What can Canvas design strategies learn from game design? How can we use what Canvas allows (Mechanics) to structure what students can do (Dynamics) in ways that encourage them to learn effectively and contribute to a course culture (Aesthetics) that values inquiry and exploration. This post lays out the framework.
MDA for Course Design
Hunicke, LeBlanc & Zubek's (2004) MDA framework for game design can be adapted here. They propose that game designers can approach their craft through the lens of MDA (Mechanics, Dynamics, and Aesthetics), where the Mechanics (what is possible — rules and resources) leads to Dynamics (what occurs — activity), which lead to players' Aesthetic experience (components of engagement). I apply the MDA lens to course design, where the instructor plays the role of game master — both a designer and a player, adjusting the Mechanics both before and during the actual game in order to affect the Dynamics in each class such that the desired Aesthetics are reached.
Mechanics include the rules and resources that allow Dynamics to happen. In game design, the mechanics include everything that can affect the play of the game: rules, pieces, cards, the game board or playing field, etc. In course design, mechanics include things like: policies and rules, classroom or class space (online or face-to-face or both), assignments, lectures, videos, etc.
Dynamics are what actually happens when players interact with the Mechanics. In games, the dynamics are what the players do. In baseball, they run and throw and hit and catch and steal and bunt and foul etc.; in Poker they shuffle and deal and fan cards and sort and draw and bluff, etc. In courses, Dynamics are what the instructor and students do. For example, students listen and watch and read and raise hands and talk and move seats and flirt and take tests and cheat and text and increase the typeface to stretch their papers, etc.; whereas instructors take attendance and lecture and assign homework and quiz and test and grade and hold office hours, etc. In addition to the mundane Dynamics in a course listed above, perhaps the most sought after cognitive Dynamics are captured in Bloom's Cognitive domain (1956), or Anderson et al's revision of them (2001)
They are others in Krathwohl & Bloom's (1964) Affective domain (these are often ignored in course design — and instructional technology, in general)
- Receive: be open to accepting new information/ideas, etc. (e.g. I am aware of a rule)
- Respond: comply; change behavior accordingly (e.g. I will follow this rule — perhaps because I don't want to suffer negative consequences)
- Value: assign intrinsic worth to new information (e.g. This rule makes sense to me)
- Organize: relate new information within existing systems (e.g. This rule helps other beneficial things happen)
- Characterize: relate new information with one's identity (e.g. This rule is part of what makes me who I am)
Dynamics spring from models — based in theory and based on trial and error experience. Models help designers predict Dynamics, but as with most models they're not as perfect or accurate (or chaotically messy) as real life. Dynamics provide Feedback to designers, who can use it to iterate and adjust mechanics, which in turn can affect Dynamics. Game designers typically do this a lot in playtests before they publish their games. As a sort of Game Master, instructors can adjust mechanics (to some degree) on the fly by modifying assignments, spending more or less time on a topic as needed, reviewing material, grading more or less rigorously, etc. Changing the Mechanics changes the Dynamics, which affects the Aesthetics. Exercising caution must be advised here — changing the course to be responsive to student needs is often a good thing, but changing the Mechanics of a course too much often results in students feeling ungrounded, and may result in backlash against an "unorganized" instructor.
Aesthetics are the tone or the experience. Hunicke et al shy away from describing Aesthetics as "what makes a game 'fun'?" (2004, p2) and instead suggest a taxonomy of Aesthetic components that includes: 1. Sensation (Game as sense-pleasure), 2. Fantasy (Game as make-believe), 3. Narrative (Game as drama), 4. Challenge (Game as obstacle course), 5. Fellowship (Game as social framework), 6. Discovery (Game as uncharted territory), 7. Expression (Game as self-discovery), and 8. Submission (Game as pastime). The balance of each of these (and there are probably others) determines the aesthetics of the experience. I think of it as a sort of graphic equalizer. One adjusts the frequencies to try to get the sound one desires. In course design, we can even match up the eight aesthetic components that Hunicke et al list with educational ones:
- Sensation (Game as sense-pleasure) = Embodiment
- Fantasy (Game as make-believe) = Epistemic Frames
- Narrative (Game as drama) = Course Schedule, pacing (help me out on this one)
- Challenge (Game as obstacle course) = Problems
- Fellowship (Game as social framework) = Sociocultural Learning
- Discovery (Game as uncharted territory) = Research
- Expression (Game as self-discovery) = Personal Strengths Finding
- Submission (Game as pastime) = Time on Task
Unfortunately, it's not as easy to adjust the Aesthetics of the experience, whether in game design or course design, as simply moving a slider. For example, if one wants a game high in Sensation and Fellowship one must adjust the Mechanics to be more like Twister than Chess. In course design, a collaborative field research assignment might be high in the Embodiment and Sociocultural learning components, whereas reflective journaling might emphasize Personal Strengths Finding. Assigning plenty of worksheets might increase time-on-task; but not in a good way.
What This All Means...
So, can we use this framework for designing courses? Yes. With the following caveat. Courses are not publish-and-leave games, or books, or movies, that can be designed and left for consumption by students. Instructors and students continually interact with and affect course form long after the initial design. Recognizing that instructors are sort of Game Masters and students are active participants (and shapers) of the gameplay of courses, it's important that we design them as evolvable and emergent systems that take into account human psyche and social interactions — much more complex mechanics than dice and cards. This is where a deeper understanding of experiential and sociocultural learning (discussed throughout the rest of my writing) begin to contribute. At this point, however, it starts to get messy. The educational Aesthetic components can be achieved through a mix and match of educational Dynamics, which in turn are affected by course Mechanics. For example, a Fellowship/Sociocultural learning is hampered when there's no forum for student-to-student interaction. Likewise, Discovery/Research may be more difficult when computer browsers are locked down. Without a compelling story, learners may not enter into the Epistemic Fantasy of deeply solving an authentic problem from the perspective of a person in the field or discipline being studied.
A good next step might be to begin to map out a number of these relationships, either through stories and examples or through educational research. Both have value in this conversation.
Anderson, L. W., Krathwohl, D. R., Airasian, P. W., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., ... & Wittrock, M. C. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives, abridged edition. White Plains, NY: Longman.
Bloom, B. S., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. Bloom, B. S. (1969).
Bloom, B. S. (1969). Taxonomy of Educational Objectives: The Classification of Educational Goals; Handbook. Affective Domain. McKay. Bloom, B. S. (1974).
Bloom, B. S. (1974). Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook 1-2. Longmans: McKay. Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A formal approach to game design and game research. In
Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI.
Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1964). Taxonomy of educational objectives, handbook ii: affective domain. New York: David McKay Company.Inc. ISBN 0-679-30210-7, 0-582-32385-1.
Krathwohl, D. R. (2002). A revision of Bloom's taxonomy: An overview. Theory into practice, 41(4), 212-218.