Reengineering Education: Unpacking the System We’ve Evolved Into

A Structural View of the System We Have

Although education systems are complex and vary considerably, it is worth zooming out to take an ‘archetypal view’ of the system to understand what is and is not working with what we have. We can view existing educational system structures through the lens of “first-order structures” — such as curriculum/standards, assessment, grade levels, etc. — which act as core pillars to the structure of the system and influence the manifestation of the “second-order structures” — such as pedagogy, application of learning technologies, etc. In other words, the shape and nature of the first order structures dictate the type and the manner in which the second order structures integrate (Adamson, Åstrand & Darling-Hammond, 2016). As a result, these structures have a significant impact on the daily practices and ultimate outcomes of the system (Darling-Hammond, 2004).

The Problem with Curriculum Standards

Although a panel of experts is typically employed to generate a set of standards, ultimately the finalized set is adopted and endorsed by a governing body that also puts legislation in place with the standards that has implications for schools that then must teach with them. Standards are often written intentionally to be both comprehensive yet also vague, so as not to over-prescribe what and how teaching and learning plays out in each classroom and allow room for the teacher’s professional judgment as needed when designing instruction around a given standard (Konrad et al., 2014). In other words, this is largely what distinguishes curriculum from standards: standards are not curriculum, but rather benchmark statements encompassing a mix of content and skills that must be translated into curriculum.

  • Integration / conflation of learning constructs within a standard. An individual standard as a unit of learning can vary greatly in scope and complexity, which impacts and complicates the way in which learning technologies and resources support and capture learning data for the teacher or learner to interpret.
  • Lack of coherence / alignment across jurisdictions. Due to this conflation of constructs, as well as variation in design, sets of standards from various jurisdictions do not correlate to one another — effectively each jurisdiction working on within its own system.
  • Semantic web integration. Since a common language for these learning constructs has not yet been defined, semantic web tools like knowledge graph cannot yet be easily employed — limiting our ability for information, data, and knowledge-sharing across learning objects, and more broadly in the domain learning and education.
  • Standards are not ‘living’, and as such, not able to accommodate more current and relevant research findings and societal demands. Typically, a jurisdiction will redesign and adopt a set of standards every 10–15 years, with long cycles of responsiveness and adaptation to modern insights and demands.

Beyond Standards

Although standards largely serve as our current infrastructure for managing learning goals, there is a much larger ecosystem around which we study, model, and support learning. Looking more broadly at how learning constructs outside content standards is managed, we see additional challenges with existing infrastructure:

  • The movement towards mastery-based education and personalized learning. In many parts of the US and now much more globally, there is a pronounced movement of leading districts moving to competency-based education (Singer, 2006; Sturgis, 2015a), where personalized learning and individual paths towards mastery are supported, versus standards-based education, which focuses on ‘proficiency’. There is considerable support from a variety of education stakeholders¹, because competency-based education can more effectively support learning environments in mastery-based learning, and more effectively aligns with learning progressions and a learning sciences’-based understanding of the nature of learning. However, the field has yet to common define a model for a competency, and as a result, these leading-edge schools are left to define these on their own. In many cases, districts will appoint a small subset of teachers to collectively define the competencies they will use based on the existing standards they follow²; as a result, what constitutes a ‘competency’ varies significantly within those competencies and across districts.
  • The movement towards broader skills and competencies. There is a long-standing discussion in education about the critical need to move away from solely focusing on content-area skills (i.e. math, science) to more broad or ‘higher-level’ skills such as collaboration, communication, critical thinking, creativity, inquiry, persistence, etc. (OECD, 2018; Duckworth & Gross, 2014; National Research Council, 2012). The recent surge in research on what were previously dubbed non-cognitive skills and more recently just commonly being referred to as ‘modern competencies’ have helped this movement. However the central challenge remains that these are not currently “tangible” — meaning, they are not fleshed out at the construct and assessment level, making them a bit like black boxes.
  • Supporting learning beyond the current educational system. How do learners use, need, and/or benefit from maps of learning that support them as they drive their own learning in skills in and beyond what is covered in school? How do we honor and integrate learning beyond the walls of the school?

Moving from What Was, to What Could Be

Certainly for anyone who has spent time working in the field of education, many of these tensions are very familiar. However what may not always be so evident is how these ‘structures’ truly inhibit our ability to support modern, competency-based learning environments and ecosystems.

The Tension of Learning, Systems & Complexity

The fundamental tension playing out in our current reality is to how to create the supports, structures, and systems that enable modern learning to be every child’s experience — without the system being the problem itself to impeding this outcome. It is the tension framed by German philosopher, Jurgen Habermas, who explained that all of society’s enterprises — from the family to the corporation — possess both a lifeworld and a systemsworld (1987). In societal learning, the lifeworld is made up of the traditions, practices, needs, and purposes of learners and teachers; the management decisions, protocols, policies, procedures, and accountability assurances comprise the systemsworld. The quality, health, and effectiveness of a learning environment erodes when a systemsworld is the generative force determining the nature of the lifeworld. Habermas refers to this latter situation as the “colonization” of the lifeworld by the systemsworld and attributes many of society’s ills to this situation (Sergiovanni, 2000).

source: https://asq.org/quality-resources/root-cause-analysis

Engineering a Future Learning Ecosystem

More than 25 years ago, Banathy and colleagues made a compelling case for designing systems of education and moving beyond our current image of education to create one that served everyone better (1988; 1992a; 1992b; 1995; Banathy & Jenks, 1993; Kahn & Reigeluth, 1993). Their work argued for why reform was largely piecemeal and incremental, and from a systems design approach was vital, and unpacked the layers of the system that would need to be considered in that redesign. What was missing in this work was the actualized design and implementation of such a new system.

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Jennifer Groff

Jennifer Groff

Learning Futurist. I research, design and create learning technologies, environments and systems. PhD @MIT Media Lab; CEO/Founder of Learning Futures