All posts by Danny Fain

About Danny Fain

After a decade teaching high school science & engineering with a learning-disabled population (and in four other, very different school settings before that), I am tunneling into digital game development and evangelism.

Game Design as Hypothesis – Research Studies on GBL

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.


Meditations on Learning Theories: from Solitary to Collective

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