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• How might generative text tools be useful in academia?

  Last updated Jun 16, 2023 | Originally published Jun 16, 2023

  21 trends, four scenarios, and some reverse archaelogy exploring the futures of generative text in research and teaching.

  • Futures
  • University
  • Academia
  • Research

• a brief guide to doing grounded theory

  Last updated Jun 10, 2023 | Originally published Jan 23, 2020

  Grounded theory is an approach to analyzing data by letting the powerful and important insights in the data *emerge* through deep, iterative reading. The best part: you can use it even if you’re not doing formal research. Grounded theory simply provides a pragmatic way of analyzing a mess.

  • Articles
  • Research
  • Theory
  • Analysis

• A Case Study of Theories of Systemic Change and Action — The Ecotrust Canada Home-Lands initiative

  Last updated Mar 7, 2023 | Originally published Mar 7, 2023

  In this presentation, we reported on a case study of the Ecotrust Canada Home-Lands initiative. Lewis and I worked with Ecotrust Canada to understand the challenges they were addressing from a systemic design lens and, using that approach, to develop a theory of systemic change and action for the initiative.

  An interesting development in the work was the development of a novel systemic evaluation technique: resonance and dissonance tests. The tests were designed as a way of testing our understanding of the system without interrupting or intruding on the processes of the initiative. The general idea behind resonance and dissonance tests is to identify a set of phenomena in your understanding of the system and to search for disconfirming evidence that those phenomena are complete and accurate. So, for instance, if you think a key phenomenon in the system is “community distrust of bureaucracy”, look for examples of the community trusting bureaucracy. If you can’t find any, it increases the integrity of the theory you’ve created.

  • Systemics
  • Design
  • Systemic Evaluation

• Leverage is Fractal, Relative, and What Else? We need a theory of leverage in systemic design

  Published Oct 14, 2022

  Donella Meadows's article on leverage points was a work in progress that hasn't been further developed in 25 years. It's time for a modern theory of leverage.

• Knowledge innovation is systemic and fractal and that should be reflected in our models of publishing

  Published Jun 25, 2022

  An argument for a new model of scholarship in systemic design.

• Design Management for Wicked Problems - talk at ADMC 2020

  Last updated Mar 30, 2022 | Originally published Mar 30, 2022

  # Design management for wicked problems - ADMC 2020

  Our toughest problems resist conventional strategies for change. In this talk from Peter Jones and I, we show how designerly approaches—namely methods from systemic design—can help create and implement systemic theories of change. Those theories may then be used to develop effective strategies for wicked problems.

  https://vimeo.com/682033442

  We presented this talk at the Academic Design Management Conference in 2020, and it led to a follow-up paper.

  • Systemic Design
  • Leverage Analysis
  • Talks
  • Articles

• Your Notes are an Information System

  Last updated Aug 8, 2021 | Originally published Aug 8, 2021

  A presentation at the MUN Graduate Students' Union's 2021 Aldrich Conference.

  • Articles
  • Personal Knowledge Management
  • Productivity
  • Information Systems
  • Research
  • Projects

• Systemics and design principles in support of Tiago Forte's PARA framework

  Published Mar 29, 2020

  Tiago Forte's PARA system is a popular new approach to organizing your digital materials. I explain its usefulness with reference to some principles from systemic design.

  • Articles
  • Personal Knowledge Management
  • Productivity
  • Systemics
  • Design

• Education Systemics - Causal Loop Mapping

  Published Jan 23, 2020

  # Education Systemics - Causal Loop Mapping

  This investigation answers the question: How does the system behave?

  

  The actor map helped with the development of a causal loop diagram: a map of the phenomena of education reform that illustrates how the relationship between these actors might lead to difficulty (or success) in reform movements.

  This map is centred on the provision of innovation education in the province. Each stakeholder of the actor map was used to generate phenomena that could impact the delivery of innovation education in Newfoundland and Labrador. How these phenomena related to and influenced one another was then mapped, and salient feedback loops and systemic archetypes (patterns of system behaviour observed in different systems with similar consequences and potential solutions) were identified.

  Explore the causal loop diagram

  ---

  # FINDINGS

  A total of 31 elements are linked together with 50 connections depicting the phenomena contributing to innovation education in the public education systems of Newfoundland and Labrador in the map linked above.

  # Loops And Archetypes

  # The Low Definition Loop

  Immediately, several feedback loops are obvious. The Low Definition (R1) loop–arguably single-handedly responsible for the context of the present research–is a reinforcing cycle driving the current lack of emphasis on innovation skills. Low innovation capacity means that we are collectively lacking in our understanding of innovation, which leads to a lack of understanding of innovation skills and competencies and therefore a lack of emphasis on educating those skills and competencies, leading to poor innovation capacity. As this is a reinforcing cycle, however, improving innovation education may reverse the direction of this trend.

  

  # We Teach What We Know

  A reinforcing loop linked to the Low Definition loop is We Teach What We Know (R2), in which a lack of innovation education leads to a lack of innovation educators. This then doubles back, limiting our capacity for innovation education. As above, introducing more innovation education into the system will impede the force of this cycle. 

  

  # The New Economy

  A third reinforcing loop is The New Economy (R3), which links Newfoundland and Labrador’s natural resource-dependent economy to the recognition of our limited innovation capacity. When oil prices drop, the provincial economy experiences economic shock, and the public becomes more aware of the degree to which the economy is tied to resource exports. This increases the public’s perception of our innovation gap, spurring a search for solutions and thus a recognition that we can do more innovation education. Over time, this will result in reform for innovation education, improving our innovation capacity and reducing our dependency on resource exports. 

  

  # Innovation-Driven Growth

  Innovation-driven Growth (R4) is the fourth and final reinforcing loop of note. As with The New Economy, this loop explains how growth in innovation skills can lead to new innovation opportunities. As innovation capacity improves, it is likely that work in knowledge economy jobs will proliferate. This leads to a growing need for innovation skills, increasing pressure to produce more innovators, which leads to increased innovation capacity.

  

  # Limited Resources

  One balancing loop is worth highlighting. The Limited Resources (B1) loop shows how our current natural resource-driven economy limits our ability to become an innovation-driven economy. When economic shock hits because the price of oil drops, public spending–the main source of education funding–becomes limited by austerity. This reduces the capacity for our educational institutions to spend time and resources on innovation education reform. In turn, our capacity to provide innovation education is limited, and so is our innovation capacity – leaving us continually linked to oil exports.

  

  # R&D, Not Innovation

  A systemic archetype – a pattern of behaviour that appears across systems, with similar consequences and similar solutions – also appears. R&D, Not Innovation is a balancing loop nested within a reinforcing loop, an example of the Fixes that Fail archetype. The perception of an innovation gap sparks a search for solutions. One of those solutions is to turn to the classical notion of innovation as R&D, and to increase R&D spending and activity in order to improve innovation capacity. This alleviates the perceived innovation gap, but does not produce meaningful gains in innovation itself. Meanwhile, the conflation of R&D and innovation takes us further away from a concrete definition of innovation, leaving us without a solid understanding of innovation skills and competencies and thus an under-emphasis of the provision of innovation education.  Andrei Sulzenko discusses this tendency for policymakers to treat R&D as the solution, and suggests searching for other solutions to Canada’s innovation gap instead.

  

  # Leverage Points And Bottlenecks

  Centrality analysis can also reveal insights in causal loop maps.

  # Reach Efficiency Centrality – Low-Hanging Fruit

  Reach efficiency metrics, for instance, reveal several low-hanging fruit for changemakers in innovation education.

  One such element is innovation learning from outside of the public education system, circumventing the messiness of trying to change the public system by injecting innovation education directly into learners through other programs and services. This is easily done–there is little to stop someone from offering programs to those who want to take them–and could prompt public institutions to recognize the market and develop their own competing solutions for it.

  Another high reach efficiency element is the lack of emphasis on innovation skills and competencies. Increasing the public’s awareness that innovation is something that can be learned may inspire other actors to recognize the deficiency of innovation education in our system, causing change.

  The third-most reach-efficient phenomena is a low price of oil–only appearing high on this list because the real complexity of influences impacting this phenomena is not included in this map. Still, it points to the significant impact an oil-driven economic boom can have on innovation education if its profits are spent on the right things.

  # Eigenvector Centrality – The Influencers

  Eigenvector centrality (how well-connected an element is to other well-connected elements; an element’s overall influence within the system) does not highlight many elements of utility here. The results are intuitive: innovation education, innovation capacity, and the perceived innovation gap rank the highest on this metric, but these elements are difficult to impact (hence why they are the focus of the present research). Torque centrality may give us more information.

  # Torque – Leverage Points

  Elements with high torque should be relatively easy to impact (as they are not densely influenced by other phenomena in the map), but will impact the rest of the map substantially. These are key leverage points of change.

  Torque analysis highlights several key elements. First on the list is the low price of oil, which I will dismiss as it is not actually easy to influence (as described above). The foremost leverage points in the system, then, are other calls for reform and accessible and practical models for innovation education – both with identical torque. 

  Other calls for reform is actually a reverse-leverage point: it points toward the many forces trying to influence the education system at any given point. Examples might include the growth of both entrepreneurial programs and social entrepreneurship on Canadian campuses of late. These forces compete, making it difficult for decision-makers to prioritize any one reform movement. This means there is a need for “co-opetition” (co-operative competition): partnership between actors looking to change the system in order to link or at least weave together their efforts such that they do not undermine each other. The high level of torque this element has reveals its forceful potential to undermine reform efforts.

  Accessible and practical models for innovation education, if accepted by reformers, would eliminate confusion about innovation and its subsidiary skills and competencies, making it easy for educators to adopt and build innovation education into their curricula. The high torque value of this element certainly validates the present research, although I caution that this could be a case of “falling in love with the solution”. It is certainly suspicious that research resulting in a model of innovation education would suggest that creating a model of innovation education is one of the most powerful forces available to change the system!

  Ranked fourth for torque is generational shifts in work, a phenomena pointing to the need for futures analysis in this problem space. This element captures the notion that some economic changes will take place only as the previous generation exits the workforce. This particularly influences educators through a form of bias: current educators teach what they know, as the system worked for them, failing to recognize that the conditions of the world have shifted since they were educated and new approaches are necessary for the 21st century. 

  # Betweenness Centrality – Bottlenecks

  Finally, betweenness centrality helps to reveal potential bottlenecks in systemic change. Innovation capacity and innovation education rank high on the list, again potentially because these phenomena are central to the system I have mapped. This is not necessarily meaningless, however: it is also an indication that many influences hold these components in place, and they will likely change slowly as a result.

  Three other high-betweenness elements are the recognition of innovation skill deficiency, the perceived innovation gap, and the search for solutions to the innovation gap. As suggested immediately above, their high levels of betweenness show that these elements are influenced by many forces. As such, they are bottlenecks or single points of failure in systems change. There is an intuitive to logic to this. If the system does not perceive an innovation gap, for instance, it is not likely to engage in any change effort, regardless of what else is happening in the system. The same is true for our recognition of a skill deficiency in innovation and for a single-minded search for solutions (e.g., R&D spending is the only answer). Thus, changemakers looking to improve the system’s innovation education must monitor these phenomena closely, making sure to mitigate these forces’ influence on any reform effort.

  ← Back to Education Systemics.

  Read the full paper.

• Education Systemics - Actor Mapping

  Published Jan 23, 2020

  # Education Systemics - Actor Mapping

  This investigation answers the question: Who is involved in this system?

  # Approach

  

  Actor mapping identifies the actors participating in a given system or related to a given issue and maps the relationships between them. Beginning with the actors linked to the process model, I identified key actors influencing a students’ education in Newfoundland and Labrador. These actors then became prompts for additional actors themselves, allowing me to articulate additional superand subsets of actors and influencers in the system. Many of these did not directly influence the student, but instead were strong influences on those actors that did. 

  EXPLORE THE ACTOR MAP

  Once the map was saturated, I coded the connections by the flow of wealth and power, two of  Jamshid Gharajedaghi’s five systemic dimensions. These dimensions help to illustrate how the map changes depending on which of these values you are interested in examining. 

  # Findings

  The initial actor map offers a simple picture of the components of this system, illustrating the complexity by defining the sheer quantity of actors influencing a student’s learning.

  This actor map offers further insights when refined and analyzed through Gharajedaghi’s iterative process of inquiry and multi-dimensional analysis. In the refined map, it became clear that the most prolific pathways between actors were wealth and power. This is intuitive: the governance of the other dimensions (beauty, or what we find joyful; knowledge, or what we find true; and values, or what we find morally right) are wrapped up in the wealth and power dimensions of this system. In other words, actors with power and wealth strongly influence the distribution and production of beauty, knowledge, and values.

  Nonetheless, overlaying these two dimensions of the system essentially results in two interlinked subsystems. I will discuss them separately.

  # The Flow of Power in the Education System

  Power is created and distributed in this system through the election, administration, governance, and lobbying of actors by one another. Thus, it is a highly political environment: issues prioritized by the electorate and leaders are the most likely to change. 

  A few features of the power subsystem are worth describing.

  First, the Government of Canada is fairly powerless, despite its symbolic position as the nation’s leadership. This is because education is provincially governed.

  Second, both the University and the College are relatively independent. While the provincial Department of Advanced Education and Skills governs these institutions, they are also governed independently by their own internal leaders.

  Third, several advocacy organizations enact political lobbying in the K-12 system, namely the NL Federation of School Councils and the NL Teacher’s Association. This gives these actors the appearance of power, but whether that power is realized depends–to a significant extent–the degree to which the actors they lobby allow their influence to hold sway. This is a complex interaction in and of itself, and it is liable that issues may need to be lobbied from multiple actors before any one lobbying effort would have success.

  # Centrality Analytics

  Centrality analysis reveals further salient insights. According to reach efficiency metrics, students themselves are significant actors–though this idea should be accepted with caution. Students retain a high level of influence because they will eventually become graduates themselves, and therefore will inherit the roles of all of the other actors of the system. This obviously takes time, and thus students may not be as useful for change as they appear. Parents place second on the reach efficiency ranking. This makes sense: parents are a substantial voting block in the elections of the province and play important roles on school councils. If a movement were able to mobilize parents to advocate for change throughout the rest of the system, they may have significant impact. The provincial government is also highly reach-efficient. Once elected on a four-year term, the politicians in the province’s leadership roles make decisions from a fairly alienated seat of power, setting the agenda for the provincial ministries that oversee the public system. 

  Eigenvector analysis (as a reminder, eigenvector centrality approximately indicates an elements’ overall influence) reveals that K-12 schools themselves are the most connected elements to other well-connected elements. Namely this is because schools administer and support educators themselves. This power may not translate directly into the potential for reform (schools themselves do not have jurisdiction over major curricula) but it does indicate the role school communities play in supporting movements for change within the system. The Board of Trustees, the governing body of the school district, is ranked second in eigenvector assessment. The Board makes ultimate decisions about operations, curricula, and other aspects of the K-12 system, so this is logical. Should the Board decide to prioritize reform, the change could quickly impact schools and educators. Finally, third on this list are educators themselves, who play a substantial role in both of the above elements. The interplay of these actors should not go unnoticed: their interaction is apt to produce systemic behaviour, as I will explore with causal loop diagramming shortly. 

  Educators are also substantial bottlenecks for change within the system, according to betweenness analysis. This is intuitive: any curriculum change, for instance, would ultimately be implemented through the educators of the province. If teachers resist changes or are slow to adapt, it will buffer impact on the rest of the system. Schools and school councils are next on this list for similar reasons. Third is the Department of Education and Early Childhood Development: even if other actors press for change, anything official must come from the Department.

  Before I end this discussion of power between actors in the system, it is worth noting that actors in the post-secondary system did not appear prominently on the above metrics. This is perhaps because of the independence of those institutions, as noted earlier. A standalone examination of the post-secondary system might reveal more nuanced mechanics of power. For now, I simply note that – from a provincial perspective – levers for changing these systems are not readily accessible. This may work both ways, however: the post-secondary system is less entrenched in provincial politics and bureaucracy, and therefore can change independently of the rest of the system should it choose to do so. Thus, while the provincial system may not have much holistic influence, a dedicated change agent may achieve success through engaging with these institutions on their own.

  # The Flow Of Wealth In The Education System

  Doubtlessly the subsystems of power and wealth intertwine, as those who have power often decide where to spend resources. Still, a separate examination of the wealth subsystem has merit. Funding is a substantial incentive, both as a call-and-response mechanic for specific initiatives and in terms of the activities of different actors that the system is willing to resource. Policymakers might create project funding for educational institutions to apply to, for instance, or students may stop enrolling in particular programs if they deem those programs poor choices for post-secondary study. 

  The government is likely to be the biggest source of revenue for most of the actors in this system. Significant revenues for the government come from taxation, and thus there should be a “pays taxes” relationship between many of the actors in this system and the provincial and federal governments. I leave these links out, however, as the degree to which one pays taxes is not decided by the taxpayer. Here I am only interested in decisions about the distribution of wealth. Thus, the relationships observed in this subsystem are composed of fees and funding.

  # Centrality Analytics

  Reach efficiency metrics on the wealth subsystem elevate the importance of students, parents, and the Government of Canada. The Federal Government can offer funding opportunities for institutions and the provinces to improve innovation education. The reach efficiency of parents and students relates to the post-secondary system: they decide which schools and programs to enrol in, decisions that could become significant if the innovation education experiences provided by different programs are increasingly differentiated. The Department of Advanced Education and Skills, the main funder of the province’s University and College, places fourth on the list, with mechanisms for change through funding similar to the Government of Canada.

  Eigenvector metrics were not calculable, unfortunately, due to the nature of the cycles defined by the map. This is not meaningfully significant–eigenvector calculations simply could not be computed due to the map’s structure.

  Betweenness analysis found several bottlenecks at similar levels of betweenness centrality. The Provincial Government, the Department of Advanced Education and Skills, the Department of Education and Early Childhood Development, the English School District, Schools, the University and the College, and students and graduates themselves all ranked similarly. If anything, this means that the resources of the system are densely dependent on one another. The wealth distribution of the system is therefore potentially volatile, in which changes in the wealth of one element ripple to others. 

  ← Back to Education Systemics

  Read the full paper.

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