Complexity and Child-Rearing: Why Amy Chua is Neither Right or Wrong
Posted: January 16, 2011 Filed under: complexity, Education & Learning, evaluation, social systems | Tags: Amy Chua, child rearing, children, complex adaptive systems, complexity, developmental evaluation, family, social systems 2 Comments »
Family
Science strives for precision and finding the right or at least the best answers to questions. The science of complexity means shifting our thinking from right answers to appropriate ones and what is best to good. The recent debate over parenting (particularly among Chinese families) illustrates how framing the issue and the outcomes makes a big difference.
Amy Chua “is probably the most reviled mother in America” according to Margaret Wente writing in the Globe and Mail. In her column, Wente is looking at the phenomenon that Chua writes about in her new book on parenting, Battle Hymn of the Tiger Mother. What has drawn such attention to Chua and her book is that she advocates for a very strict method of parenting in a manner that achieves very specific objectives with her children. The payoff? Her children are very successful. This is not a new argument, particularly when it comes to Chinese and other Asian cultural stereotypes. But like many stereotypes, they emerge from something that has a kernel of truth that gets used in ways that gets applied as a universal, rather than in context. Judging by the comments on the original Wall Street Journal story that attracted attention and the Globe and Mail’s review page, I would say that there is some truth to this stereotype and some wild overstatements as this gets applied universally to parenting.
A summary of the comments and commentary on this, crudely, fall into two camps (which, for reasons I’ll elaborate on later is ironic given how problematic the whole idea of reducing arguments into twos is, but go with me on this): 1) Amy Chua is recalling my childhood or parenting reality and its nice to hear someone acknowledge it and 2) Amy Chua is promoting harmful, inaccurate, racist stereotypes.
Child-raising is a common example of a complex system, showing how past experience is not necessarily a formula for future success. Thus, you can have the same parents, same household, even same genes (in the case of twins) and get two very different outcomes. Complex systems do not lend themselves to recipes or “best practices”. You can’t shoehorn complexity into “right” / “wrong” and either/or positions.
What is interesting about the discussion around Chua’s parenting style, which she claims reflects traditional Chinese behaviour (I am not Chinese so this is out of my realm for comment) is that the focus is on raising successful children, not necessarily happy, well-adjusted, self-determined or even creative children. And success, in the terms referred to means achieving or exceeding certain prescriptive standards for socially acceptable activities. This might mean acceptance at a prestigious school, an error-free performance, or a straight A report card. It is a rather narrowly proscribed form of achievement based upon a particular set of cultural conditions and assumptions.
One of the problems I see in this debate is that people are conflating the two types of outcomes, which is where the complexity comes in. What Chua has done is actually refer to parenting in line with a set of complicated activities and outputs, rather than part of a complex system. She has sought to reduce the complexity in the system of parenting by focusing on issues of tangible measurement and has created a familial system aimed at reducing the likelihood that these objectives will not be met. Her benchmark for success are visible outcomes, not the kind that come from growing one’s self-esteem, building true friendships, or learning to love. This isn’t to say that her children or those raised by “tiger parents” don’t have such experiences, but this isn’t what her method of parenting is focused on. And therein lies the rub and why much of the debate surrounding Chua’s book is misaligned.
If you are assessing the life of a person and their total experience as a human being, Chua’s method of parenting is quite problematic. Success in this situation has many different paths and may not even have a clear outcome. What does it really mean to be successful if love, happiness, and self-fulfilment is the outcome of interest – particularly when all of those things change and evolve over a week, a month or a lifetime? It is the kind of task that one might use developmental evaluation to assess if you were looking to determine what kind of impact a particular form of parenting has on children’s lives. Margaret Wente’s article uses some examples of “tiger parenting” outcomes with those who achieved much “success” using the benchmarks of externally validated standards and found mixed outcomes when “success” was viewed as part of a whole person. Andre Agassi grew to loathe tennis because of his experience, while Lang Lang appears to love his piano playing. Both have achieved success in some ways, but not all.
These two examples also go to show that with human systems, there is little ability to truly control the outcomes and process. Even if one can reduce outcomes to complicated or simplistic terms, those outcomes are still influenced by complex interactions. Complicated systems can be embedded within complex ones or the opposite. So no matter what kind of prescription a person uses, no matter how tight the controls are put, the influence of complexity has a way of finding itself into human affairs.
So is Amy Chua’s method of parenting successful or not, supportive or harmful, right or wrong? The answer is yes.
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.
More Design Thinking & Evaluation
Posted: November 15, 2010 Filed under: design thinking, Education & Learning, evaluation, innovation | Tags: creativity, design thinking, developmental evaluation, evaluation, innovation Leave a comment »
Capturing Design in Evaluation (CameraNight by Dream Sky, Used under Creative Commons License)
On the last day of the American Evaluation Association conference, which wrapped up on Saturday, I participated in an interactive session on design thinking and evaluation by a group from the Savannah College of Art and Design.
One of the first things that was presented was some of the language of design thinking for those in the audience who are not accustomed to this way of approaching problems (which I suspect was most of those in attendance).
At the heart of this was the importance of praxis, which is the link between theory, design principles and practice (see below)
Design Thinking
As part of this perspective is the belief that design is less a field about the creation of things on their own, but rather a problem solving discipline.
Design is a problem solving discipline
When conceived of this way, it becomes easier to see why design thinking is so important and more than a passing fad. Inherent in this way of thinking are principles that demand inclusion of multiple perspectives on the problem, collaborative ideation, and purposeful wandering through a subject matter.
Another is to view design as serious play to support learning.
Imagine taking the perspective of design as serious play to support learning?
The presenters also introduced a quote from Bruce Mau, which I will inaccurately capture here, but is akin to this:
One of the revelations in the studio is that life is something that we create every single day. We create our space and place.
Within this approach is a shift from sympathy with others in the world, to empathy. It is less about evaluating the world, but rather engaging with it to come up with new insights that can inform its further development. This is really a nod (in my view) to developmental evaluation.
The audience was enthralled and engaged and, I hope, willing to take the concept of design and design thinking further in their work as evaluators. In doing so, I can only hope that evaluation becomes one of the homes for design thinking beyond the realm of business and industrial arts.
Design Thinking & Evaluation
Posted: November 13, 2010 Filed under: design thinking, Education & Learning, evaluation, innovation, research | Tags: conference, design, design thinking, developmental evaluation, education, empathy, evaluation, innovation, social innovation, utilization-focused evaluation 2 Comments »
Design Thinking Meets Evaluation (by Lumaxart, Creative Commons Licence)
This morning at the American Evaluation Association meeting in San Antonio I attended a session very near and dear to my heart: design thinking and evaluation.
I have been a staunch believer that design thinking ought to be one of the most prominent tools for evaluators and that evaluation ought to be one of the principal components of any design thinking strategy. This morning, I was with my “peeps”.
Specifically, I was with Ching Ching Yap, Christine Miller and Robert Fee and about 35 other early risers hoping to learn about ways in which the Savannah College of Art and Design (SCAD) uses design thinking in support of their programs and evaluations.
The presenters went through a series of outlines for design thinking and what it is (more on that in a follow-up post), but what I wanted to focus on here was the way in which evaluation and design thinking fits together more broadly.
Design thinking is an approach that encourages participatory engagement in planning and setting out objectives, as well as in ideation, development, prototyping, testing, and refinement. In evaluation terms, it is akin to action research and utilization-focused evaluation (PDF). But perhaps its most close correlate is with Developmental evaluation (DE). DE is an approach that uses complexity-science concepts to inform an iterative approach to evaluation that is centred on innovation, the discovery of something new (or adaptation of something into something else) and the application of that knowledge to problem solving.
Indeed, the speakers today positioned design thinking as a means of problem solving.
Evaluation , at least DE, is about problem solving by collecting the data used as a form of feedback to inform the next iteration of decision making. It also is a form of evaluation that is intimately connected to program planning.
What design thinking offers is a way to extend that planning in new ways that optimizes opportunities for feedback, new information, participation, and creative interaction. Design thinking approaches, like the workshop today, also focuses on people’s felt needs and experiences, not just their ideas. In our session today, six audience members were recruited to play the role of either three facets of a store clerk or three facets of a customer — the rational, emotional and executive mind of each. A customer comes looking for a solution to a home improvement/repair problem, not sure of what she needs, while the store clerk tries to help.
What this design-oriented approach does is greatly enhance the participant’s sense of the whole, what the needs and desires and fears both parties are dealing with, not just the executive or rational elements. More importantly, this strategy looks at how these different components might interact by simulating a condition in which they might play out. Time didn’t allow us to explore what might have happened had we NOT done this and just designed an evaluation to capture the experience, but I can confidently say that this exercise got me thinking about all the different elements that could and indeed SHOULD be considered if trying to understand and evaluate an interaction is desired.
If design thinking isn’t a core competency of evaluation, perhaps we might want to consider it.
Systems Thinking, Logic Models and Evaluation
Posted: November 12, 2010 Filed under: complexity, evaluation, research, systems thinking | Tags: complexity, conference, evaluation, systems thinking 1 Comment »
San Antonio at Night, by Corey Leopold (CC License)
The American Evaluation Association conference is on right now in San Antonio and with hundreds of sessions spread over four days it is hard to focus on just one thing. For those interested in systems approaches to evaluation, the conference has had a wealth of learning opportunities.
The highlight was a session on systems approaches to understanding one of evaluation’s staples: the program logic model.
The speakers, Patricia Rogers from the Royal Melbourne Institute of Technology, and consultants Richard Hummelbrunner and Bob Williams spoke to the challenges posed with the traditional forms of logic models by looking at the concepts of beauty, truth and justice. These model forms tend to take the shape of the box model (the approach most common in North America), the outcome hierarchy model, and the logic framework, which is popular in international development work.
The latter model was the focus of Hummelbrunner’s talk, which critiqued the ‘log frame’ approach and showed how its highly structured approach to conceptualizing programs tends to lead to a preoccupation with the wrong things and a rigidity in the way programs are approached. They work well in environments that are linear, straightforward, and in situations where funders need simple, rapid overviews of programs. But as Hummelbrunner says:
Logframes fail in messy environments
The reason is often that people make assumptions of simplicity when really such programs are complicated or complex. Patricia Rogers illustrated ways of conceptualizing programs using the traditional box models, but showing how different program outcomes could emerge from one program, or that there may be the need to have multiple programs working simultaneously to achieve a particular outcome.
What Rogers emphasized was the need for logic models to have a sense of beauty to it.
Logic models need to be beautiful, to energize people. It’s can’t just be the equivalent of a wiring diagram for a program.
According to Rogers, the process of developing a logic model is most effective when it maintains harmony between the program and the people within it. Too often such model development processes are dispiriting events rather than exciting ones.
Bob Williams concluded the session by furthering the discussion of beauty, truth and justice, by expanding the definitions of these terms within the context of logic models. Beauty is the essence of relationships, which is what logic models show. Truth is about providing opportunities for multiple perspectives on a program. And a boundary critique is a an opportunity for ethical decision making.
On that last point, Williams made some important arguments about how, in systems related research and evaluation, the act of choosing a boundary is a profound ethical decision. Who is in, who is out, what counts and what does not are all critical questions to the issue of justice.
To conclude, Williams also challenged us to look at models in new ways, asking:
Why should models be the servant of data, rather than have data serve the models?
In this last point, Williams highlights the current debates within the knowledge management community, which is dealing with a decade where trillions of points of data have been generated to make policy and programming decisions, yet better decisions still elude us. Is more data, better?
The session was a wonderful puctuation to the day and really advanced the discussion on something so fundamental as logic models, yet took us to a new set of places by considering them as things of artful design, beauty, ethical decision making tools, and vehicles for exploring the truths that we live. Pretty profound stuff for a session on something seemingly benign as a planning tool.
The session ended with a great question from Bob Williams to the audience that speaks to why systems are also about the people within them and emplored evaluators to consider:
Why don’t we start with the people first instead of the intervention, rather than the other way around like we normally do?
American Evaluation Association Conference
Posted: November 9, 2010 Filed under: evaluation, systems thinking | Tags: developmental evaluation, evaluation, research, systems thinking Leave a comment »Over the next few days I’ll be attending the American Evaluation Association conference in San Antonio, Texas. The conference, the biggest gathering of evaluators in the world. Depending on the Internet connections, I will try to do some live tweeting from my @cdnorman and some blogging reflections along the way, so do follow along if you’re interested. In addition to presenting some of the work that I’ve been engaged in on team science with my colleagues at the University of British Columbia and Texas Tech University, I will be looking to connect more with those groups and individuals doing work on systems evaluation and developmental evaluation with an eye to spotting the trends and developments (no pun intended) in those fields.
Evaluation is an interesting area to be a part of. It has no disciplinary home, a set of common practices, but much diversity as well and brings together a fascinating blend of people from all walks of professional life.
Stay tuned.
Does Solitude Enhance Creativity? A Critique of Susan Cain’s Attack on Collaboration
Posted: January 16, 2012 Filed under: Education & Learning, evaluation, innovation, research, Science & technology | Tags: collaboration, innovation, team science, transdisciplinary research 43 Comments »I’ve just read a New York Times article by Susan Cain, author of the forthcoming book Quiet: The Power of Introverts in a World That Can’t Stop Talking. It’s the frustrated cry of a true introvert. Cain is clearly tired of everyone touting the benefits of collaboration; some people, herself included, just want to be left alone. And, she argues, those are the people who really come up with all of the great ideas.
There’s a grain of truth to Cain’s claim: Psychologists who study creativity know that it requires both solitude and collaboration. Exceptional creativity involves a lot of hard work, and that often happens in solitude. But Cain misses the big picture: Researchers have found that breakthrough ideas are largely due to exchange and interaction, and that’s because breakthrough ideas always involve combinations of very different ideas. (Matt Ridley famously calls it “ideas having sex.”)
In 2007, my book Group Genius was partly responsible for what Susan Cain calls dismissively “the rise of the new groupthink.” So I feel like I’ve been called out to respond. Yes, solitude plays a role in the creative process, but Cain overstates her case and misrepresents some of the research. Here are five specific examples of misleading or incorrect statements in her article:
1. Cain says that research by Dr. Mihaly Csikszentmihalyi found that exceptional creators are more likely to be introverted. Csikszentmihalyi was my graduate advisor, so I know that what his research actually found is that “Creative people tend to be both extroverted and introverted….[they] exhibit both traits simultaneously.” Reviewing all of the studies of creativity and extroversion using the “five-factor” personality model, most studies don’t show any relation between creativity and either introversion or extraversion. A few studies show a small relation, and for those, it’s always a positive relation between creativity and extraversion. (see my book Explaining Creativity for the details.)
2. Cain argues that Steve Wozniak, co-founder of Apple with Steve Jobs, is a classic introvert and he’s the one who actually invented the Apple personal computer. She grants that Wozniak never would have had the idea if he hadn’t been exchanging ideas with the Homebrew Computer Club, and he knows that Wozniak’s computer never would have been built and sold if it weren’t for his collaboration with Steve Jobs. It’s true that Wozniak had to go home and build the thing alone…but the real creativity came from collaboration.
And the Macintosh computer–which was a much more innovative product, with the graphic user interface that the one we still use today–resulted from Steve Jobs’ networking and idea exchange with Xerox PARC, the lab where the windows-and-mouse technology was first demonstrated. No solitude story there.
3. Cain is critical of the new trend of using collaborative groups in school classrooms. But in the New York Times article, she doesn’t give any reasons to dislike this, and doesn’t cite any research on the topic (maybe she will in the forthcoming book). Collaboration and learning is one of my research topics, so I know that there’s a huge volume of evidence–going back three decades–showing that collaborative interaction enhances learning. Of course, it has to be done in the right way, and no doubt there are teachers who form student groups in ineffective ways, but you can’t base an argument on a few ineffective teachers.
Regarding learning and mastery, Cain cites Anders Ericsson’s expertise research correctly; that research shows it takes 10,000 hours of mostly solitary practice to become an expert. And I too have argued that this is a prerequisite to a creative life. But that’s not where new ideas come from; that’s just the base of knowledge you need before you’re able to play the game, to combine great ideas and to recognize good ideas.
4. Cain argues that the “Coding War Games” study shows that solitary computer programmers perform better than programmers that don’t get any privacy. But I’ve done studies of pair programming–a core technique of the popular approach known as “extreme coding”–and the research convincingly demonstrates that pair programming results in better computer programs.
5. Cain is absolutely right about the research showing that brainstorming groups generate fewer ideas than the same number of solitary people working alone. But there’s an important exception to this research: if the problems are complex, or if they are visual or spatial, then groups usually outperform solo workers. And in most real-world organizations, problems are pretty complex–not the simple word-generation tasks used in brainstorming experiments.
Cain has read a broad range of important research, and she gets some things right. And she’s smart enough to realize that the more defensible position is that you need both solitude and collaboration. But in her desire to elevate the role of solitude, Cain’s article misrepresents the research. And the research has found just the opposite: collaboration is the key to creativity.
There must be a lot of introverts out there, because when I looked at her book on Amazon.com today, it’s one of the top 100 best selling books. Cain’s book will no doubt appeal to those readers who enjoy solitary work, who’ve sat in endless time-wasting meetings, who did a group project in high school with a bunch of slackers…come to think of it, that pretty much describes everyone, including me! But don’t let yourself be misled by your own bad experiences with groups. The science of creativity shows that exceptional, successful creativity depends on groups, networks, and conversation. If you hole up alone at home, I guarantee you will be less creative.
Developmental Evaluation: Problems and Opportunities with a Complex Concept
Posted: July 31, 2010 Filed under: complexity, evaluation, research, social systems, Systems science, systems thinking | Tags: complexity, developmental evaluation, eHealth, evaluation, knowledge integration, knowledge translation, public health, systems thinking 11 Comments »
Everyone's Talking About Developmental Evaluation
“When it rains, it pours” so says the aphorism about how things tend to cluster. Albert Lazlo-Barabasi has found that pattern to be indicative of a larger complex phenomenon that he calls ‘bursts‘, something worth discussing in another post.
This week, that ‘thing’ seems to be developmental evaluation. I’ve had more conversations, emails and information nuggets placed in my consciousness this week than I have in a long time. It must be worth a post.
Developmental evaluation is a concept widely attributed to Michael Quinn Patton, a true leader in the field of evaluation and its influence on program development and planning. Patton first wrote about the concept in the early 1990′s, although the concept didn’t really take off until recently in parallel with the growing popularity of complexity science and systems thinking approaches to understanding health and human services.
At its root, Developmental Evaluation (DE) is about evaluating a program in ‘real time’ by looking at programs as evolving, complex adaptive systems operating in ecologies that share this same set of organizing principles. This means that there is no definitive manner to assess program impact in concrete terms, nor is any process that is documented through evaluation likely to reveal absolute truths about the manner in which a program will operate in the future or in another context. To traditional evaluators or scientists, this is pure folly, madness or both. When your business is coming up with the answer to a problem, any method that fails to give you ‘the’ answer is problematic.
But as American literary critic H.L. Mencken noted:
“There is always an easy solution to every human problem — neat, plausible and wrong”
Traditional evaluation methods work when problems are simple or even complicated, but rarely do they provide the insight necessary for programs with complex interactions. Most community-based social services fall into this realm as does much of the work done in public health, eHealth, and education. The reason is that there are few ways to standardize programs that are designed to adapt to changing contexts or operate in an environment where there is no stable benchmark to compare.
Public health operates well within the former situation. Disaster management, disease outbreaks, or wide-scale shifts in lifestyle patterns all produce contexts that shift — sometimes radically — so that the practice that works best today, might not be the one that works best tomorrow. We can see this problem demonstrated in the difficulty with ‘best practice’ models of public health and health promotion, which don’t really look like ‘best’ practices, but rather provide some examples of things that worked well in a complex environment. (It is for this reason that I don’t favour or use the term ‘best practice’ in public health, because I simply view too much of it as operating in the realm of the complex, which is something for which the term is not suited.)
eHealth provides an example of the latter. The idea that we can expect to develop, test and implement successful eHealth interventions and tools in a manner that fits with the normal research and evaluation cycle is impractical at best and dangerous at the worst. Three years ago Twitter didn’t exist except in the minds of a few thousand and now has a user population bigger than a large chunk of Europe. Geo-location services like Foursquare, Gowalla and Google Latitude are becoming popular and morphing so quickly that it is impossible to develop a clear standard to follow.
And that is OK, because that is the way things are, not the way evaluators want them to be.
DE seeks to bring some rigour, method and understanding to these problems by creating opportunities to learn from this constant change and use the science of systems to help make sense of what has happened, what is going on now, and to anticipate possible futures for a program. While it is impossible to fully predict what will happen in a complex system due to the myriad interacting variables, we can develop an understanding of a program in a manner that accounts for this complexity and creates useful means of understanding opportunities. This only really works if you embrace complexity rather than try and pretend that things are simple.
For example, evaluation in a complex system considers the program ecology as interactive, relationship-based (and often networked) and dynamic. Many of the traditional evaluation methods seek to understand programs as if they were static. That is, that the lessons of the past can predict the future. What isn’t mentioned, is that we evaluators can ‘game the system’ by developing strategies that can generate data that can fit well into a model, but if the questions are not suited to a dynamic context, the least important parts of the program will be highlighted and thus, the true impact of a program might be missed in the service of developing an acceptable evaluation. It is, what Russell Ackoff called: doing the wrong things righter.
DE also takes evaluation one step further and fits it with Patton’s Utlization-focused evaluation approach., which frames evaluation in a manner that focuses on actionable results. This approach to evaluation integrates the process of problem framing,data collection, analysis, interpretation and use together akin to the concept of knowledge integration. Knowledge integration is the process by which knowledge is generated and applied together, rather than independently, and reflects a systems-oriented approach for knowledge-to-action activities in health and other sciences, with an emphasis on communication.
So hopefully these conversations will continue and that DE will no longer be something that peaks on certain weeks, but rather infuses my colleagues conversations about evaluation and knowledge translation on a regular basis.
Design Thinking or Design Thinking + Action?
Posted: April 8, 2010 Filed under: design thinking, Education & Learning, evaluation, innovation, research, systems thinking | Tags: design, design thinking, education, evaluation, innovation, research methods, university Leave a comment »
There is a fine line between being genuinely creative, innovative and forward thinking and just being trendy.
The issue is not a trivial one because good ideas can get buried when they become trendy, not because they are no longer any good, but because the original meaning behind the term and its very integrity get warped by the influx of products that poorly adhere to the spirit, meaning and intent of the original concepts. This is no more evident than in the troika of concepts that fit at the centre of this blog: systems thinking, design thinking and knowledge translation. (eHealth seems to have lost some its lustre).
This issue was brought to light in a recent blog post by Tim Brown, CEO of the design and innovation firm IDEO. In the post, Brown responds to another post on the design blog Core77 by Kevin McCullagh that spoke to the need to re-think the concept of design thinking and whether it’s popularity has outstripped its usefulness. It is this popularity which is killing the true discipline of design by unleashing a wave of half-baked applications of design thinking on the world and passing it off as good practice.
There’s something odd going on when business and political leaders flatter design with potentially holding the key to such big and pressing problems, and the design community looks the other way.
McCullagh goes on to add that the term design thinking is growing out of favour with designers themselves:
Today, as business and governments start to take design thinking seriously, many designers and design experts are distancing themselves from the term.While I have often been dubbed a design thinker, and I’ve certainly dedicated my career to winning a more strategic role for design. But I was uncomfortable with the concept of design thinking from the outset. I was not the only member of the design community to have misgivings. The term was poorly defined, its proponents often implied that designers were merely unthinking doers, and it allowed smart talkers with little design talent to claim to represent the industry. Others worried about ‘overstretch’—the gap between design thinkers’ claims, and their knowledge, capabilities and ability to deliver on those promises.
This last point is worth noting and it speaks to the problem of ‘trendiness’. As the concept of design thinking has become commonplace, the rigor in which it was initially applied and the methods used to develop it seem to have been cast aside, or at least politely ignored, in favour of something more trendy so that everyone and anyone can be a design thinker. And whether this is a good thing or not is up for debate.
Tim Brown agrees, but only partially, adding:
I support much of what (McCullagh) has to say. Design thinking has to show impact if it is to be taken seriously. Designing is as much about doing as it is about thinking. Designers have much to learn from others who are more rigorous and analytical in their methodologies.
What I struggle with is the assertion that the economic downturn has taken the wind out of the sails of design thinking. My observation is just the opposite. I see organizations, corporate or otherwise, asking broader, more strategic, more interesting questions of designers than ever before. Whether as designers we are equipped to answer these questions may be another matter.
And here in lies the rub. Design thinking as a method of thinking has taken off, while design thinking methodologies (or rather, their study and evaluation) has languished. Yet, for design thinking to be effective in producing real change (as opposed to just new ways of thinking) its methods need to be either improved, or implemented better and evaluated. In short: design thinking must also include action.
I would surmise that it is up to designers, but also academic researchers to take on this challenge and create opportunities to develop design thinking as a disciplinary focus within applied research faculties. Places like the University of Toronto’s Rotman School of Business and the Ontario College of Art and Design’s Strategic Innovation Lab are places to start, but so should schools of public health, social work and education. Only when the methods improve and the research behind it will design thinking escape the “trendy” label and endure as a field of sustained innovation.
