuals take charge of their educational journey, empowered by technologies that ensure security, autonomy, and portability of their academic credentials.

In these communities, learners are no longer bound by traditional educational structures and geographical limitations. Instead, they have the freedom to curate their learning experiences from a global pool of resources. The decentralization aspect ensures that learning is democratized, making high-quality education accessible to a broader audience irrespective of their location or background.

The integration of these technologies in learning communities paves the way for a more inclusive, flexible, and learner-centric educational model. It encourages lifelong learning, as individuals can continually update their skills and knowledge, with their achievements being recognized and easily shared with potential employers or educational institutions. Our Self-driven approach aligns perfectly with the future of work, where adaptability and continuous learning are key.

What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?

The selfdriven team supporting the projects have a wealth of experience in education and technology.

The selfdriven Foundation was founded in 2019 and the team is highly engaged within the Cardano community. It has a robust organisational structure.

Benjamin Heurich (Co-Founder) is a university lecturer and researcher in the departments of Sociology and Educational Sciences with a focus on digital education, educational equity and internationalisation.

Mark Byers (Initiator & Co-founder) is a qualified Engineer and has 30+ years experience delivering internet based high-grade solutions to market, including the vision to co-found the entityOS.cloud service in 2000.

Bence Lukacs (Co-Founder) is a former sports trainer and teacher and brings experience in school development, as well as teacher education projects and Media Education research.

Damian Noonan (Co-Founder) has over 20 years experience delivering technology projects as part of strategic transformation initiatives, with expertise particularly Salesforce, MuleSoft and its emerging technologies. As co-founder of recently acquired Tquila ANZ, Damian has experience in building teams and delivering enterprise solutions.

Diverse advisory team with over 100+ years experience

Advisory team includes Mario Altimari (Co-Founder) eLearningDAO.

About The Team

About The Organisation

What are the key milestones you need to achieve in order to complete your project successfully?

1/ Research Objectives and Literature Review (3 weeks)

  • Define the research objectives, focusing on social dynamics, educational principles, and community engagement within the Cardano ecosystem
  • Conduct a thorough literature review on the identified topics, exploring existing research and theories in sociology, decentralization, and education
  • Analyze the literature findings to identify the root causes of shortcomings, micro- and macro-sociological challenges, and deficiencies within the Cardano ecosystem

>2/ Framework Development and Analysis

  • Develop comprehensive frameworks, strategies, and recommendations based on the analysis of social dynamics, educational principles, and community engagement
  • Apply the sociological systems theory (Luhmann) and the structuration theory (Giddens) as the theoretical foundation for the research
  • Conduct socio-philosophical analysis, exploring the implications of decentralisation and democracy, as well as educational aspects related to communal values and open societal principles

>3/ Data Collection and Analysis

  • Collect qualitative and quantitative data through surveys, interviews, and analysis of existing datasets to gather insights on social dynamics and community engagement within the Cardano ecosystem
  • Apply appropriate research methodologies to analyse the collected data and identify patterns, trends, and challenges related to education and community development
  • Integrate the data analysis with the theoretical frameworks developed in Milestone 2 to validate and refine the findings

>4/ Recommendations and Strategy Formulation

  • Synthesise the research findings, theoretical frameworks, and data analysis to develop comprehensive recommendations and strategies
  • Consider the long-term empowerment of communities through self-driven learning and the establishment of robust community structures guided by decentralisation principles

>5/ Finalise Research and Reporting

  • Incorporate feedback and revisions based on the evaluation of the research findings, theoretical frameworks, and recommendation
  • Finalise the research paper, ensuring coherence, logical flow, and clarity of the presented analysis, frameworks, and recommendations
  • Final video report
  • Preparation of Open Access publishing

Who is in the project team and what are their roles?

  • Benjamin Heurich (Review)

Over 10 years of experience as a researcher and lecturer in the departments of sociology and educational sciences with a focus on digital education, educational equity and internationalisation. Several years of experience in digital branding and international marketing consulting. Current research and activity areas include DeSci, Open Science and Trust.

  • Mark Byers (Tech Lead)

Co-founder of entityOS.cloud, an internet cloud services platform founded in 2000.

Co-founder of slfdrvn.io (this project)

30+ years experience in information technology.

Mechanical Engineer

  • Damian Noonan (Tech Design)

Damian has over 20 years experience delivering technology projects as part of strategic transformation initiatives, with expertise particularly Salesforce, MuleSoft and its emerging technologies. As co-founder of recently acquired Tquila ANZ, Damian has experience in building teams and delivering enterprise solutions.

  • Bence Lukacs (Design)

Many years of experience in e-Learning Instructional Design and Media Didactics. Driven by a passion for science (particularly Open Science and Decentralized Science), human learning, and digital worlds he's researching, conceptualizing and building decentralized education projects.

Please provide a cost breakdown of the proposed work and resources.

  • Research outline and compilation: 4,000 ADA
  • Refining models, theories and frameworks: 4,500 ADA
  • Empirical Work, analysing theories and collecting data: 10,000 ADA
  • Evaluation/Review/Feedback: 3,500 ADA
  • Final Submission, Publishing, Reporting: 10,000 ADA

How does the cost of the project represent value for money for the Cardano ecosystem?

  • Generally leveraging the considerable existing investment into selfdriven Framework & Services.
  • All funds are applied directly to community returns as core framework exists.

Developing a theoretical framework as a basis for both scientific and practical work is tremendously beneficial for the ongoing evolution and expansion of the Cardano community. Such frameworks, when robustly constructed, offer a foundation that can be continually refined, evaluated, and assimilated within the community over both short and long terms. This is achieved through rigorous research, experimentation, and peer-review processes.

The researched frameworks and methodologies are designed to be dynamic, allowing for continuous integration and iteration by the entire community. This decentralized approach to scientific development ensures that the frameworks and methodologies not only gain wider acceptance but also undergo continual enhancement. This is made possible through empirical testing conducted by community members themselves, fostering a collaborative environment where practical application informs and improves theoretical constructs.

close

Playlist

  • EP2: epoch_length

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  • EP1: 'd' parameter

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  • EP7: max_tx_size

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