Learning as a Pattern that Connects

r3.0
14 min readJan 5, 2022

by Anneloes Smitsman, PhD, EARTHwise Centre, and Ralph Thurm & Bill Baue, r3.0

This is part 6 of a series of 9 articles to promote the just released r3.0 Educational Transformation Blueprint, discussing the profound changes that are needed to educate ourselves and next generations on how to imagine and come to a regenerative & distributive economy. At the end of this series, r3.0 is inviting readers to a free 2-hour online workshop on January 26, 2022, 4–6pm CET. You can already register by sending an email to hello@r3–0.org, mentioning your full name, affiliation and country you will be joining from.

What feedback do you create and utilize for learning about yourself, life, and the worlds and systems you form part of? All living systems feedback and feedforward the complexity of life in meaningful and holistic ways. Life is essentially a connective pattern. Yet many of the mainstream educational systems do not facilitate learning as a pattern that connects. Instead, children from an early age are bombarded with data and sensory stimulations that disconnect us from the connective patterns of life. It is thus not surprising that increasingly more people, and especially children and teenagers, suffer from anxiety, addiction, depression, and developmental disorders.

The explorations of this article are based on chapter 6 of the r3.0 Educational Transformation Blueprint, which launched 7 September 2021. This Blueprint includes 7 Transformative Learning Perspectives for Regeneration and Thrivability, the fifth of which is “Learning as Connection” and the focus of this article. To read a brief introduction of the Blueprint, click here.

Learning as Connection

Image design by Anneloes Smitsman for the r3.0 BP9 Educational Transformation Blueprint

Learning as Connection serves as an essential inquiry into the future trends of education, including the role of digital technologies and tokenization. It also provides a deeper inquiry into the role of assessments and evaluation, and how to create meaningful feedback for the ecology of learning as a whole. We’ve explored Learning as Connection through the following perspectives, which are further explained below:

  1. Learning as a Connective Pattern.
  2. Digital connections and the role of AI and VR.
  3. Learning Feedback — Rewards, Tests, Evaluation, Tokenization.

1. Learning as a Connective Pattern

Learning is a connective pattern, just like life is a connective pattern. How can we best honor these connective patterns in the ways we design, facilitate, and evaluate education? Unfortunately, many children learn from an early age to break the patterns that connect us to the larger ecologies of life. For example, many children have no idea where the milk they drink on a daily basis comes from. Furthermore, many have never been on a farm or touched a cow, sheep, or goat and formed a personal relationship with the animals that serve as their ‘food supplies.’

Learning and development is a complex and non-linear process (see Gibson and Pick, 2000; Fogel, 1993; Smitsman and Smitsman, 2020). Infants start developing their skills by exploring and applying their sensory capacities and generating their own feedback for learning. From birth onwards, children are natural learners. If education does not foster and enhance our innate learning potentials, there is something wrong with the ways we have conceived and designed education.

Learning as a Connective Pattern provides a systemic focus for reducing and removing (as much as possible) the artificial silos and factions that we have imposed on the many processes of learning and development.

By exploring how we form part of the connective patterns of life it can also help heal the sense of isolation and fragmentation that so many people are suffering from.

Furthermore, becoming aware of phenomena and events as patterns can help to shift the divisive patterns of blame and polarization. This deeper systemic understanding of causation and emergence is at the heart of what a living system’s based education seeks to foster.

2. Digital connections and the role of AI and VR

The COVID-19 pandemic has significantly increased the uptake of digital learning technologies around the world. Yet, this crisis has also revealed many challenges and significant gaps and inequalities. Many schools and universities from around the world had to shut down their physical learning facilities in early 2020, without the financial and technological means to prepare for transitioning to distant learning modes. Especially in countries of the Global South, the impacts of this pandemic are long and far-reaching.

The inequality of access to digital devices and internet services — coupled with a lack of digital skills — has meant that many children and youth around the world have not been able to continue their education. Research by Avenesian et al. (2021, p.1) suggests that “more than 30% of schoolchildren globally cannot be reached by remote learning policies due to the high variation in access to assets for remote learning that exists within and between the world regions.”

The inequality and opportunity gaps between the richer and poorer nations have grown even more starkly during this whole crisis.Especially for children and youth from rural communities and poorer households — they are at the greatest risk of being left behind.

Even though access to quality education is considered a basic human right, the realization of this right in times of crisis requires whole new approaches and further resources. Digital technologies for remote learning can play a positive role if carefully and equally applied, and if applied in way ways that do not impair children with physical needs. Especially for younger children, remote learning cannot replace the physical educational support they require. This raises another challenge of digital learning, and that is the modus of connection, which to many people feels distant.

While the world had to adapt to new forms of connection, the rates of suicides, depression, and mental problems have increased significantly from the onset of the Pandemic. Although it may appear as if our human world has never become more connected, from a psycho-social perspective it is to be noted how increasingly more people feel isolated and alone. Lost in technologies that do not provide the warmth and connectivity of human contact, and scared of technologies that many do not understand, and yet bring significant consequences to their lives.

Our human societies increasingly require that people shift over to digitally facilitated connections, for which new forms of meaning and sense-making will need to be developed (Introna, 2017). Furthermore, in absence of visual and physical feedback, it can be difficult for people to sense or understand how they are being received and understood by others.

Digital technologies for social usage come with a real risk of trivializing and distancing relationships. When the reciprocal basis of digital relationships becomes “economized” this further increases the risk of moral disengagement from social life (see Bandura 1991, Willard, 1998). Willard (1998) further states that: “Technology can act to dehumanize others because of the lack of affective or tangible feedback.”

Our sense of community is greatly enhanced by creating common physical experiences that are meaningful and supportive, which cannot be surrogated by digitally facilitated connections. However, by better understanding how communities thrive and flourish, this can be digitally assisted and supported.

By being aware of potential adverse effects as well as advantages of digitally facilitated connections for collaborative learning and co-working, education can and must play an enabling role in developing digital literacies during this time of rapid change. Education for digital competencies should enable:

  1. Awareness of the potentially positive and negative sides of digital technologies, including AI and VR learning modes.
  2. Development of digital literacies of children from an early age, by getting them familiarized with many of the existing and new digital technologies that form part of the demands and opportunities of our digitizing worlds.
  3. Exploration for how digital learning modalities and digitally facilitated evaluation can create new empowering learning experiences, and better feedback for the various learning and developmental needs of diverse groups of students.
  4. Collaboration between educational initiatives and institutions from around the world to more effectively reduce the economic, social, technical, and competency gaps between people and countries.

In their review of AI applications in education, Zhang and Aslan (2021, p.9) noted how, “AI technologies have great potentials in education, in particular, to increase access to learning opportunities, to scale up personally customized learning experiences, and to optimize methods and strategies for desired learning outcomes.”

AI and VR applications in education will only increase. Hence, we highly recommend educators get acquainted with these developments, so they can guide their students appropriately. Working group member Alexander Laszlo noted how, “Smart Data, IoT, deep AI, VR, AR, AE (artificial emotion) are making great strides and have serious implications for societal development in harmony with the rest of life and living relationships. Of these, augmented reality (AR) may hold the greatest potential for impacting learning contexts.”

This also raises an interesting opportunity, namely how to purposefully design digitally facilitated experiences of an interconnected world. For example, biology videos about the human body can show children through animated movies what happens inside the human body. VR and AE facilitated learning can guide students inside in making decisions and exploring the qualities of and processes of life. Such developments require a careful design process through life-centric systemic thinking. These new developments in educational technologies also require the development of a new kind of ethics for guiding and discerning the choices, risks, and opportunities — free from interferences of economic market interests.

Gamification of learning can also provide many new opportunities. Working group member Kurt Barnes mentioned: “Having worked in the fields of education for many decades it is my experience that teachers need to become literate about IT and other digital technologies — in particular the gamification of education for greater learning engagement. VR is already being used by Medical schools around the world for training students to perform the most complex surgeries and treat rare diseases, similar also in Aviation schools for pilot training. Application to other fields of learning can greatly benefit from these new learning technologies. Furthermore, teachers should learn how to create their own practical teaching games in the same manner that one makes a PowerPoint presentation.”

Working group member Remko Van Der Pluijm added: “AI, VE, and AE can also be applied the form of feedback loops in classrooms in order to create immersion into a topic, especially to immerse in certain historical events and to experience these situations. Truly being able to experience certain natural phenomena (akin to IMAX movies and their VR-relatives) might also help to foster empathy with students.”

On a cautionary note, we do want to emphasize how the rise of artificial intelligence, and new forms of data imperialism, can also pose many known and unknown dangers. AI facilitated algorithms are creating and processing data in ways that human brains can’t. We offer the following questions for exploring this topic further:

  • How do we process the feedback and data that many AI programs provide to us?
  • Who is controlling what we see, how long we see what we see, and what we will conclude from what we are exposed to?
  • What data are we providing and to whom, and what influence are we allowing in educational environments by AI-enhanced programs, in a world where data is becoming the new gold to mine for?

Historian and philosopher, Yuval Noah Harari warns how AI algorithms make decisions in fundamentally different ways than humans (Harari, 2021). Learning happens by processing data or information in a variety of ways, and this involves decision-making from the most subtle to the deeper systemic. If data processing and decision-making are increasingly allocated to algorithmic programs, then are we in some ways devolving or reducing our learning capacities?

A decision that we make ourselves, through conscious deliberation and reflection, carries a very different impact compared to decisions that we follow or are made by others.

What and who is the invisible ‘other’ that we are in the process of co-creating through rapidly developing digital technologies?

This digital ‘other’ is incapable of the kind of understanding that we attribute to consciousness. As mentioned by physicist Sir Roger Penrose, artificial intelligence is in fact a form of ”artificial smartness”, which is not the same as intelligence. He also states that consciousness is not merely computational or algorithmic and has to do with understanding, which is precisely what is lacking in AI (Penrose, 2020).

3. Learning Feedback — Rewards, Tests, Evaluation, Tokenization

Learning and development is fundamentally a process that creates as well as requires feedback. Without appropriate feedback, living systems cannot evolve or learn. Even artificial systems, such as AI-based programs, require data inputs and feedback in order to learn.

Learning for standard exams often becomes a major barrier to transformative learning (see case-study research in Smitsman, 2019). Rigid national educational policies often dictate what students need to learn and how learning outcomes are assessed and rewarded, for both students and teachers. Similar barriers can also be observed in organizational learning, where standardized evaluations and goal-oriented reward schemes create a culture of result-based learning that hinders the development of essential transformative capacities that are process-oriented.

Educational transformation requires reviewing and adjusting many of the learning feedback mechanisms of current evaluations, assessments, tests, exams, remunerations, and appraisals. In particular to assess whether these mechanisms provide the appropriate feedback for learning and development for regeneration and thrivability.

Many standardized and result-oriented types of assessments and accreditations create cultures that inhibit the development of transformative capacities and systemic understanding. Especially, where assessment relies heavily on preconceived and predefined learning outcomes that only value, or reward, what is expected.

For educators, we strongly recommend implementing the 7 Learning Perspectives of the r3.0 Educational Transformation Blueprint in learning evaluations and assessments. Working group member Bas van den Berge suggested that quantitative forms of standardized testing often miss capturing the more qualitative aspects of learning and development, which also tend to be more subjective.

We, therefore, recommend designing evaluations and assessments in ways that are inclusive and supportive for varying forms of learning and development — including embodied, experiential, imaginal, cognitive, intuitive, and sensory. Furthermore, we recommend the inclusion of dynamic feedback over time, rather than singular tests and evaluations in snap-shot-moment, as is often the case in standardized testing.

Educational transformation requires a major revisioning and redesign of the role of examining bodies and accreditation agencies, to shift away from control and management of learning outcomes, and move towards the facilitation and nurturing of learning via experimentation, play, and experiential risk-taking.

This analysis of the shortcomings of current evaluation and incentivization systems aligns with analyses in other r3.0 Blueprints, most prominently the Value Cycles Blueprint. It critiques the evaluation modality exemplified by the Impact Valuation framework, which “evaluates” impacts through “valuation,” or placing a monetary “pricetag” on impacts that then allows for a kind of “marketplace” of impact assessment. Unfortunately, this mechanistic approach defies the physics and principles of holism, whereby impacts on vital capital resources are not “fungible” and thus cannot be offset or traded like commodities on an exchange: i.e. a positive impact on gender diversity cannot undo negative impacts on water quality.

As well, the Value Cycles Blueprint asserts the need for “true” incentivization that likewise takes a holistic approach, linking compensation and remuneration directly to respect for the carrying capacities of capitals that are vital to support wellbeing. This approach is a clear analog for education, where incentivization must not be divorced from holistic realities (as standardized testing does). Instead, education must incentivize understanding and respect for the holistic, interconnected nature of complex adaptive living systems.

Tokenization, SEEDS as case-study

The case study of SEEDS can serve to explore how tokenization through digital currencies and gratitude tokens for regenerative education can scale and accelerate the necessary engagement for our societal transformation. “SEEDS” is an acronym that stands for, Sowing Ecological, Equitable and Decentralizing Societies — a movement of movements serving the Regenerative Renaissance by providing support, systems, and tools for a thrivable world. “Seeds” is the name given to the utility tokens used within the SEEDS ecosystem.

SEEDS is an open-source decentralized financial ecosystem and governance platform, owned and governed by the citizens who use it, to empower humanity and heal our planet. SEEDS supports the myriad of change-maker movements by providing tools and finance through its digital regenerative currency called ‘Seeds,’ for harnessing the power of wealth creation and scaling global coordination of the Regenerative Renaissance Movement.

Seeds tokens are used to reserve bandwidth for transactions on the blockchain that underpins SEEDS (the network), and to access SEEDS services and features. SEEDS also allocates gratitude tokens to its members and accordingly tokenizes the behavior of sharing gratitude as an active expression of appreciation, which is acknowledged as adding system value.

SEEDS architecture of systems, tools, and governance processes are based on leading-edge protocols, tools, and systems for decentralizing economics and governance, inspired by the self-organizing holonic architecture of life. The three evolutionary principles of life that are mentioned in article 3 of this series, are explicitly incorporated in Article 3 of the SEEDS Constitution(for which I served as an architect).

These evolutionary principles are further implemented in Article 6 of the SEEDS Constitution, which lists 13 architecture protocols to provide guidance for the development and evolution of the SEEDS design, code, tools, systems, education, and governance:

  1. Openly Share Knowledge — Open Source Code.
  2. Enable and Encourage Choice — Citizen Governed.
  3. Include Spaces to Dream — Architect from the Future.
  4. Capture Carrying Capacities — Operate Within Sustainability Thresholds.
  5. Increase Carrying Capacities — Improve Systemic Resiliency and Health.
  6. Encourage Diversity — Strengthen Evolutionary Coherence.
  7. Communicate Inclusively — Create Resonance and Alignment.
  8. Be Transformative — Develop Capacities Together.
  9. Collaborate for Thrivability — With the Patterns that Connect.
  10. Be a Good Future Ancestor — Allocate Prosperity Equitably.
  11. Design in Fractals — Scale Holistically.
  12. Enhance Fertility — Create Abundance Regeneratively.
  13. To be Created … — Open Space to Dream into Together.

Through the SEEDS Constitution, the founding principles for SEEDS to become an evolutionary learning ecosystem are also embedded, and rewarded through the SEEDS tokenization mechanisms. Accordingly, SEEDS goes well beyond a regenerative financial system in terms of ‘just being money.’ It also provides architecture, tools, education, and systems for rethinking and redesigning our societal models and systems. Rather than utilizing the market as the primary distributor of collective wealth, SEEDS aims to consciously program into economic systems what people collectively determine as contributions to the wellbeing of our civilizations.

The governance system of SEEDS and its HYPHA DHO platform also serve as illustrative examples of holarchic self-organizing and decentralized systems. Similar decentralized modes of organization are emerging throughout the Regenerative Economics movement and related initiatives, which foster very different learning capacities compared to standardized education.

Holarchy is a fundamental quality of the architecture of living systems. Holarchic organization is a natural and an innate organizing principle of the universe itself. Living systems do not impose organizational structures, like many of our human systems do, nor are their organizational dynamics artificially controlled. Instead, the organizational structures and dynamics of living systems emerge from nonlocal fractal potentials that become localized within the evolving structures of their systems, and the systems they form part of.

If we are to create regenerative economies for thrivability through transformative education, it is essential that we start to embed these living system principles in our educational, governance, and economic systems.

Source: Extracts from chapter 6 of the r3.0 Educational Transformation Blueprint.

Other Articles in this Series

References

Avanesian, G. Mizunoya, S. & Amaro, D. (2021). How many students could continue learning during COVID-19-caused school closures? Introducing a new reachability indicator for measuring equity of remote learning. International Journal of Educational Development, Volume 84, https://doi.org/10.1016/j.ijedudev.2021.102421.

Bandura, A. (1991). Social cognition theory of moral thought and action. In W. M. Kurtines & J. L. In, Gewirtz (Eds.), Handbook of moral behavior and development. Vol. 1: 45–96. Hillsdale, NJ: Lawrence Erlbaum..

Fogel, A. (1993). Developing through relationships: origins of communication, self and culture. Chicago: University of Chicago Press.

Gibson, E.J. & Pick, A.D. (2000). An ecological approach to perceptual learning and development. Oxford: University Press.

Harari, Y.N. (2021). The World after Covid, FT Weekend Digital Festival 2021. https://youtu.be/iWo4OrGhGxI

Introna, L. (2017). Phenomenological Approaches to Ethics and Information Technology. The Stanford Encyclopedia of Philosophy, Fall 2017 Edition.

Penrose, R. (2020). Physics of Consciousness and the Infinite Universe. Lex Fridman Podcast #85. https://youtu.be/orMtwOz6Db0.

Smitsman A. (2019). Into the Heart of Systems Change. Ph.D. Dissertation. Maastricht University, the Netherlands. DOI: 10.13140/RG.2.2.28450.25280

Smitsman A. & Smitsman A.W. (2020). The Future-Creative Human — Exploring Evolutionary Learning. World Futures: The Journal of New Paradigm Research. https://doi.org/10.1080/02604027.2020.1810536

Wahl, D. C. (2016). Designing Regenerative Cultures. Axminster: Triarchy Press.

Willard, N. (1998), Moral development in the Information Age, In: Proceedings of the Families, Technology, and Education Conference. retrieved via ERIC: https://files.eric.ed.gov/fulltext/ED425016.pdf.

Zhang, K. & Aslan, A.B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence,Volume 2, 100025, https://doi.org/10.1016/j.caeai.2021.100025.

Note: this article first appeared on the Medium Channel of Anneloes Smitsman on December 22, 2021. It was very lightly adapted for reposting on r3.0’s Medium Channel.

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