The Knowledge Metric in Education
Posted: January 9, 2013 Filed under: education & learning, evaluation, innovation, science & technology, systems thinking | Tags: design, education, educational design, evaluation, higher education, journalism, knowledge integration, knowledge translation, learning, professional education, social innovation, teaching, universities, university 5 Comments »
Higher education is asking itself some big questions and making substantive changes to the way it sees itself and produces value for society. Education is increasingly being rationalized, which calls into question the metrics that are being used to judge how resources should be allocated. In a previous post, I looked at the jobs metric. Now, it’s time to look at the knowledge metric.
Just the facts
Education writer and teacher Will Richardson‘s TED Book Why School is a provocative read for those connected to teaching or just interested in schooling. While it focuses largely on grade school, the issues are the same for universities and colleges particularly as the primary and secondary students of today are tomorrow’s graduate and professional learners. Richardson questions the role of the school as institution in its current form suggesting that if the status quo — one characterized an information delivery warehouse — is maintained there is little need for schools to exist at all. Yet, if the education within schools is focused on asking better questions and learning when to apply knowledge, not just what knowledge to apply, there is hope.
The current trend in school reform is towards Common Core Standards, which emphasizes specific forms of knowledge, ‘facts’ and asks that students be able to recall such content when required. Under this model, the role of the teacher is one of content manager and facilitator rather than guide or mentor and students are prepped for the tests of their knowledge (memory) rather than be asked to demonstrate its application to anything outside of the test. It is this model that many proponents of online education embrace, because the Internet is a fabulous content delivery system and education can be literally programmed and delivered to students directly without the ‘noise’ that teachers introduce to the signal. Under this model, educational content can be delivered cheaply and widely to support uniform intended effects among learners.
Richardson argues for reforming schools to something closer to the alternative model that was advanced by educational reformer and philosopher John Dewey. Richardson writes:
“In this version of reform, schools and classrooms are seen as nodes in a much larger learning network that expands far beyond local walls. Students are encouraged to connect with others, and to collaborate and create with them on a global scale. It’s not “do your own work,” so much as “do work with others, and make it work that matters.” To paraphrase Tony Wagner, assessments focus less on what students know, and more on what they can do with what they know. And, as Dewey espoused, school is “real life,” not simply a place to take courses, earn grades, amass credits, and compete against others for recognition. There lies the tension.
This second path is simply not as easy to quantify as the first. Developing creativity, persistence, and the skills for patient problem solving, B.S.-detecting, and collaborating may now be more important than knowing the key dates and battles of the Civil War (after all, those answers are just a few taps on our phones away), but they’re all much more difficult to assign a score to. I’m not saying that a foundation of content knowledge isn’t still important. To communicate, function, and reason in the world, students need effective reading and writing skills, as well as a solid foundation in math, science, history, and more. But I’m convinced we must revise the overreaching coursework requirements we place on students — requirements created at a time of scarcity, by the way. And we desperately need to revisit the thinking we’ve developed around assessment that, as Harvard researcher Justin Reich says, “optimizes the measurable at the risk of neglecting the immeasurable.””
Facts vs Problems
The knowledge metric is flawed because it assumes that content solves problems. It also presumes that the curriculum teaches the right knowledge for the right problems and that those problems can be known in advance. Let’s look at these.
One need only look to cigarette smoking as an example of how knowledge alone doesn’t always solve or prevent problems. One would be hard pressed to find anyone over the age of five who doesn’t know that sticking a lit tube of anything in their mouth and sucking on it isn’t at least somewhat unhealthy (and most know it is very unhealthy). An individual’s knowledge of smoking’s effects on physical health may not be complete, but it is often sufficient to inform the decision to quit or not start the unhealthy habit. And yet, citizens in highly educated countries like the United States, Canada and the U.K. smoke more than 1000 cigarettes per year per capita (and over 2700 per capita in places like Russia). These are not countries lacking in information on tobacco and health.
Using students’ ability to recall content makes the presumption that what is contained in a curriculum is what they need to know when they leave their program of study (at least as a start). While it may be somewhat true for students in the humanities and languages, it becomes highly problematic for those in dynamic fields or emergent areas of practice, which is becoming more normal than rare. There is no doubt that a corpus of key concepts, skills and ‘facts’ is useful, but the manner in which this knowledge can and may be applied is changing dramatically. For example, social media has upended communications in ways that very few health professionals are trained for. Journalists are particularly aware of the role that Twitter and related tools have had on their profession.
It also presumes that the content itself is relatively static. Certainly, curriculum renewal is something that most learning institutions engage in, but the primacy of content itself as the driver of education also assumes that the foundation for that knowledge is solid and can be applied today in the manner it was applied yesterday. In dynamic conditions, that isn’t often true. Further, the relevance of knowledge is framed by the problems to which that knowledge is applied. Genetic information, for example, can be incredibly useful when framed against tests that have high confidence, predictability and value to people, yet without such a context it is largely useless to those non-scientists who have it.
Areas of social innovation — which are expanding dramatically in number and scope — illustrate the problem of changing context well. This is a field characterized by problems, problem solving and novelty (which is what innovation is all about). Standard approaches don’t apply easily or at all when we are faced with high levels of novelty. Thinking and re-thinking the problem frame, knowing what to find, where to find it, and the skills to integrate relevant knowledge together is something that is not captured in the knowledge metric. Yet, it is those skills that will lead innovation. Knowledge translation professionals know this and so do knowledge brokers.
Are we designing our educational programming to advance on the kind of design issues of problem framing, finding and solving that our world is facing? Or are we simply taking content that can be obtained through books, the Internet and other materials, repackaging it and creating expensive warehouses of information that take learners out of the world and out of context in the process?
I don’t suggest that universities and continuing education programs stop delivering content, but if knowledge is the metric by which they are judging their success then it behooves educational administrators and funders to justify why they can do it better than other tools. What made sense when content was a rare commodity makes little today when it is overflowing in abundance for little or no cost. Universities and post-graduate training programs have an opportunity to re-imagine education and have the tools to do it in a way that makes learning more powerful and relevant for the 21st century should they choose to change their metrics of success.
Designing education
How might we take the enormous talent trust that exists among university faculty (and their students) who co-locate (physically, virtually or in some combination) in a school and develop the skills to not only address problems of today, but prepare everyone for possible challenges in the future?
How might we integrate what we know, identify the knowledge we need, and create systems to take advantage of the talent and creativity of individuals to make universities, colleges, and post-professional training venues for innovation and inspiration rather than just content delivery vehicles?
What kind of metrics do we need to evaluate this kind of education should we choose to develop it?
These are questions whose answers might yield more learning than those focused on what knowledge students have when they graduate.
___
Image source: Shutterstock.
The Fourth Estate of Health and Medicine
Posted: December 11, 2012 Filed under: knowledge translation, public health, science & technology, social media | Tags: Andre Picard, blogging, Darwin the monkey, evidence, health evidence, health reporting, journalism, Julia Belluz, knowledge translation, Malcolm Gladwell, media, Mitch Waldrop, news, newspapers, public health, science, social media, Stan Glantz, Steven Johnson, the fourth estate, tobacco control 2 Comments »
Journalists occupy an important, yet often unacknowledged, role in the health system by providing a dispassionate account of the system’s strengths, weaknesses, and opportunities to the public. It is through journalists that much of the research we scientists and practitioners produce gets communicated to the audiences likely to use them. This fourth estate is also a place where hard questions can be asked and answered, holding governments, business and the health system itself to account because journalists operate apart from this space, unlike scientists and clinicians. We are at risk of losing this and it’s time to consider what that means for our collective health and wellbeing.
Disrupted Media
The news business is going through a massive upheaval, part of a larger overall disruption in media. Many newspapers are reducing the size of their print offerings, publishing less frequently or ceasing operations altogether.
This reduction in the capacity and size of the fourth estate begs two simple questions: Who will hold health scientists, clinicians, pharmaceutical companies, health product manufacturers, and policy makers to account? and who will tell the stories of science, health and medicine in public?
While we have some activist academics doing great work on influencing broader audiences like policy makers, they are exceptions not the norm. Stanton Glantz, a major tobacco control champion from UCSF who taken to blogging as a means of communicating to professionals and the public directly, is one of these such people. But Stan is atypical and holds a tenured position at a major university, something he’s acknowledged protected him when pursuing issues of evidence withholding from the tobacco companies in the 1990′s and beyond. Many faculty (particularly younger ones) are not this secure and even fewer independently funded scientists are. Academia is changing and not in ways that favour security and stability, which has implications for the kind of stories that get told.
Journalists have traditionally relied on protection from their publisher or producer under the name of journalistic freedom (the fourth estate) as a key pillar of their profession. It’s hard to imagine the Watergate scandal coming to light had Bob Woodward, Carl Bernstein and the other reporters working for the Washington Post, Time Magazine and New York Times not had the resources, stability and support provided by their newspapers . But what happens when these resources are no longer available or there are no institutions to support journalists in serving as watchdogs to hold people or institutions to account for what they do and don’t do?
Are ‘Monkeys in Coats’ A Healthy Story?
It’s been suggested that the Internet will take care of this. Citizen journalists, armed with camera-laden handsets connected to social media will fill the news gap. For example, it was citizens, not journalists, who first captured the story of Darwin the monkey, dressed in a shearling coat, walking around an Ikea parking lot in Toronto that went viral on a global scale on December 10, 2012. This is great for those interested in simian fashions and retail adventures, but the reason it was captured was because the story was obvious and in the face (or at the ankles) of those who told it. (For those of you not familiar with Toronto, coat-wearing monkeys are not typically seen at shopping centres or anywhere around town for that matter.)
Health and medicine is not the same as monkeys wearing coats (no matter what kind of joke you want to make). There is nuance, debate and reason that requires sustained attention and focus that someone with an iPhone and Twitter account is less likely to convey. Reasoned arguments for citizen journalism’s potential suggest it can complement the work of traditional journalism, not replace it. Yet, is this belief in one form (citizen journalism) undermining support for the other (traditional journalism) and serving as a fix that ultimately fails? If free-and-easy content is available, how likely are publishers willing to pay for professional work? Particularly if the choice of stories of one group (e.g., monkeys in coats) are more likely to garner the kind of attention that drives advertising than that of another (e.g., health care financing). Only one of these stories will impact our collective health.
Why does this matter? Trained journalists are required to be good communicators to a broad audience, scientists are not. Clinicians are slightly better, but decades of research has shown it is still highly problematic across areas of practice. This will not be solved overnight, if at all. Scientists and clinicians have told me they are already burdened with enough job expectations and adding knowledge translation skills to that list is asking too much.
As I have argued previously, there is a valued place for synthetics in research: those are who are good at taking ideas and weaving them together into an accessible narrative. Journalists are ideally suited to play or support this role. They do the job that many scientists can’t or won’t do and have better to tools, skills and strategies to do it. They write in a style that is suited to broad audiences in a way that suit those audiences’ needs, not what funders, disciplinary traditions, universities, or scientific peers demand (without evidence that those methods of communication are effective). There are reasons why journalists assess the reach of their work in the thousands and social scientists in the dozens (by citations in their field of practice).
Going Deeper to See Clearer
Although we have more information about health available to us than ever before, this may not be healthy for patients. The potential for those uninformed about medical diagnostics, evidence, and the nature of health itself to make poor choices based on incomplete, incorrect or overwhelming information is high. Further, without the kind of dispassionate examination of evidence in a synthetic manner that is tied to the way in which that evidence is expressed in the world through public opinion, policy making and healthcare practices, we lose a major accountability mechanism and means of informing public discourse.
In October I co-delivered a workshop on health evidence for students at the University of Toronto with the 2012 Hancock Lecturer and journalist Julia Belluz. Julia writes the Science-ish blog for Macleans Magazine and is an Associate Editor with the Medical Post. Julia`s lecture was on the role that social media plays in our health system and how its power to leverage the attention of the masses — for good and ill — is shaping the public understanding of health and medicine often in the absence of evidence for effects of conditions, processes, and practice. The lecture is summarized online on Science-ish beginning here.
Reading through the lecture notes one sees a depth of study that would be unlikely to be found anywhere within the formal health system. The reasons are that it blends evidence with commentary, observation with carefully selected sources, and takes a perspective that seeks to inform a wide, not narrow audience in both practical and intellectually stimulating ways. Taken together, this is a collection of activities that are not within the scope of practice for scientists and practitioners. There are reasons why the greatest contributors to public discourse on many scientific issues has come from journalists, not the scientists who generate the research. They tell the story better.
Malcolm Gladwell, Steven Johnson, Mitch Waldrop, Julia Belluz, Andre Picard and others are a big part of the reasons most of the those who vote to support funding of science, who donate to research-related causes, and fight for policies to keep us healthy know of the research that backs those ideas up.
Imperfect as journalism is, it serves the public when done with integrity. It’s worth spending some time considering what can be done to support the fourth estate so it supports us.
Photo credit: DBduo Photography on Flickr used under Creative Commons Licence.
Have We Turned the Page on Social Science Research for Health?
Posted: May 15, 2012 Filed under: knowledge translation, science & technology, social systems, systems science | Tags: funding, health promotion, knowledge translation, public health, research, research funding, science policy, social science 2 Comments »
Turning the Page on Social Science and Health Research
Over the last two weeks social science researchers across Canada began receiving the decisions from last autumn’s competition for a Social Science and Humanities Research Council (SSHRC) funding award. SSHRC is the principal funder of social science research in Canada, although notably is not in the business of funding heath-related research, which is supposed to be funded by the Canadian Institutes for Health Research (CIHR). [Full disclosure: I currently hold grants from both of these organizations]. The problem is that CIHR was born from a policy and programming body and the former Medical Research Council and has a rather awkward relationship with social science research given its medical focus. It has funded some social science programs, but not in a manner that has enabled social scientists to comfortably explore the range of issues that they might have under traditional SSHRC funding programs, particularly when social issues are not always obviously health issues (e.g., poverty, education) and can easily be dismissed as not being relevant in spite of the evidence that they are. Yet, SSHRC has decided to forgo any funding of health-related projects due in part to the absence of funding to support it when there are presumably options through CIHR or the disease-specific health charities like the Canadian Cancer Society, the Lung Association and others.
Yet, these options are not suitable. In a manifesto entitled “The end of medical anthropology in Canada” a group of leading social scientists painted the picture of the situation in grim terms in University Affairs. Although medical anthropology is the focus of the piece, the authors might as well be speaking for social sciences in general:
Health is inherently social and cultural. SSHRC has always understood this; CIHR, we fear, does not. We face the possible extermination of one of the most vibrant, high-demand and policy-relevant health disciplines, the only scholarly field that places culture at the centre of the analysis of health and that characteristically does so in both national and international contexts. In a multicultural, settler society with a substantial aboriginal population, and in a world where health is at the core of developmental, political and social issues in so many countries, where Canada otherwise wishes to have an impact, does this make any sense?
This brings me back to the beginning of this post and the announcement of the results of the last competition. Looking at the funding numbers released by SSHRC, a discouraging picture emerges. In 2011-12, 37 per cent of all applications in the open competition were deemed fundable, yet only 22.5 per cent were funded. These numbers are similar t0 2010-11, when 36 per cent were deemed fundable and 22 per cent were funded. What is not mentioned in these numbers was the level at which these grants were funded in the first place. I am a 2010-11 recipient of funding from SSHRC — meaning my grant proposal was within the top 22 per cent of all applications for that year — and the amount I received was approximately half of what I requested. That means that I had to take half of my budget and throw it away. So yes, I was successful providing I did either half of the research or found money elsewhere. I did the latter and my pocketbook is none the better for it.
Consider the implications of this change in funding. With one in five projects funded and many of those that are funded at levels well below what was requested the motivation for researchers is one of the first casualties. Researchers know that funding is tight and that it is highly competitive, but few alternative sources for research grants that lay outside of specific disease-focused areas, social scientists young and old are faced with little option. This creates another set of affected parties: students and trainees. Research funding not only supports the scientists themselves in many cases (see my previous posts on this), but those seeking to become scientists themselves or those who seek to get better acquainted with research. In health sciences and policy, this means just about everyone enrolled in such programs.
Now consider all of this in light of a trend towards increasing graduate education numbers. At the academic institution I am affiliated with (like many of its peers), the enrolment numbers are set to nearly double across many of the professional programs associated with health practice and policy in the coming years. Increased demand for training opportunities from the public has created a means for universities to cash in. Of course, what these students will do when they get there is unclear (let alone when they graduate), but it cannot be much in the way of research — at least as it pertains to social science and health. The funding is simply not there to support the kind of broad-based inquiry into the social factors that influence health, illness and well-being anymore. We have, as I call it, reached ‘the Turn’.
The Turn is that point where the system changes irrevocably towards a new direction. It is like a ‘tipping point‘. Dwindling numbers of social scientists working from funding from an institutional budget (e.g., tenure-stream faculty positions) + a doubling of the student cohort * half of the research dollars makes for rather toxic math. The Turn will fundamentally shape the way social science inquiry is done and the kind of questions that get asked. As question foci change, the quality of the research shifts, and the depth of inquiry is reduced, so too will the real impact that social science has on our health.
The gap between what we know, what we do, and what we can do to prevent illness, treat sickness, and promote well-being will grow.
Anecdotally speaking, this trend is not unique to the social sciences, but it is amplified in this domain. Social sciences in Canada and abroad are consistently funded at lower levels than that of basic research (see here for a starting point). But what is interesting is that many of the problems that we face within health require social science knowledge and research to address and social science — from knowledge translation, social network studies, technology adoption, innovation, management, to policy implementation and beyond .
Prevention of disease and chronic illness is often a social phenomenon (e.g., hand washing). Even the act of taking the best of basic science and translating it into practice or policy options (or other scientific research) is a social act that draws on social science research to execute. Social determinants of health are social in nature and require social science to understand their impact. Designing the policy and programmatic interventions that support creating a healthier society also falls to social science research and practice.
What will our health landscape look like without the ability to take what we know and translate it into action? Worse yet, what if we simply are unable to even know what to do because the research and evidence isn’t there in the first place to translate into anything? Without another turn towards something more positive in our research support, we are about to find out.
* Photo Turn the Page by Miaboas used under Creative Commons License from Deviant Art.
(Un)Building a Mystery: Peeking Behind the Curtain in the Academic Land of Oz
Posted: December 16, 2011 Filed under: education & learning, research, science & technology | Tags: academia, academic freedom, education, faculty life, innovation, research, teaching, university 1 Comment »
Mystery by UK Tara
The gap between what academics do and what those outside of the academy think they do is enormous. The mysteriousness and elite status that universities enjoy may actually serve to undermine the very values of inquiry and education that it seeks to promote. In this second in series of posts on academic life, I take you behind the curtain of Academic Land of Oz to illustrate what life for at least one professor looks like.
‘Cause you’re working
Building a mystery
Holding on and holding it in
Yeah you’re working
Building a mystery
And choosing so carefully- Sarah McLachlan, Building a Mystery, from the album Surfacing
The academic world has been my home for my entire adult life and one that I helped to build and shape along with my peers with the aim of making a contribution to our collective knowledge, the education of (mostly) young professionals, and hopefully enriching all of our lives along the way with insight drawn from research. This is what the public thinks happens in universities and, to a large extent, they are right. But the way this is done, the roles people play, and the manner in which the academic system is designed and operates is as much of a mystery you will find in our society. But perhaps its time to (un)build it**.
And unlike the Wizard of Oz, this mystery does more to harm those both building it and experiencing it from the outside. How? In part, because times are changing quickly and public institutions along with it. When times are tight, there is little appetite to support professors sitting in their offices, thinking deep thoughts, doing research that has tangential value for society, teaching badly to undergrads and only to small groups of grad students, and taking four months off in the summer and three during the December holidays.
The first part of the problem is that this perception is widely off the mark from reality.
The second part is that universities seem to be doing a poor job of correcting this perception.
For starters, universities are investing a lot less in faculty than people think. In my six years, my university itself only picked up only a small portion of my salary. The rest was through a philanthropic donation, salary awards I earned from both government-funded research programs (e.g., the Canadian Institutes of Health Research), contracts with community service groups, or sometimes from grants. Unlike other countries, Canada doesn’t have a system where investigators can easily draw a salary from the operating grants they receive. Thus, I could afford research assistants, equipment and travel, so long as I didn’t get paid.
To cover this, I had to get separate career awards to pay for my salary and as these awards typically covered less than 50% of my wage, I needed multiple revenue streams at the same time. This meant writing 2-3 times the number of grants that a tenured faculty would have to write. To make matters worse, there are a lot more people in my position than there are tenured faculty so the competition was and is stiff.
In the current CAUT Bulletin, Tom Booth writes about this further in the context of academic freedom and the US system:
It is disturbing to note that only 41 per cent of faculty members in universities in the U.S. are tenured or tenure stream. The majority of those will be retiring in the next 10 years and unless the current trend to replace tenured academic staff with non-tenure track appointments is reversed, the next decade will likely see tenured faculty representing only 20 per cent of American university teaching and research staff.
Earlier research by Harold Bauder (PDF) on academic labour segmentation in Canada found, among other things:
In Canada, academic labour has been depreciating over the previous decades. For example, faculty salaries declined relative to total expenditures of universities, from more than 31 percent in the late 1970s to roughly 19 percent in 2004 (CAUT, 2006, 4). In addition, the faculty-student ratio at Canadian universities has changed. While in the 1992-1993 academic year there were on average only 18.8 full-time students for every full-time faculty member, eleven years later there were 23.7 (CAUT, 2006, 51).
For more on the problematic faculty math in Canada, check out the CAUT’s report on the state of university teaching (PDF).
But the research side of the equation isn’t faring much better. Last February I profiled the declining state of things in the United States, which is mirroring Canada. Scientists Johannes Wheeldon and Richard Gordon recently pointed this out in a column in the Huffington Post, stating:
The role of research funding to an academic’s career has never been more important, and yet there is an emerging consensus that the way we organize our system of research grants is broken. While concerns about Canada’s model of research funding are longstanding, in recent years they have become increasingly stark. These include perpetual underfunding, charges of bias, and an over-reliance on the peer review system, which favours orthodoxy over innovation.
In short: if you’re a young researcher your share of the funding pie is smaller than ever. If you want to innovate, your prospects are even worse.
Yes, but what about academic freedom? That does exist, for now. In all my years at my university my boss (the Chair or Director) came to visit me only a handful of times. No one checks when I arrive or leave, nobody even cares if I work from home or a desert island. As long as I show up for my teaching duties, respect academic procedures, and continue to produce good research, the university system doesn’t much care what I do with my day-to-day activities. That is a real blessing and supports creative thinking about big problems.
Yet, while I could sleep in almost any day, I never did. I could take a long weekend anytime, but instead was in the office. Visiting a cottage? Sure, so long as there was Internet access and plugs for a laptop. See the world! — just make sure you keep on top of your email. Family time is wonderful as long as there’s time to write before and after. My average workweek was 90 hours for the past two years. And while work does inspire me, too much of anything is not good for long periods of time. Oh yes, and did I mention that I study health promotion? The power of social norms, and of what Pierre Bourdieu calls habitus, is akin to the Death Star‘s tractor beam, only you don’t see it; it’s deep within us.
None of these were enforced activities, but they are the norm. My faculty colleagues — young and old, tenured or not — work long hours all year. The system is set up for it. For example, the Tri-Council grants in Canada — SSHRC, CIHR, and NSERC – and many of the major health charities that fund research all have deadlines that require registration (pre-proposals) at times between August 15th and October 30th, which happens to coincide with things like: 1) summer vacation for most North Americans and Europeans (in August and the months before when you organize the research plan), 2) start of classes and the academic year, 3) orientation of new students, and 4) student awards and bursaries (for which we serve as referees to write letters of support). Just try and get a date for anything longer than lunch with an academic doing research during this time.
Grading? Our exams and papers are due at my institution on December 21, which means Hanukah, Christmas, Kwanzaa, and New Years Day are all grading holidays. Pass the gravy on this turkey.
And we are the ones who invented this system!
None of what I am writing is meant to garner sympathy for me personally. I made these choices in my career with a hope it would lead to something good for the world, myself and those I care about. Sometimes I succeeded and others not, but they were my choices that I live with, whether wise or not. What I am doing is trying to paint the picture for others about the environment that I and other faculty and staff like me live in every day. This is not the idyllic life that the public thinks it is. And while the professor is still among the most respected professions out there, it will fall flat if times get tight and people are looking for more for less and we faculty are seen (misguidedly) as having more while others have less.
But what about pay? That’s a tricky one. I get a wage that I have no complaints about in absolute terms. I make well above the Canadian average, but not something that is anywhere close to being indexed to education. Considering I have 16 years of post-secondary education (education that I paid to have), I could have done a lot better going into other fields. But as a wise colleague of mine once said about pay in professor-dom: “you won’t get rich, but you’ll never be poor” . That counts for something.
At the same time, on an hourly basis, my pay goes downhill. And at some point, time becomes worth far more than anything I have to offer financially. I also have the support to spend money on my job. Indeed, teaching supplies, continuous learning, staff rewards (and continued education for them), and the incidentals from the job cost money for which there are few mechanism to pay from in most traditional centres. They come from somewhere and that’s the faculty member’s pocket, just as elementary and secondary school teachers often pay for school supplies. We believe so strongly in what we do we’ll do it without recognition or compensation.
We are a tribe that is as foreign to the public as the San people in Africa were to the first European explorers. But like a tribe we have behaviours that are not always pro-social.
Academia has been considered gang-like in its behaviour:
Just as members of street gangs earn most of their livelihood from theft, academics gain most of theirs from careers. Being a member in good standing of a gang and a supergang is crucially important for advancement of one’s career. There is little chance of advancement in the academy without hard work, but flaunting membership in gang and clan can certainly supplement or even substitute for talent and intelligence. Clearly and repeatedly showing one’s loyalty to these groups can be most helpful in obtaining research grants and acceptance of publications, twin lifebloods of the academic career. – Scheff, T.J. (1995), Academic gangs. Crime, Law, and Social Change 23: 157-162.
It is a strange space to be in. Alien.
While I don’t particularly like the system we’ve created, it is what it is — today. But it can change if we — all of us — stop and pay attention to what it really is and work to make it what we want it to be. Well established institutions are hard to change because the practices within them are so deeply entrenched in a culture that is often accepted as is.
As this series unfolds, I’ll explore some more of these themes in detail.
The message to my fellow academics is this:
The modern university system has a lot of problems, yet our mandate and potential to contribute to the world through our research, teaching and social consulting is as big and needed as ever. Society needs us when we’re at our best, but we are doing more to undermine our best at our peril. We need to fix the system now otherwise forces beyond ourselves will force the changes on us in ways that may not be conducive to good scholarship, equity, and effective public service.
For those who like the system as it is, let me leave you with this quote from Guiseppe di Lampedusa’s book, The Leopard:
If we want things to stay as they are, things will have to change..
I don’t think we want things to stay as they are. But, we do want some things to stay the same.
This is the latest in the Alien Shores series of reflections on life in academia from one who is about to leave it.
* Photo Mystery by UKTara used under Creative Commons Licence from Deviant Art.
** and yes, I know that un-building is not correct use of the English language. But deconstruct, take down, demolish or pull apart don’t work here. I am using my academic privilege to make words up 
Unravel the mystery and crank up Sarah McLachlan and think about what these words mean for our business…
Sarah McLachlan “Building a Mystery”: excerpt
You live in a church
Where you sleep with voodoo dolls
And you won’t give up the search
For the ghosts in the halls
You wear sandals in the snow
And a smile that won’t wash away
Can you look out the window
Without your shadow getting in the way?You’re so beautiful
With an edge and charm
But so careful
When I’m in your arms[Chorus]
‘Cause you’re working
Building a mystery
Holding on and holding it in
Yeah you’re working
Building a mystery
And choosing so carefully
The Persistent Myth of the Lone Genius in Art and Science
Posted: June 7, 2011 Filed under: education & learning, innovation, science & technology | Tags: collaboration, creativity, genius, innovation, Keith Sawyer Comments Off
Alone in the Sky
Of the many persistent myths about innovation, the lone genius is about the most sticky. Continued research shows how untrue this is.
When we consider achievement in science, we think of individuals. The Nobel Prize might be awarded to small groups of individuals, but they are not awarded to teams. Indeed, team science is not something recognized in the same way that we recognize individual achievement.
There is a persistent myth that discovery is best achieved through individual genius applied to a problem. The “eureka!” moment is played up in science fiction stories and films from Frankenstein to Back to the Future.
It is a myth because research on creativity and innovation consistently shows that hard work and persistence beats out raw skill (which is a myth in itself) . Indeed, people become skilled through some natural talent, but mostly hard work, concentration and consistent practice.
Yesterday, Keith Sawyer, a psychologist and researcher of innovation and creativity, asked that the lone genius myth to be put to rest. I wish that luck and support the idea, but don’t suspect it will come true. He writes (on artists):
The Wall Street Journal of June 3, 2011 reports that many contemporary artists use an equally collaborative studio system. The article (by Stan Stesser) reports that Jeff Koons has 150 people on his payroll and readily admits that he never paints himself. A long list of expensive, widely collected artists are named in the article; apparently, it is not a secret that the “artist” doesn’t actually execute the work himself. There’s no misreprentation here; gallery owners and dealers tell potential buyers the actual story, and buyers still collect the works.
The earliest return to a collaborative studio model was probably Andy Warhol in the 1960s, who called his studio “The Factory” and famously said “I want to be a machine.” So the “lone genius” model of the painter has been fading for several decades already. In the greater scheme of history, the Romantic era belief that the painter was an inspired solitary genius has been a small blip: slightly over 100 years. Painter as lone genius: Rest In Peace.
The notion that creativity is an individual thing might have to do with the uniqueness in which we all experience creativity. While each of us might create a idea from different things — ideas, feelings, abstract experience — we put such sensory stimuli together in manners that must make coherent sense to understand them. To communicate them, we need to make sure that these ideas are coherent beyond ourselves to others and the best way to do that is to get the input of others in the process. It means, collaboration.
Whether it is science or art, the notion of teams, collaboration, sharing, and co-creating is something too often denied or left unexplored in daily practice. In its place, the myths of the lone genius. It is why faculty are rewarded for being the first author on a paper or grant rather than being part of a team or collaboratory. It is why we do individual performance appraisals for most people. It is also why students are graded on their own work, with little attention to how they brought that work to others to share.
Dr. Sawyer’s declaration of the lone genius as dead is optimistic. What is needed now is something to make it realistic.
Interested in learning more about this topic? Visit the library section of Censemaking.
*** Photo lone giraffe by eddiemalone used under Creative Commons License from Flickr
Design and Science: An Opportunity for Knowledge Translation and Exchange??
Posted: February 27, 2011 Filed under: art & design, design thinking, knowledge translation, research, science & technology | Tags: collaboration, design, discovery, IDEO, knowledge translation, science, Tim Brown, translational research 3 Comments »
Design of Science or Science of Design
IDEO’s CEO Tim Brown recently observed a renewed interest in design within science, but is that same feeling reciprocated and, if so, what does that mean for both fields?
Tim Brown, author and CEO of the renowned design firm IDEO, recently posted on the firm’s blog some observations he had on the relationship between design and science.
In that post, he asks some important questions of both designers and scientists.
I wonder how much might be gained if designers had a deeper understanding of the science behind synthetic biology and genomics? Or nanotechnology? Or robotics? Could designers help scientists better see the implications and opportunities of the technologies they are creating? Might better educated and aware designers be in a position to challenge the assumptions of the science or reinterpret them in innovative ways? Might they do a better job of fitting the new science into our lives so that we can gain more benefit?
The question of the relationship between designers and the science used to inform the materials or products they us is one that will play out differently depending on the person and context. However, I would welcome the opportunity for designers to challenge much of what science — and I use that term broadly — does, particularly with regards to the application or translation of scientific research into policies and practices. Indeed, this is a frontier where designers have tremendous opportunities to contribute as I’ve discussed elsewhere.
Knowledge translation and translational research are two of the most vexing problem domains in science, particularly with health. Despite years of efforts, scientists haven’t been able to advance the integration of what is learned into what is done at a rate that is acceptable to policy makers, practitioners and the public alike. The problem isn’t just with scientists, but the way the scientific enterprise has been engineered.
Scientists haven’t had to consider design before. Tim Brown asks further questions about what it might be like if they did:
If scientists were more comfortable with intuitive nature of design might they ask more interesting questions? The best scientists often show great leaps of intuition as they develop new hypotheses and yet so much modern science seems to be a dreary methodical process that answers ever more incremental questions. If scientists had some of the skills of designers might they be better able to communicate their new discoveries to the public?
In this case, it might be the chance for designers to step up and consider ways to work with those in science to create better institutional policies, laboratories, and collaborative environments to foster the kind of linkages necessary for effective knowledge translation.
Knowledge translation models, such as the widely cited one conceived of by the Canadian Institutes for Health Research, are both process and outcome oriented; ideal for designers. KT is a designed process and the more it is approached through the lens of design thinking, the greater likelihood we’ll get a system that reflects its intentions better than what we currently have.
The Myth of (Complex) Decision Making
Posted: February 18, 2011 Filed under: complexity, science & technology | Tags: artificial intelligence, complexity, computers, knowledge translation 1 Comment »
Can computers contemplate how ridiculous they look in a cowboy hat?
This week Watson, the latest IBM-created supercomputer trounced two of Jeopardy’s greatest champions at their own game. A sign of the dawn of true artificial intelligence or a red herring?
It seems that this was not a great week for human decision making. After much hype, the human race lost its supreme battle for supremacy on Jeopardy to a computer named Watson. Just as it was said when Garry Kasparov was beaten by another IBM product, Deep Blue, in 1997 as a match of chess supremacy, computers are now considered to be nearing the smarts of humans. It sounds plausible when you consider what kind of knowledge that Jeopardy champions Brad Rutter and Ken Jennings.
The problem is that Jeopardy is about knowledge of facts organized in a catalogue manner. With all due respect to Mssrs Rutter and Jennings, the ability to learn facts is relatively straightforward, even if nearly 99% of the population can’t do it as well as they can. It is a simple input-storage-output problem, whereby data is entered, encoded and stored, and then brought forth upon request. It is the classic example of something that might be simple, but not easy. Clearly, the fact that it took many years of programming to create a computer that could compete with humans shows how difficult the task is.
But the discourse that suggests that Watson and its progeny are about to displace humans is misguided for many reasons, but most notably because of the nature of the problem at hand. Computers are pretty good — perhaps outstanding — at organizing and recalling simple information that is presented in a linear manner. They might also be good at complicated information, the kind that is organized in a manner that has many interlocking components, but still has a relatively ordered manner.
Complexity introduces a whole new realm of problem solving skills that I don’t see computers addressing soon. Complexity adds an exponentially larger amount of information combinations that become contextually bound. Computers are great at processing algothrims, but not so good at reading landscapes like humans are. We’re wired for it.
It’s one thing to ask who wrote the Études-tableaux (“study pictures”), two sets of piano pieces developed by Sergei Rachmaninoff, and quite another to explain how the piece can be used to understand the mood and spirit of the Fair that was invoked by the piece. The former is simple, the latter is more complex as it is open to multiple interpretations and contexts, which overlap creating a complex scenario.
A complex scenario cannot be broken down into component parts, because we never have perfect information that is complete. In chess or Jeopardy! we do, we can know all of the answers and possible combinations and thus can program something to respond to it. Too often, this model prevails in our decision-making in public health, where we naively presume we know everything. But that is often a fallacy or at best, a myth.
Fifteen hundred years ago everybody knew the Earth was the center of the universe. Five hundred years ago, everybody knew the Earth was flat, and fifteen minutes ago, you knew that humans were alone on this planet. Imagine what you’ll know tomorrow. – Agent K (played by Tommy Lee Jones), Men in Black
We once knew that health was simple, that research knowledge would always translate into use in a way that researchers intended it to be, and that the problems we faced we would solve using computers. Imagine — to follow Men in Black — what we will know tomorrow?
Embracing Complexity / Science
Posted: December 24, 2010 Filed under: complexity, design thinking, education & learning, innovation, research, science & technology, systems science, systems thinking | Tags: complex adaptive systems, complexity, design, education, knowledge translation, science, systems thinking 1 Comment »
Seeing Complexity for What it Is (CC - Flickr by nerovivo)
SEED magazine recently posted on the concept of early warning signs in complex systems that I found quite provocative and important.
Science is a creative human enterprise. Discoveries are made in the context of our creations: our models and hypotheses about how the world works. Big failures, however, can be a wake-up call about entrenched views, and nothing
produces humility or gains attention faster than an event that blindsides so many so immediately.
There are so many key points in this one phrase that are worth discussing at length.
Science is a creative enterprise . For reasons I’ve discussed elsewhere, I think that science needs to embrace its creative side more than ever and embrace design. This isn’t a universal, but if we (scientists) approached problems from the multidimensional manner in which designers typically approach them, we might create new innovations and discoveries that are different than the ones we’ve made before. Why is this important (beyond the obvious to those whose business it is to discover)? Complexity. The problems we are dealing with now more than ever are likely to be complex ones, which require different ways of approaching them and (some) different science and practice.
And as Albert Einstein famously said (or at least many people have attributed this to him — I can’t verify it, but it works nonetheless):
“We can’t solve problems by using the same kind of thinking we used when we created them.”
Discoveries are made in the context of our creations: our models and hypotheses about how the world works. In public health where I work, the dominant models remain those rooted in reductionist science. We are asked to ‘prove’ the links between certain activity and the outcomes they produce. This works relatively well in areas like sanitation, toxicology, (some) pharmaceutical or vaccination interventions, and injury prevention. It is for these reasons that the top achievements in public health, including massive increases in life expectancy and reductions in premature death took place in the 20th century. But that was then. The challenges we face now are into the realm of complexity, unless we fail to support fundamentals in public health and then we’ll have both simple and complex challenges on our hands. The point here is that our models will only take us so far without some acknowledgement of the complexity of the problems they seek to explain. The context of our creations is complexity.
Big failures, however, can be a wake-up call about entrenched views. The key term here is “entrenched views” . My colleagues Alex Jadad, Murray Enkin, Shalom Glouberman and others once had a group called the Clinamen collaborative that wrote a great piece on the problem of complexity when dealing with entrenched health care practices. Their recommendations are essentially:
1) there are no recipes for universal success,
2) pay attention to local conditions,
3) intervene small and often and then scale,
4) aim for stability first, then change.
In science, we’re failing a lot and rather than see this as a potential positive, I see more conservative approaches to science based on risk aversion. Providing support for smaller, rapid response scientific studies that are encouraged to fail will do more than these big, non-adventurous team projects that provide high-level window dressing for grant funders and avoid making anyone look bad.
…and nothing produces humility or gains attention faster than an event that blindsides so many so immediately. Humility is a word that is too often absent from my profession. I’m not talking about the kind of humility that comes from acknowledging the limitations of a scientific study or the recommendations of a report. I am speaking of true humility, where one “seeks to first understand, then to be understood”. Indeed, I would argue that we are lousy at both more often than we’re successful. Our understanding comes from a scientific perspective that holds us up as the experts. Once you’ve labelled someone or yourself an “expert” conversations immediately shift. Watch a classroom where the instructor insists on pure lecturing, being called “Dr.” and where “right” and “wrong” are regular parts of the conversation. Then watch a classroom where students learn from each other, are encouraged to share their experience and challenge the material, where the professor doesn’t push her or his titles and credentials, and where there is interaction between everyone. You’ll see a very different sense of humility from students and teachers alike.
When I encounter others on genuine, authentic and intimate level of learning I never cease to be left in awe. That comes from humility and is something I was fortunate to have modeled to me. I was once told by a retiring professor who was leaving on the day I was convocating from my undergraduate degree:
“When I was in my undergraduate, I new everything. Now that I am a retired professor, I realize I know nothing. Every year of learning serves to teach me that I know less and less.”
The SEED article goes on to point to the current problems in science in dealing with complexity and the imperative towards collaboration and cross-disciplinary engagement:
Examples of catastrophic and systemic changes have been gathering in a variety of fields, typically in specialized contexts with little cross-connection. Only recently have we begun to look for generic patterns in the web of linked causes and effects that puts disparate events into a common framework—a framework that operates on a sufficiently high level to include geologic climate shifts, epileptic seizures, market and fishery crashes, and rapid shifts from healthy ecosystems to biological deserts.
The main themes of this framework are twofold: First, they are all complex systems of interconnected and interdependent parts. Second, they are nonlinear, non-equilibrium systems that can undergo rapid and drastic state changes.
Complex systems require the kind of deep attention that science brings, the spirit of engagement and problem solving that designers offer, and a space to bring them together. With their focus on reductionist science and the lack of embrace of design, universities haven’t been the home to this kind of thinking. But things can change because, after all, this is a complex dynamic system we’re talking about.
The Science of Design & the Design of Science
Posted: December 21, 2010 Filed under: behaviour change, design thinking, evaluation, research, science & technology | Tags: design education, design science, design thinking, evaluation, innovation, research, science 2 Comments »
Glasgow Science Centre (by bruce89, used under Creative Commons Licence)
As the holidays approach I’ve been spending an increasing amount of time looking at a field that has become my passion: design. Design is relevant to my work in part because it frequently deals with the complex, requires excellent communication, and as Herbert Simon would suggest, is all about those interest in changing existing situations into preferred ones.
Yet for all the creativity, innovation and practicality that design has I find it lacking in a certain scientific rigour that it requires to gain the widespread acceptance it deserves.
This is not to say that designers do not employ rigorous methods or that there is no science informing design. For example, architecture, a field where design is embedded and entwined, employs high levels of both rigour and science in its practice. The issue isn’t that these two concepts aren’t applied, they just aren’t applied to each other. I was heartened this week to see Dexigner profile a new pamphlet on the science of design. Although true in spirit, it wasn’t what I expected to see as it largely profiled ways to assess the quality of design projects from the perspective of design.
What if we could assess the impact of design on a larger scale, a social and human scale?
Interaction designers speak of this need to connect to the human in design work. The emergent field of social design exemplified by groups like Design 21 who aim to produce better products for social good. All of this is important, but it’s important largely because we say it is so. Rhetorical arguments are fine, but at some point design needs to confront the problem of evidence.
Does “good” design lead to better products than “bad” design?
What components of design thinking are best suited to addressing certain kinds of problems? Or are there simply problems that design thinking is just better at addressing than other ways of approaching them?
What methods of learning produce effective design thinkers? And what is effective design thinking anyway? Does it exist?
What is the comparative advantage of a design-forward approach to addressing complex problems than one where design is less articulated or not at all?
These are just some of the many questions that there seems to be little evidence in support of. A scientific approach to design might be one of the first ways of addressing this. In doing so, a scientifically-grounded design field is far more likely to garner support of decision makers who are the ones who will approve and fund the kind of projects that can have wide-scale impact. Design is making serious in-roads to fields such as business, education, and health, but it represents a niche market when it has the potential to be much larger.
Roger Martin has argued that the reliance on scientific approaches to problem solving runs counter to much of design thinking. This assumes that science is applied in a very detached, prescriptive manner, which is common, but not the only way. Micheal Gibbons and colleagues have described two forms of science, which they call Mode I and Mode II science. The first Mode is the one that most people think of when they hear the term “scientist”. It is of the (usually) lone researcher working in a lab on problems that are driven by curiosity with the aim of generating discoveries. For this reason, it is often referred to as discovery-oriented research.
Mode 2 research is designed to be problem-centred and aimed at answering questions posed by practical issues and has a strong emphasis on knowledge translation. This is an area more accustomed to the designer.
Design presents the opportunity to transcend both of these Modes into something akin to Mode 3 research, which I surmise is a blend of the abductive reasoning inherent in Roger Martin’s view of design thinking and the discovery-oriented approach that goes beyond just the problem to create value beyond the contracted issue. A design-oriented approach to the science of design would involve leveraging the creative processes of designers with some of the tools and methods accustomed to researchers in Mode 1 and 2 science. Can we not do detailed ethnographic studies looking at the process of design itself? Is there any reason why we cannot, with limits acknowledged and in appropriate contexts, attempt to do randomized controlled trials looking at certain design thinking activities and situations?
If design is to make a leap beyond niche market situations, a new field must dawn within design + science and that is the science of design and the design of science.
Creating the Future Through Systems-Design Thinking
Posted: August 20, 2010 Filed under: complexity, design thinking, eHealth, innovation, science & technology, systems science, systems thinking | Tags: complexity science, design thinking, eHealth, ICT, innovation, organizational change, social innovation, systems thinking Comments Off
Back to the Future
Arturo Muente-Kunigami wrote in the World Bank’s Information and Communication Technology blog about the challenge of innovation and putting new information technology into practice in governments worldwide. Muente-Kunigami writes:
Most governments that introduce ICTs in their service delivery structure have basically applied technology to the exact same workflow they had before, replacing papers with emails and signatures with digital certificates. But ICTs in general – and broadband in particular – do not just improve the efficiency of governments. They have the potential to transform how governments work, redefining their relationship with citizens and expanding the array of services and transactions that could be provided and implemented.
This, however, is a very risky proposition for governments. And if most private companies rely on analytical thinking due to their overall aversion to risk, governments in most developing countries have a much less functional innovation system (in many cases, equivalent to a “copy-paste” function to be applied to “best practices” in other countries).
This is basically a ‘back-to-the-future’ problem: how to use the past to shape the future? How do we create best practices in areas where there are constant shifts, changes and altered contexts? Marty Neumaier would argue that we can’t. This is a design problem, not a knowledge transfer one. Muente-Kunigami also recognizes the potential for design thinking here and argues that governments need to follow their private sector peers in applying it to ICT and innovation:
So what is design thinking for governments anyway? It is not that much different than its private sector equivalent. It is about going back to the basics. And I mean the basics, trying to understand what citizens need from their governments (yes, that far back) and then answering the question: how could governments (hopefully, leveraging the new set of technologies and devices that exist today – and their spread among the general population) be able to satisfy these needs? Then, it is all about building prototypes, testing, trial and error, and of course a good set of evaluation and feedback mechanisms2.
This scary territory for a lot of organizations, particularly governments where decisions are not only shaped by history, but capital P politics. It’s also a language problem: Design gets equated with style instead of substance. Innovation is something done in business, not social and public services. Technology is something for wealthy nerds, not everyday citizens.
Marty Neumaier, Bruce Mau, Roger Martin and other design thinkers have been trying to shape this attitude, but it is an uphill battle. Language is one barrier, thinking differently is another. Both are challenges that I’ll address in future blogs, but the one I want to focus on here is the concept of best practices and the pull of the past on the present. Indeed, this is as good of an example of the power of an idea that you can find. Ideas may be the most powerful concept in human thinking as they shape the cognitive space that we inhabit by illustrating what is, what was, and what could be.
It is when what was becomes what could be that problems occur, particularly in the space of complex systems, which is where a great deal of government’s work is. Best practices is one of those ideas that is seductive because it reduces variation and provides a blueprint for how to handle problems. Indeed, best practices are pretty good when your problems are simple, or maybe even complicated at a very low level of abstraction, but lousy when you get into the realm of complexity.
Another point that Muente-Kunigami hints at is the systems problem; that is, the need to design systems to accommodate change. Implementing ICT-based strategies into a system straight-away is a recipe for failure. Technical systems do not enhance functionality without corresponding changes in social systems. An organizational shift in the way ICT is deployed is necessary if there is much chance of these tools and technologies living up to their potential. This, too, requires design thinking – in creating usable technologies and receptive social systems (including those that are literate enough to take advantage of them).
I would also argue that this approach requires an evaluation approach that supports incremental evaluation and rapid-response feedback like we see in developmental evaluation (PDF), which I discuss elsewhere.
Taken together, the future of government may well be in design, but to create this future we need both the systems and design thinking to make it one day be the past.
