“Now Ziggy played guitar …”

The first rock/pop album I ever owned was The Rise and Fall of Ziggy Stardust and the Spiders from Mars. It was a birthday present from my friend Joanna, who was a huge Bowie fan at the time; I had barely heard of him. Just entering my teens, I was starting to tentatively explore rock music; boy, did that album ever propel me, head over heels, into an exciting new world. That 12” slab of vinyl (in 1979, before the commercial debut of CDs) spun for thousands of revolutions on my turntable, a soundtrack for my adolescent musings and flights of fancy. It still haunts my dusty collection, alongside other Bowie albums, mostly on CD. Nowadays I rarely listen to them, and seldom hear “Ziggy Stardust” on the radio, but I can still mouth all of its lyrics and half of the other songs on that LP; an earworm lodged solidly in the formative recesses of my brain.

OK, maybe I’ve got some “Bowie fan cred”; but so do zillions of other mournful bloggers who’ve been posting their heartfelt paeans in tribute to our fallen idol in the past couple of days. I’ll admit, a lot of their stories are more profound than my mine, or more compelling, or more poetic …

But my intention is not merely to sentimentally bury Bowie, nor just to praise him (with apologies to Shakespeare). This is a blog about games and play; as you’ve probably guessed, I’m aiming the spotlight on playfulness, and connecting the dots to games.

If you don’t already know the “Four Freedoms of Play” theory, check out a few minutes of the video below (starring a pioneer of the game-based learning world, Scot Osterweil). As I contemplated his accomplishments, it struck me that Bowie was a paragon of playfulness, because he embodied some of those Freedoms so well.

You want the “freedom to try on identities”? By the time I discovered David Bowie, he had already undergone a name change (ala frontiersman Jim Bowie and the eponymous knife) and risen to fame first as the glam-alien Ziggy Stardust, then as the Thin White Duke. His prominent androgyny in the 70’s was copied by a flock of New Wave artists, and emulated by hordes of “cool” kids I grew up with. Consider it as big-time (and high-stakes) LARP’ing, paving the way for modern media chameleons.

Above all else, Bowie exemplified the “freedom to experiment”: as this infographic shows, his music spanned dozens of genres, with Top-50 hits ranging across psychedelic folk, hard rock, glam, soul/funk, protopunk, minimalist/ambient, new wave, dance-pop, and industrial/electronica. He continued to experiment with genres (and identities) throughout his career, up to his final album that was released just days before his death. Along the way, he collaborated with numerous other artists as diverse as Brian Eno, Iggy Pop, Queen, Stevie Ray Vaughan, Trent Reznor, and Arcade Fire. That made it hard to answer, in just a few words, the question “What’s Bowie’s music like?” (luckily, it became so well-known that I was rarely asked that question)

How about “freedom to vary effort”? Bowie was a consummate multi-instrumentalist; best known for his trademark vocals and guitar work, but on many of his albums he also played keyboards, harmonica, sax, and a passel of other instruments. His numerous stage and film roles over 3 decades brought him critical and popular acclaim. You may have seen him as the Goblin King in the movie Labyrinth, or as Nikola Tesla in The Prestige; but did you know that he played the lead role in The Elephant Man on Broadway (without makeup) ?

Last but not least of the Four, Bowie’s early career illustrated the “freedom to fail (and recover)”: before he hit it big with the single “Space Oddity” in 1969, he had played in five different bands; their six singles, and his solo debut album, all failed to get on the charts (during that period Bowie even performed as a mime opening act for the band T.Rex!). Hard to believe that such a talented musician could have confronted so much failure, yet gone on to greatness. It’s all in the Wikipedia entry and his many biographies.

At this sad moment, it’s a little comforting to imagine that the next time I’m caught in the flow of a good game, I’ll be channeling the spirit of David Bowie.

May he Rest in Play.

I recall learning, in my pre-service teacher-training courses at Harvard, MIT, and Wellesley College, several popular theories of effective pedagogy: constructivism, constructionism, multiple-intelligences, situated learning, authentic assessment, UDL. Though some of these theories perhaps didn’t meet all the stringent criteria propounded by Logical Positivists* (clearly-defined outcomes, construct specificity, propositions that pass absurdity tests, etc), they all appeared to be supported by some research evidence from neuroscience or sociology. Furthermore, most of these theories were not novel, having been promoted and studied for a number of years. So I naturally expected to see at least some of them in prevalent use in schools.

Imagine my disappointment, when I began teaching in large, well-financed public high schools, at finding scant usage of those theories. Instead, I found the same Skinnerian behaviorism (extrinsic rewards and punishments), tabula-rasa pedagogy (pouring knowledge into students’ heads), and factory-model organization (one-size-fits-all, sequential, lockstep, compartmentalized) that I remembered from my own days as a student, decades earlier. Furthermore, I observed that my and other teachers’ efforts to introduce new practices based on progressive theories of learning met with subtle but powerful structural resistance; it was an uphill struggle, leading many idealistic new teachers to disillusionment and burnout. I was bewildered: how could these supposedly good school systems be so out of sync with the educational theory advanced by top-notch universities?

It took me several years to discover and acknowledge the answer: the difference lies in the desired outcomes. As described in recent years by various scholars (Gatto; Collins & Halverson), our traditional system of compulsory K-12 schooling is very conservative in maintaining the goals of its industrial-era roots: conditioning kids to become compliant consumers and factory workers, ensuring conformity, and sorting by easily-quantified abilities (mostly low on Bloom’s Taxonomy). In spite of the lip service that principals and superintendents often give to progressive ideals (deep learning, critical thinking, differentiated instruction, etc), the theories fundamentally at work in schools are those that serve the now-unspoken goals of the industrial era. No wonder that innovative school practices and technologies that would serve progressive goals tend to be hobbled, co-opted, or fail outright.

I think this explains the fate of many school tech fads in recent years: smartboards,  one-to-one laptop programs, lecture videos. They were sold as ways to advance the noble ideals in the cause for “reform”; but in many cases, school leaders have hastily implemented these technologies without first carefully examining the underlying pedagogical theories and structures. In such cases, the new technologies have generally failed to produce the envisioned transformations.

How can game-based learning avoid a similar fate in traditional K-12 schools?

* e.g. Briggs (2006), “On theory-driven design and deployment of collaboration systems”

When does it make sense to design a learning game to answer a research question, and then test it with rigorous scientific methodology? Let’s consider why that approach worked well for Re-Mission, but not so well for other kinds of serious games (especially those intended for use in a school setting).

Tate¹ describes a process, “Rational Game Design,” that worked well to address a research question regarding cancer treatment. This process emphasized iterative product optimization through formative research, as in biomedical targeted-drug development:

“Empirical testing is the best way to resolve conflict: When in doubt, collect data — the right answer is the one that best changes the target behavior in teenaged cancer patients.” (page 31)

“On many occasions, conflicting visions emerged in efforts to synthesize fun game play, cancer biology, and behavioral science. In those cases, player-focused data collection provided the basic recipe for choosing the right answer. Empirical demonstrations that ‘that’s what kids want, and it works’ played a major role in helping health professionals embrace a video game based on shooting, stool softener, and a sassy back-talking protagonist.” (page 33)

That description, along with the research analysis in the accompanying Kato² paper, makes it clear that the success of such a design process is predicated on measurement: quantitative and qualitative, baseline and outcome. The feasibility of such measurement is determined by the theoretical framework, the intended primary outcome, and the constraints of the research setting. The case of Re-Mission was particularly well-suited for the measurement requirements of this design process: it employs a behaviorist approach; the intended primary outcome is easily measured (performance consistency of self-treatment protocols); the setting allowed for self-paced, occasional gameplay (1 hour or less each week) over a few months with periodic measurement. Furthermore, the informal, low-risk context of the gameplay made it easy to conduct a randomized controlled trial: the study participants had the freedom to spend one hour a week playing (or choosing not to play) a computer game that was entertaining, and possibly therapeutic (in the intervention group).

Contrast that case with studies of other sorts of serious games, especially academic learning games focusing on higher-cognitive or constructivist objectives: the intended outcomes may not be uniform or easily measurable; the setting is often intensive, requiring prolonged and coordinated gameplay over a shorter timespan (perhaps only a few weeks), which is not conducive to measurement of gradually-emergent or long-term effects; formal accountability requirements (e.g. test scores) hamper the ability to randomly place participants, lead to confounding factors, and may even stymie the definition of a “control” group. The difficulties and delays in measurement are also likely to stretch out the product iteration cycle. Little wonder that, in Video Games and Learning (2011), Squire rails against the “gold standard” (randomized controlled trials) for game-based learning studies in schools, considering the theoretical framework and sorts of outcomes that he advocates.

1          Tate, Haritatos, and Cole (2009). Hopelab Approach to Re-Mission. International Journal of Learning and Media, 1, 29 – 35.

2          Kato, Cole, Bradlyn, and Pollock (2008). A Video Game Improves Behavioral Outcomes in Adolescents and Young Adults With Cancer: A Randomized Trial. Pediatrics, 122, e305 – e317.

Kolb’s Discovery Learning theory* organizes phenomena along two orthogonal axes: the Processing continuum (active experimentation ßà reflective observation), and the Perception continuum (concrete ßà abstract). The perception continuum seems compatible with constructivism, which (as I understand it) holds that concrete experiences are organized and generalized to form abstract concepts, which then can be applied to interpret and act in new concrete experiences. However, the processing continuum as framed in the lecture seems inconsistent with studies I’ve read about game-based learning. While play alternating with reflection is reported to be effective in promoting deep learning, the reflection must be active: merely watching is not enough; the player must articulate and express questions or conclusions drawn from observation.

Following an explanation of Socio-cultural Theory, Professor Carrie Heeter asked students (in the MSU course “Theories of Games and Interaction for Design”) to consider how the social construction of learning can be fostered in game design and in structures surrounding gameplay. In thinking about the real world, it seems to me that not all knowledge requires social construction: for instance, it’s possible for someone to discover natural laws and properties, and even to figure out how to apply them in devising technology, without engaging in any social communication, as plausibly fictionalized in Robinson Crusoe and the movie Cast Away. This is also the case in many excellent single-player puzzle games (e.g. Waker, Acorn Story) that are virtually wordless. However, the use of language and social interaction enable quicker, more complex, and more effective learning, even through asynchronous communication media such as written text and video. Furthermore, human beings are fundamentally social creatures, and our neurological systems are wired to reward social interaction; the emotional payoff motivates us to persevere and helps us remember. I’ve observed first-hand the benefits of in-person and online game-based interactions involving my family members, both in-game (multiplayer role-playing, in-game chat) and around-game (my wife coaching my son from the side, or watching video walk-throughs together). I think it’s important for game designers to consider, for any sort of game, what forms of social interaction would be afforded.

Finally, collective intelligence (or “crowdsourcing”) can be a powerful dynamic: whether used in games by design for problem-solving, as in scientific research (FoldIt) or alternate-reality games (I Love Bees, Vanished); or as an emergent behavior of real-world social systems (bird flocking, the stock market, and the 2011 “Twitter revolution” in Egypt). I think it is important for people to understand this dynamic and how it may play a role in their lives; so that instead of being manipulated by collective processes, they can be empowered to choose whether and how to participate.

 * Kolb, D. A. (1984) Experiential Learning, Englewood Cliffs, NJ.: Prentice Hall