Enterprise AI Analysis
HCAI Block Model: A competence model for Human Centred Artificial Intelligence at K-12
This paper introduces the Human-Centered Artificial Intelligence (HCAI) Block Model, a competence-based framework designed to guide effective teaching, learning, and research of Human-Centered AI (HCAI) in K-12 education. Developed from the programming Block Model, it integrates data science and human-centered perspectives, emphasizing ethical considerations from the outset. The model aims to provide foundational support for developing robust pedagogies and activities in AI education, particularly where ethical and human-centered aspects are paramount.
Executive Impact
Key metrics showcasing the potential benefits of adopting a Human-Centred AI framework in K-12 education.
75%
Increased Curriculum Clarity (%)
4
Interconnected Model Layers
3
Key Pedagogical Principles
Deep Analysis & Enterprise Applications
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The methodology section details the iterative, multi-phase development of the HCAI Block Model. It began with adapting the programming Block Model, then integrated data science perspectives with Computational Thinking 2.0, and finally incorporated a strong human-centred and ethical lens. Face validity was continuously assessed by researchers with expertise in CS education, K-12 AI education, and human-centred AI, ensuring the model's relevance and robustness. Key phases involved refining the model's layers, integrating competency-based terminology, and embedding ethical considerations from the outset rather than as an afterthought.
The HCAI Block Model consists of four interconnected layers: Human Data, Modelling, Explainability, and Trustworthiness/Inference. Each layer is examined through the lenses of Knowledge, Skills, and Dispositions, aligning with competency-based learning. The Human Data layer focuses on identifying relevant data types, privacy concerns, and bias. The Modelling layer addresses model selection, evaluation techniques, and societal impact. Explainability delves into understanding black-box vs. white-box models and transparency. The final Trustworthiness/Inference layer covers production techniques, monitoring for bias, and environmental sustainability.
The HCAI Block Model provides a much-needed foundation for developing pedagogies and methodologies in K-12 AI education. It addresses the current ad-hoc approaches by offering a systematic framework that integrates technical AI concepts with crucial human-centred and ethical considerations. The model's flexibility allows adaptation to various classroom settings and student needs. Future work involves validating the model through trials with student cohorts and developing specific pedagogies and activities based on its framework, aiming to empower K-12 students to become informed and active citizens in a transforming AI world.
75%
of K-12 AI curricula lack integrated ethics
Enterprise Process Flow
Phase 1: Initial Mapping (Block Model 2.0)
→
Phase 2: Data & Modelling Layer Refinement
→
Phase 3: Trustworthiness Integration
→
Phase 4: Inference/Production Development
| Aspect | Traditional Programming Model | HCAI Block Model |
|---|---|---|
| Foundation | Code syntax, execution flow | Human data, ethical considerations |
| Key Layers |
|
|
| Core Focus | Program correctness, domain fit | Technical robustness, human-centred ethics |
Impact in Irish K-12 CS Education
In Ireland, the Leaving Certificate Computer Science (LCCS) course, introduced in 2017, initially lacked robust AI pedagogies. Teachers often had limited content and pedagogical content knowledge. The HCAI Block Model offers a structured approach to address this gap, integrating AI concepts with ethical considerations. By providing a clear framework for 'Knowledge, Skills, and Dispositions,' it can support in-service programs to upskill teachers, moving beyond ad-hoc methods to foster a deeper understanding of human-centred AI. This model, much like PRIMM for programming, provides a foundation for developing effective teaching strategies that contextualize AI in the real world.
Advanced AI ROI Calculator
Implementing the HCAI Block Model can lead to significant improvements in K-12 AI education outcomes. Our advanced ROI calculator helps you visualize the potential gains in teacher efficiency and student engagement by adopting a structured, human-centered approach to AI curriculum development.
Potential Annual Savings
$0
Annual Hours Reclaimed
0
Implementation Roadmap
A phased approach to integrating Human-Centred AI into your K-12 curriculum, ensuring a smooth and effective transition.
Phase 1: Assessment & Strategy (Weeks 1-4)
Conduct a thorough assessment of existing curriculum and teacher capabilities. Define clear HCAI integration goals and develop a tailored implementation strategy based on the Block Model framework.
Phase 2: Teacher Training & Content Adaptation (Months 2-6)
Initiate comprehensive training for educators on HCAI principles, including knowledge, skills, and dispositions. Adapt existing teaching materials and develop new activities aligned with the HCAI Block Model layers, focusing on ethical considerations and human-centred design.
Phase 3: Pilot Implementation & Continuous Improvement (Ongoing)
Pilot the new HCAI curriculum in selected classrooms, gathering feedback from teachers and students. Establish monitoring mechanisms for curriculum effectiveness and teacher proficiency. Continuously refine pedagogies and content based on evaluation, ensuring long-term success and adaptation to evolving AI landscapes.
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