# Executive Summary The [[ABC curriculum]] is an [[ABC curriculum is integrative|integrative]] and [[ABC curriculum is inclusive|inclusive]] educational framework designed to prepare students in a world influenced by [[Generative Artificial Intelligence]] ([[GAI]]) technologies, which have greatly increased the **[[information density]]** for the general public in unprecedented ways. (See [[Participatory Design#PD in the Era of Generative AI]]) Open sourced [[GAI]] technologies are enabling personal computing devices with [[Large Language Models]] ([[LLM]]) to autonomously acquire, summarize, and verify extensive amounts of information across diverse fields such as arts, history, literature, mathematics, and sciences. As a result of the rapid increase in data processing or [[GAI]] capability, there has been a significant transformation in the way knowledge is recorded, accumulated, and refined in all [[workflow|workflows]]. Not only is it possible to create a personalized encyclopedia with a virtually infinite capacity to address a broad variety of issues, but it is also clearly becoming an operational advantage over individuals without access to such GAI-enabled **personalized knowledge** assistance. Open software and [[highly deployable data engineering techniques|data driven project management skills]] together hold the key to broadening **information equity**, easily deployed to more people with minimum technical and operational barriers. The rise of LLMs and their ability to generate highly relevant information by engaging with customized inputs has not only presented a challenge to traditional curricula but also changed how knowledge can be produced and transferred. [[GAI]]/[[LLM]] related innovation is causing a substantial change in the organization, distribution, and provision of knowledge to users. The [[ABC curriculum]] improves both individual and group learning activities by employing self-administered [[GAI]]/[[LLM]] interactive technologies by reducing the entry barriers and up-front engineering efforts for people who want to have access to up-to-date knowledge processing [[workflow|workflows]]. Besides presenting an organization of online and offline learning activities, this curriculum encompasses a personalized encyclopedia (see [[PKC]]), computationally updated learning outcome assessments, and a networked community of learners and content providers. The curriculum provides a comprehensive approach that combines theoretical knowledge, educational resources, and practical exercises to minimize obstacles and enhance learning by contextualizing theoretical knowledge in real-life situations. The ABC curriculum offers a comprehensive educational experience that empowers students with the skills to effectively utilize rapidly evolving GAI technologies. Additionally, this inclusive approach to utilizing data evidence from all angles assures that students possess awareness regarding the ethical implications and remain consistently informed on the risks of technology-assisted operations throughout their lifelong learning journey. ## Why ABC - addressing the challenges By leveraging [[GAI]]/[[LLM]] technologies—which index and compress enormous amounts of content knowledge stored on [[personal computing devices]]—currently, it is possible to circumvent information asymmetry, a systemic advantage that unfairly distributes benefits within established social structures. It tries to address the three crucial problems that challenge the way we learn: (More details in [[GASing and the Trinitarianism]]) 1. **Incoherent content organization:** The lack of a [[coherence|coherent educational program]] that effectively bridges the gap between abstract theoretical concepts and real-world applications, as seen in the disjointed teaching of theoretical subjects like logic, math, and physics from data-intensive subjects such as geography, literature, and physical education (see [[@PhysicsInformedMachine2024|Brunton 2024]]), obstructs the development of deep insights and diminishes long-term learning interests. It is crucial to consciously connect students with the complex interplay of diverse data types, teaching them how to organize all information with consistency and rigorous methods and up-to-date tools. (See [[Information Architecture]]) The failure to arrange different subjects within a cohesive, complementary framework leaves theoretical knowledge and practical skills misaligned, or at the very least, not presented in a unified, interconnected manner. This segmentation of disciplines forces learners to constantly shift their mental focus, obscuring the natural links and patterns that exist across all knowledge areas (see [[@MasterAlgorithmHow2018|Domingo 2018]]). 2. **No timely feedback:** A lack of skilled educators increases educational costs and hinders student success. Without enough teachers to provide timely, personalized feedback, students may misunderstand concepts or develop poor learning habits. We need scalable solutions to deliver prompt feedback across subjects. The internet's vast, unfiltered information further complicates learning, and the gap widens between students with timely guidance and those without. Utilizing modern technologies to improve the feedback mechanism in learning is also an emerging aspect of opportunities. (See [[Timeliness]] and [[Tutorial Experience]]) 3. **Lack of Relevance:** Students often encounter difficulties in connecting the skills and knowledge gained through traditional curricula with their practical applications in the real world. It is not uncommon for learners to find that the application of their newly acquired knowledge is not immediately evident, or that abstract theoretical concepts are not presented in a manner that seems relevant to their unique situations. This disconnect prevents them from engaging in real-life situations in a way that allows for a deep understanding of their educational achievements or areas for improvement within their specific social contexts. The adoption of [[GAI]]/[[LLM]] technologies can aid in presenting data and rephrasing theoretical concepts in formats that are more applicable and resonant with the learners' social and operational environments. (See [[Liveness]]) It is crucial to establish a **theoretically sound** educational initiative that is **operationally feasible** with the publicly available [[GAI]]/[[LLM]] technologies. It also needs to enable the general populace to conduct **[[Introspection# Introspection with LLM|introspection]]** with [[PKC|Personal Knowledge Containers]] ([[PKC]]) that are designed to serve individualized and self-sovereign intellectual interests. Additionally, the program should enable individuals to investigate emerging **[[external opportunities]]** that are accessible via the Internet. To enable individuals to safeguard their property and fundamental rights in our extensively interconnected society, it is imperative to provide them with an integrative curriculum that brings together mutually supportive **[[Archetypal]]** theories, **[[Broad|Broadly]]** accessible tools, and **[[Context|Contextualized]]** applications. (The name [[Why ABC|ABC]] was therefore chosen. See [[Why ABC]]). This methodology ought to afford the adaptability necessary for preserving diversity and tolerance. Since this inclusive learning approach requires theoretical insights, tool development, and localized contexts for applications, therefore, it must be developed through collaborative efforts under transparent communication and self-governance protocols, leveraging operational wisdom and infrastructures developed by the Free Software and Open Source communities. ABC curriculum is the program to iteratively refine theory, tools, and application templates like grooming a publicly shared **computable natural language** with [[GAI]]//[[LLM]] technologies. ## Who created ABC for whom? The [[ABC curriculum]] was developed by a [[transdisciplinary]] team consisting of educators, linguists, mathematicians, technologists, artists, cryptographers, and life-long learners. This team has extensive experience in designing learning programs across different periods and locations. Born in the [[Cloud Native]] era, ABC encompasses the entire life cycle of knowledge management, leveraging the latest technology to ensure scalability, resilience, and efficient operability by organizations anywhere. ABC employs interactive computational tools and automated theorem-proving languages to systematically acquaint students with profound technical concepts grounded in logically verifiable theoretical foundations. The curriculum offers a freely available [[Personal Knowledge Management]] ([[PKM]]) tool called [[Personal Knowledge Container]] ([[PKC]]). This tool includes software configurations and privacy-protecting methods to ensure [[@PurelyFunctionalSoftware2006|software deployability]] and [[data security]] (See [[Experimental-operational Symmetry|EOS]]). The ABC curriculum provides data-intensive project templates in the format of [[Cubical Logic Model]], enabling students to apply their knowledge in real-world contexts. This allows them to collaborate with diverse groups, potentially beyond their usual social circles, and gain firsthand experience of the curriculum's value both online and offline. In other words, the curriculum's continuous improvement is created by people who believe in the [[FSM|Free Software Movement]] and through open-source community conventions, allowing the public to access and contribute to its development. Put simply, anyone with an interest in utilizing it is encouraged to embrace it, ensuring that the ABC curriculum remains at the forefront of educational innovation in the Cloud Native era. ## What constitute ABC The [[ABC curriculum]] is an educational program that uses the open-source instruments to distribute content knowledge, as well as the relevant tools and community resources in an [[MediaWiki|Wiki-like]] encyclopedic package called [[PKC]]. The PKC serves as a platform for distributing data-intensive content knowledge, online references, and performing functions such as data backup, data transformation, and data analytics for content knowledge. This platform enhances the learning process by enabling data-driven educational activities, which are classified into three mutually supportive cognitive modalities. The [[Design Thinking]] module in the ABC curriculum helps students develop habits based on principles from cognitive science with self-administered data manipulation tools such as PKC. One can enhance their pattern recognition capacities by employing both cognitive abilities and algorithmically derived judgments. This allows individuals to get a broader perspective of factual information by utilizing intuition, tools, and methodologies. The [[Computational Thinking]] module provides learners with logically sound theoretical concepts and well-indexed terminology, known as [[namespaces]], alongside computationally condensed knowledge index like [[Large Language Models]]. This module is essential for understanding data organization and its value in knowledge management, particularly in the era of [[Generative Artificial Intelligence]] ([[GAI]]) that provides timely feedback with high [[information density]]. The [[Systems Thinking]] module in the curriculum provides a systematic approach for analyzing complex causal relationships. Within this educational framework, students explore the behaviors of various components and their interconnections, employing computational tools like [[System Dynamics]]. The three modalities in the [[ABC curriculum]] are interdependent, and designed to establish connections and enhance each other modality's efficacy. The curriculum prioritizes the significance of ongoing and adaptable learning for both students and institutions, underscoring the imperative of staying well-informed in this swiftly changing world of technology and information. It utilizes [[PKC]] to implement networked data services that facilitate learners in recognizing that learning is not a solo skill, but rather a collaborative network operation. A preliminary roadmap that covers the components in [[ABC curriculum]] can be found here in [[ABC Roadmap#Three-Layered ABC Curriculum in one diagram]]. The following diagram delineates how the [[Three Circles|three tracks]] of content knowledge [[Systems Thinking]], [[Design Thinking]], and [[Computational Thinking]] are mapped onto the three aspects of **[[Correctness]]**: [[Timeliness]], [[Accountability]], and [[Observability]]. ![[ABC_in_3by3.excalidraw|800px]] [Go to the Diagram](ABC_in_3by3.excalidraw) ## How does ABC work for you ABC emphasizes timely content distribution and interactive, [[reproducible]] learning environments using LLM-indexed knowledge content. It is **necessary** to have a **functionally symmetric** and **highly reproducible** software deployment platform in the age of GAI/LLM to conduct learning programs that are engaging and pervasive. This is how: ### Distributed, yet Reproducible The [[PKC]] platform plays a crucial role in facilitating the ABC curriculum. This open-source platform facilitates the monitoring of educational progress and assessment data by both students and instructors, ensuring transparency and convenient access. The presence of process transparency in the assessment results cultivates confidence among students. The ABC curriculum leverages the open-source nature of PKC to create learning environments that can be reproduced anywhere. The **[[reproducibility]]** of platform functionalities ensures that individuals, irrespective of their geographic location or operating system, can readily access the published educational materials, tools, and their configurations, provided they have access to contemporary web browsers. In the present era of [[GAI]]/[[LLM]], **platform function reproducibility** is particularly relevant. Platform reproducibility enables autonomous agents and agencies to execute localized LLM models and the refinement of Generative AI to organize and create content from various locally generated documents, including textual, image, audio, and video files. Utilizing a highly efficient content index using LLM and General AI technologies is an **essential requirement** for knowledge management in this era of massive automation. This feature not only simplifies the deployment of interactive learning activities but also lowers the cost of searching relevant content, enabling individuals and organizations to do more with much less. Therefore, making the technology available to all is a form of social fairness. See [[Experimental-operational Symmetry]]([[EOS]]). The lack of a universally adopted and easily reproducible knowledge management platform may result in the emergence of disparities in information access and distribution. Furthermore, the absence of distributed processing capabilities and decentralized approaches for gathering and exchanging knowledge content may also impede the development of resilient learning communities. ### Interactive Feedback and Personalized Assessment PKC gives students immediate feedback with interactive learning loops, distributed data storage, and behavioral analytics. Based on the interaction data with the system, students and instructors can adjust their learning strategies to improve comprehension and outcomes. This requires all students to have access to software with timely updates and **[[reproducible]]** software functionalities. Otherwise, it would be challenging to analyze performance data and provide systematic feedback based on collected data. ABC values student-driven over teacher-centered assessment. Instead, it tailors evaluations to students' measurable progress or regression. This lets students manage their education and create their unique learning journeys. Without an open-sourced data collection infrastructure with privacy protection features that are tested by a large number of participants, it is difficult to garner enough trust in the integrity and trustworthiness of the data collection process. See [[Tutorial Experience]]. ### Collaborative Content Filtering Collaborative filtering promotes curriculum community involvement. [[ABC curriculum]] provides a common pool of content knowledge and allows participants to customize the content selection using a common data format. This common structure helps learners find relevant learning opportunities and navigate the vast online information reservoir using the learning community's knowledge and expertise. Having a common and reproducible data platform to manage this **collaboration** process requires the networked software to have a high degree of **[[reproducibility]]** and autonomy. Otherwise, collaborative content filtering can be dominated by centralized data censorship controlled by a small collection of people, which defeats the purpose of **[[collaborative content filtering]]**. ## Where and whence does ABC reside The ABC curriculum systematically encodes content knowledge within a robust configuration management scheme. This scheme is detailed in the format of [[Function|functions]] as explored in [[@MathematicalMaturityThomas2017_1|On Mathematical Maturity]] by [[Thomas Garrity|Garrity]]. Under the [[Logic Model]], functions are crafted to provide input fields that facilitate the recall and application of three distinct models of computation. These include: 1. **[[Semantic Computation]]**: This model is about human written text, or textual content associated with other data assets that are represented in vector embeddings. This content knowledge is organized and accessible through a vector database for semantic-based content organization. This collection of content is known as the [[Prompt Collection]]. 2. **Executable Code**: Often associated with the concept of a [[Turing Machine]], this type of content knowledge involves procedural or executable aspects and is systematically documented in the [[Code Collection]]. 3. **Real-World Interactions**: This model addresses the realistic expectations of interactions in real-world spacetime contexts, which frequently involve concurrent interactions, typically explained through [[cellular automata]]. The related content knowledge is meticulously stored in the [[Data Collection]], complete with timestamps and version control labels to ensure accountable interactions among various procedures. The three collections of data content is managed in a [[Unified Configuration Management]] framework to ensure consistency and offer a content platform that abide to the principle of keeping a [[Single Source of Truth]]([[SSOT]]). To highlight the effectiveness of these computational models, the curriculum specifically incorporates [[Cellular Automata]] ([[CA]]) to demonstrate the transformative power of these models, owing to the significant benefits that [[CA]] provides. - **Spacetime Representation:** CA inherently models concepts within a spacetime framework, essential for representing complex systems and processes. - **Compositionality:** The discrete nature of CA aligns with how humans build complex concepts from simpler components, easing the process of human-machine collaboration. - **Computational Exploration:** CA models can be computationally analyzed and manipulated, enabling exploration of these complex concepts and supporting knowledge discovery. - **Alignment with Quantum Field Theory:** The computational formalism of [[Continuous Cellular Automata]]([[CCA]]) offers compatibility with [[Quantum Field Theory]], providing a theoretical foundation for representing the physical world and a very wide range of representable non-physical ideas. This approach actually relates back to [[Semantic Computation]] and [[Linear Algebra]]. Choosing [[Cellular Automata]] as a foundational representation makes it possible to express complex concepts within a framework that both humans and machines can manipulate, opening the door to unprecedented levels of understanding – anywhere and anytime. ### Web-based Anytime, Anywhere The [[World Wide Web]]'s beauty lies in its accessibility: the curriculum utilizes web browsers on portable computing devices and prioritizes open-source, customizable software. Through the [[CA Funnel]], the curriculum empowers learners to code interactive simulations, revealing how complex system-wide behaviors emerge from simple, localized rules – the essence of spacetime reasoning. See [[Experimental-operational Symmetry|EOS]]. ### Learning Concurrency: Telling stories across any scales Thinking and programming in [[Cellular Automata]] within the [[CA Funnel]] helps introduce learners to the concept of concurrency. Concurrency refers to the ability to handle multiple tasks or processes simultaneously. This fundamental principle underpins how reality operates. Just as countless events occur concurrently in nature, Cellular Automata models allow learners to experiment with parallel execution, fostering a deeper understanding of real-world phenomena. While this [[Lenia]] video effectively demonstrates the dynamic nature of [[Cellular Automata]], our long-term vision is a data pipeline that produces a continuous flow of interactive content. This content would be housed on a web-based platform like [[ABC Theatre]], enabling students and teachers to engage in collaborative [[storytelling]] at scale. The integration of multiple Personal Knowledge Containers (PKCs) ensures that generated experiences are rich, diverse, and personalized to each learner.  For more computable examples of seeing knowledge from interactive medium, see [[Ten Minute Physics]],[[@CreativeComputationJack2019|Creative Computation – Jack Rusher]], [[@FluidDynamicsFeels2021|Fluid dynamics feels natural once you start with quantum mechanics]]. ### Personal granularity of Spactime On a higher level of data content manipulation, [[PKC]] interactions allow for customization based on factors like cultural or geopolitical context, reflecting how [[CA]] patterns evolve from local conditions. Approved individuals gain access to these resources for personalized learning. [[CA]] principles are woven throughout the ABC curriculum: modules function independently yet interdependently, mirroring cellular structures. Data autonomy is achieved through [[Personal Knowledge Container]] ([[PKC|PKCs]]). Like cells in a CA, PKCs hold localized data and interact with their environment. This decentralized structure grants users control over their knowledge assets. ### Initial Knowledge Provisioning All instances of PKCs will receive a distribution of a comprehensive compilation of application-agnostic material, initially focused on [[Archetypal Theory|Archetypal Theories]] such as logic, mathematics, and natural sciences, and the common configuration and operational knowledge of [[Broad|Broadly Accessible Tools]]. The content organization reflects the inspiration of [[Cellular Automata]], wherein each cell possesses a shared set of abstract rules but functions according to concretized local information. In other words, [[Context|Contextualized Applications]] will be stored locally and only shared with locally interested parties when the context matches. Downloadable Large Language Models (LLMs) that include substantial content knowledge can be obtained and customized to operate within these PKCs. This functions as a primary reservoir of knowledge, assisting humans in their acquisition of knowledge, similar to how a [[Cellular Automaton]] develops and changes according to original circumstances and nearby interactions. ## When and How to start using ABC Upon installing a PKC and commencing note-taking, [[Topological Note-taking]] in particular, you are initiating the journey with [[ABC curriculum]]. By establishing a daily practice of taking notes and actively monitoring your own advancement, you are well on your path to reaping the advantages of the ABC curriculum. An iterative model originally proposed by [[Extreme Programming]] is shown here:  By allowing your [[PKC]] instance to share your data with others, you actively participate as a contributor in the ABC curriculum community. In other words, one can start participating in ABC curriculum when they start using a [[ToDo App]] that is connected with one or more [[PKC]]s in their local community. Also see [[The Eight Stages]] and [[Extreme Learning Process]]. # Conclusion ABC addresses the needs in modern education by tackling these three main concerns: ## 1. Coherent content organization: Traditional curricula struggle to keep up with the rapid advancements in data processing and the constant influx of new knowledge. In response to this challenge, the [[ABC curriculum]] offers a comprehensive solution by providing a unifying [[Archetypal Theory]] as [[@OutlineMathematicalTheory1977|outlined]] by [[Dana Scott]], that enables effective navigation of evolving circumstances. Central to this curriculum is the integration of inclusive computation and intuitive representation rooted in the Archetypal Theory originated from [[MIT quadrivium]]. Drawing from Field Theory, which underpins both classical and quantum mechanics, the curriculum accommodates diverse interpretations and representations. Archetypal Theory is presented through the geometrical analogy of Continuous Cellular Automata, a graphical model of computation that seamlessly aligns with Field Theory and [[Lattice Theory]]. This alignment grounds the curriculum in the notion of ordered entries and causal relations, providing a solid foundation for understanding complex data dynamics and facilitating adaptable information presentation. The curriculum's reach extends beyond traditional subjects by leveraging the power of an integrated [[Multi-modal Large Language Model]] ([[MLLM]]), enabling exploration and learning across diverse domains, such as visual and audio arts, literature, history, social sciences, and even sports. This interdisciplinary approach is enriched by semantic data filtering and generation technologies like LLMs, ensuring content is continually refined based on comprehensive computational models. See [[Unified Knowledge Representation#The ABC of Unified Knowledge Representation|The ABC of Knowledge Representation]] to see how content coherence can be systematically attained. As a result, the curriculum offers a structured and coherent progression rooted in the archetypal framework of [[Field Theory]], [[Continuous Cellular Automata]], and [[Lattice Theory]]. It empowers learners to construct mental models efficiently while embracing the rich, interdisciplinary knowledge facilitated by Large Language Models. ## 2. Timely feedback: Industrialized courses nevertheless rely on many instructors to give students timely and personalized feedback. This increases operating expenses and lowers learning efficacy due to variable teaching methods and student diversity. Poor and delayed feedback might cause incorrect conceptions and ineffective learning. These issues will become tougher to solve without a viable approach that provides fast input on a wide range of subjects on a huge scale. Education will become more unequal. ABC curriculum uses computational theories and technology to help practitioners establish [[Timeliness|time-based]] habits and constantly updated information and strategies to teach students and instructors learning objectives. Specifically, this curriculum encourages data-rich daily journal writing and goal-oriented music-listening ([[EuMuse]]) for habit-forming and multi-modal learning (learning with music, literature, games, and exercises, etc.). ABC curriculum uses appropriate **privacy-protecting** techniques and content referencing technologies ([[Hyperlink|hyperlinked notes]]) to track individual and group performance records utilizing a visible metrics dashboard for advanced topics, delivering timely and contextualized feedback. However, **only with the power of LLM-based multi-modal automated reasoning** can we **systematically analyze** the vast amount of data collected and **generate highly relevant, personalized feedback** at scale. These technologies enable systematic content relevance validation, paving the way for a transformative curriculum. Recent breakthroughs in personalized computing technologies have made it possible to develop such a curriculum, one that dynamically adapts content organization for diverse learning contexts, achieving [[coherence]] and [[timeliness|timely feedback]] to individuals at scale and rendering it both computationally and operationally viable. ## 3. Personal and Contextualized Relevance: Learners in the dynamic world of [[GAI]] and [[LLM]] frequently face the challenge of translating newly acquired knowledge or skills into real-world applications, which is facilitated by these technologies' ability to reorganize content quickly. (To mobilize learners sharing knowledge, the [[Challenge Designer]] and [[Mission Executor]] role play is critical.) The inability to identify any information's immediate, practical applications, or its direct [[relevance]] to ongoing projects or societal contributions, can stifle effective engagement with real-world scenarios. This disconnect limits students' ability to fully recognize their strengths and identify areas for improvement in a rapidly changing technological landscape. The absence of a centralized repository for personalized learning progress complicates the process of locating pertinent information. Personal-scale adaptive computing advancements have enabled individuals to process personally relevant data sets with ever-lower barriers to entry. To establish relevance with adequate discipline, learners must now be immersed in the use of data-intensive tools as part of their daily data processing activities. The [[ABC curriculum]], which employs LLM-based technologies, includes strategic project templates such as the [[Cubical Logic Model]] as a practical planning tool. This approach helps students filter and prioritize information and **[[social activities]]**, ensuring direct alignment with the practical and theoretical skills needed to make learning experiences relevant to their daily lives. Furthermore, this curriculum aims to facilitate the incorporation of applied learning opportunities that are closely related to academic content, as well as the promotion of connections within a large, **networked community**. This integration not only helps students understand the practical implications of their studies but also gives them the personalized tools they need to sort the relevance across their personal knowledge content systematically. The three strategic directions mentioned above are critical in improving education quality in an era dominated by [[GAI]] and [[LLMs]]. Citizens in this new era must be prepared to effectively use data-driven automation tools, develop skills for adapting to emerging data processing technologies, and understand how to protect their data assets. An effective curriculum must address the interplay of content [[coherence]], timely feedback, and relevance to the learners' specific contexts, ensuring that these elements are addressed together rather than separately. The traditional method of disseminating knowledge through a centralized, bureaucratic educational system may no longer be viable without the development of adaptive educational programs, personalized and automated learning tools, and content structures that are tailored for a broad, decentralized audience rather than being imposed from the top down. ## Curriculum as an order-preserving Life Style The [[ABC curriculum]] was born in the Cloud Native era, a time characterized by computationally intensive processes and interconnected networks. Its foundation lies in the philosophical bedrock of movements like the Free Software Movement, which champions open access and collaboration. This curriculum is designed to preserve intellectual discoveries and avoid centralized biases, drawing inspiration from the scalability and decentralized nature of the Internet. At its core, the ABC curriculum introspects the benefits and fundamental philosophies behind the ideas of freedom and justice, emphasizing their distributive nature. These principles act as guiding lights, ensuring that the curriculum not only embodies an order-preserving lifestyle but also fosters the emergence of new ideas and new life forms. More than just an academic offering, the ABC curriculum is an intellectual journey amplified by the [[GAI]]/[[LLM]] and personalized data sovereignty movements. Students gain theoretical insights, practical skills supported by robust data processing platforms, and an adaptive mindset crucial for success in the Generative AI era. It seamlessly integrates [[Archetypal Theory]], [[Broad#Broadly accessible tools|Broadly Accessible Tools]], and [[Context|Contextualized Applications]] to provide an irreducible, comprehensive educational experience. The [[ABC curriculum]] is a meta-structure, designed to be replicated easily and enable bootstrapping in resource-constrained environments. Its domain independence and cross-platform [[reproducibility]] encourage open collaboration and continuous learning, preparing individuals and organizations to thrive in a data-driven society. Before diving into the [[ABC curriculum]], it's recommended to start with the [[ABC Roadmap]]. For people to immersively experience what needs to be learned in this modern networked society, it is essential to fully immerse in a game-based learning environment. This leads to the notion of designing a [[Meta Game]]/[[時空緒言]] that is particularly focused on using contextualized technologies in a socially and physically engaging way. # Note [[Why ABC]] # References ```dataview Table title as Title, authors as Authors where contains(subject, "ABC Curriculum") or contains(subject, "ABC curriculum") or contains(subject, "Master Algorithm") or contains(subject, "Active Learning") or contains(subject,"Three Circles") ```