How and why things work
Theory plays an important role in developing expertise in a domain. Novices read about concepts and direct their efforts in meaningful ways. Intermediates use frameworks and collected writings to guide their inquires, study phenomena, and make sense in complex spaces. Advanceds critique and ask deeper questions underlying theory—how is a theory supported and where can it be improved? Masters formalize their experiences and knowledge into theory and complete the cycle of learning.
My experience in learning theory has been broad. I started learning about psychology and the human body during community college. After transferring to university, I proceeded deeper into that domain with studies on human anatomy, physiology, and cognitive development. My courses helped me to understand how the body develops from adolescence and how cognition functions.
I ended my study of the human body my junior year with a focus on neural networks. In my junior year, I shifted my studies to the mathematical domain of psychometrics, which deals with the statistical relationships of unobservable human qualities—intelligence, ability levels, depression.
My coursework in measuring human qualities carried me into user experience, interaction design, and understanding human factors. I have an ever growing desire to make experiences that improve human qualities. This passion for making subverted my interest in becoming a measurement expert.
Now in a PhD program, I have been taking human design and interaction coursework—HCI, UXUI, Human engineering. In my studies, I have noticed that multiple domains inform human design but do not commingle.
The base domain of design is constructed from knowledge in HCI, UXUI and human-centric study. Academics study and develop theory about humans playing games, piloting aircraft, operating devices and so on.
Theories in this domain are about human motivation, decision-making, and incorporate human elements such as psychology, physiology, and cognition. This domain has a long standing in human design work and will continue to produce experts in HCI.
Social and cultural domain knowledge has a lower awareness in human design—but contributes powerful understandings. Theory here explains how groups of humans engage as communities, participate in social conventions, and create meaningful experiences. Studies investigate who participates in social resistance and what participants learn from their interactions in that group.
Learning theory draws heavily from this domain, where figureheads such as Lev Vygotsky explain social development and scaffolding knowledge. There are fringe cases where this domain addresses design work—multidisciplinary scholars have studied distributed cognition in piloting aircraft.
Such studies illustrate how complex social systems account for the abilities and design patterns of successful piloting. The number of multidisciplinary scholars is low, and crossover of theory between HCI and the social domain is limited.
Purpose of my work
My PhD specialization has involved combinations of theory from social and HCI domains. Situated from this multidisciplinary perspective, I work to understand play and games. Game mechanics are incredibly interesting cultural artifacts. Designers plan an experience and organize game mechanics with the intent to mediate player action.
Players interpret a game system—consciously and subconsciously—and act and behave in relationship to the system in congruence to their identity. This description of play and games naturally implicates both social and HCI theory.
Accordingly, games scholars are hybridizing social and HCI theories to explain and understand the nature of play and games. The writings below capture my experience with theory.
What's in my brain
Video game mechanics are my primary academic focus. The video game study sector is a few decades old and has not formalized a standard language or method of inquiry. The language of game design has largely existed within a commercial context, and it is recently that scholarly channels and mediums are emerging to discuss, learn, and theorize about it.
Even within the commercial sector, game design knowledge is diverse and remains on the edge of a standardized practice. Initiatives in both sectors have seen a blend of traditional academic perspectives and commercial design practices.
The blending is evidenced by an increasing number of user research, data analyst, and data insight positions at game companies and by scholars who develop complete games as research objects.
Outline of projects
I use a number of different perspectives to understand play and video games. While there is no wrong way to develop theory and understand this field, each path will afford different knowledge to scholars and designers.
[Click titles below to view article PDFs]
Seen below as: Video game theory
This work dives into the term game mechanic. Conducting research requires precision, no? I start with a basic introduction of what a game mechanic is and build up the levels of complexity.
After establishing some terminology and understandings, I bridge into game studies and illustrate how scholars study game mechanics. I end the piece proposing future directions to improve research practices.
Seen below as: Sociocultural theory
A literature review covering hallmark learning theories from the sociocultural domain. Brief information and examples are provided on each and then they are tied together in the end.
This work is a synthesis of sociocultural theory and intended to provided a new perspective on the domain. The experience of this writing is less about using frameworks to guide my own processes, and more on engaging with the theory at a novice level.
Video Game Theory
Below are excerpts from my paper with added commentary. Each addresses a main theme and presents a partial view of the whole discussion. Check out the full text for an in-depth reading.
What is a game mechanic?
CommentaryDefinitions direct how we think about and organize information. They give us power over a space to create relationships and explain the world we see world. This is a light journey into some of the work that has been done to reach a definition for game mechanic. Additional sections of the paper support why I chose to use Sicart’s definition.
PaperResearchers from multiple disciplines have been working to develop an ontology for game studies. Sicart (2008) exposed contrasting ontological perspectives in their search for the definition of game mechanic. The study referenced work in 1971 by Avedon, where game mechanics were described as a formal procedure of action.
Later in 2005, game designer Richard Rouse formalized game mechanics as a component of the game design document—they are the what and how of a compelling player-driven experience. In other communities, game mechanics are single instances within a rule system where interactions occur, or are elements that motivate exploration and learning via systematic feedback.
Across decades and fields of study, the definition of game mechanic has been controversial and remained elusive to consensus. Sicart’s purpose for resolving game mechanic was to facilitate the analysis of games—a primary concern of this paper. Drawing on historical voices in game studies, Sicart synthesized a precise and inclusive definition with the goal of driving inquiry:
“Game mechanics are methods invoked by agents, designed for interaction with the game state.” (ibid)
The boundaries of a game experience
CommentaryGame design and scholarly study has been notoriously confined to the limited scope of the gameworld. We design and study in consideration to the object of focus—the game—but miss the outside complex relationships. A great read about external actions affecting players and gameplay is Abiding Chance by Natasha Schull. What Schull addresses that I don’t: player’s life behaviors are affected by their game experiences. The section below illustrates how games are not isolated objects, and identifies topics for design and research.
PaperExternal actions of players should not be dismissed as a separate activity from game mechanics. An end-game raid mechanic from Destiny 2 (Bungie, 2017) mediates upwards of 2,000,000 players to engage with each other in non-game mediums before subsequently returning to the gameworld (KackisHD, 2017). External actions and behaviors have been studied under the term “metagame.”
Game communities are diverse, and game mechanics uniquely influence the practice of metagaming. In World of Warcraft (Blizzard Entertainment, 2004), theorycrafting is an external activity that involves the statistical breakdown of strategies, gear, level dynamics, talent charts, and every other component tied to the player’s existence (Paul, 2011).
A theorycrafter may be working to increase their performance—indicated by a damage per second (DPS) metric—using excel spreadsheets, testing scenarios in the gameworld or on paper, and communicating extensively with other players. Theorycrafting occurs in the gameworld, in web forums, on YouTube, and many other social channels.
Metagame activities involve a two-way interaction. They influence the gameplay, then the affected gameplay influences the metagame. World of Warcraft theorycrafters identify correct playstyles, establish gear requirements for challenges, and develop training regimes for novice players (ibid). Metagaming is not separable from game mechanics, but emerges in relation to them and influences future engagement with them.
How do we build knowledge?
CommentaryA gameworld affords player action. What do players do? How do players make sense of their activity? And what kind of effects are associated with their behavior? Understanding the nuance of mechanics is critical to develop theory in research and guide best practices in design.
PaperIn a history-based gaming club, Civilization IV (Firaxis, 2005) players demonstrated learning in systems thinking through their discourse, communication, and actions with the gameworld. Player activity centralized on the game’s missions, challenges, and mechanics—where systems thinking knowledge affected gameworld success.
For example, players iteratively constructed cognitive models to solve health issues in their gameworld cities. After construction, players critiqued and discussed their models with the help of representations in the game—population size, local resources, and trade routes. The players formed theories about the game system and tested to see if their cognitive models aligned with the true nature of the gameworld—a foundational skill in systems thinking.
Players even relied on experiences and artifacts beyond the gameworld, demonstrating continuity of thought extending from the gameworld into the physical world. The continuity is characterized by players using their school textbooks and referring to real geographic and historical contexts when building models and solving gameworld problems. (Devane et al., 2010). The Civilization IV game system afforded experiences to understand complex knowledge.
How do we study game mechanics?
CommentaryDesigners and researchers use frameworks, guidelines, and past examples to advance their fields and organize work. From time to time, we need to check and see what is being used in the community, what methods are effective, and how to lead innovation. Below is a new game design method coming from games researchers. In my paper, I question whether it is useful for game analysis or is too focused on game production.
PaperA standardized practice of academic inquiry is missing across gamification, where the focus has been on building frameworks to produce successful implementations of design—as opposed to analyzing them. Deterding’s (2015) Skill Atoms framework is an effort to develop a common design language for producing game-based environments.
An evaluation component is built into the framework, but the scope maintains an orientation towards designing gameworlds versus substantiating them. Evaluation uses Skill Atoms to tease out what game elements are present in a system, and then develop prototypes and test builds to improve the current game system.
A possible solution for a common analysis may be to adapt this framework—Skill Atoms—to guide academic inquiry. A dual-purpose framework that connects methodological inquiry to design production might solve a common problem in academia—translating theory into practice. Skill Atoms is a schema framework for contextualizing game design elements. Game elements are considered along seven dimensions:
- Goals: System states the user attempts to achieve. Goals are typically explicitly suggested by the system but must be actively pursued by the user to be goals.
- Actions: What the user can do to approach her goals.
- Objects: Entities the user acts upon; their configuration embodies the system state.
- Rules: Specifications what actions the user can take and how they affect the system state. These may be algorithms, humanly enacted rules, physical laws, or a combination thereof.
- Feedback: Sensory information that informs the user of system state changes resulting from her actions or autonomous system processes; entails immediate feedback on each action and progress feedback on the user’s accumulated progress.
- Challenge: The perceived challenge of achieving the user’s current goal, posed by the current system state relative to the user’s perceived current skill.
- Motivation: The psychological needs energizing and directing the user to seek out and (continue to) engage with the system—typically competence.” (ibid)
Below are excerpts from my paper with added commentary. Each addresses a main theme and presents a partial view of the whole discussion. Check out the full text for an in-depth reading.
CommentaryThe section brings attention to the idea that we do not copy/paste information into our heads. We rely on mechanics outside our cognition to develop understandings and build knowledge.
PaperLev Vygotsky, a developmental psychologist, established how historical, cultural, and societal elements mediate learning and cognition. Vygotskian theory is most known for describing the importance and interdependence between the social and individual.
The social captures many aspects of development: interactions with experienced mentors and peers, using tools to manipulate and understand the environment, relying on patterns of social relations and institutions, and the many dialects of language (i.e., dialogue; Rogoff 2003).
From Vygotskian logic, the social was the first stage in the process of development. The second stage was that of the individual: the internalization of the social experience to some higher functioning structure (Valsiner, 1997).
The way we know
CommentaryWe develop specific ways of knowing and exercising what we know. If my mother was a famous writer, she would have passed along ways of researching books and genres. She would have shared and influenced me with her style of writing. The section here examines consequences of sociocultural learning and differences in abilities. Differences not in the pure power of cognition, but differences in how we produce what we know.
PaperSerpell (1979) provides a powerful example of the sociocultural perspective by demonstrating the individual differences and fidelity of pattern production between Zambian and English children. In the study, children had naturally learned particular ways to accomplish certain tasks as part of their upbringing and development.
In this case, pattern production with either paper and pencil (English medium) or strips of wire (Zambian medium). The premise of the work is that a child’s knowledge and ability is dependent on their social relationships and cultural interactions.
Support for this claim was demonstrated when children were requested to produce a pattern using an opposing medium they were not familiar with. Results demonstrated that using the opposing medium hindered the performance of a child’s ability to produce a pattern (Zambian or English). When both Zambian and English children used a similar and unfamiliar method of pattern production (e.g., modeling with clay), the performance between the groups was equivalent.
This work illustrates how our knowledge and abilities are not an isolated internal property. In other words, knowledge and performance on tasks is not solely the property of an individual, other elements need to be taken into account in order to explain the presence and type of knowledge demonstrated. This has a direct impact on educational pedagogy, the networks of social and individual elements surrounding students play an integral role in the process of learning.
CommentarySystems are the rule, not the exception. Humans are complex, and our worlds should be modelled with the respectful amount of depth and connectivity. Learning for one person involves understanding the dynamic life experiences that one person had (Zambian vs English pattern production). A classroom is a collection of such individuals and forms a constellation of interactions and influences. Care must be taken to unpack those relationships and understand them.
PaperBeyond the value achieved by seeing the student as a networked learner, seeing the classroom from a networked perspective is the next logical transition. Classrooms, are not sterile and unidimensional; they are the manifestation of multiple and dynamic agents. With the concept of a networked classroom in mind, Berland (2011) demonstrated how students, teachers and curriculum influenced the practice and learning of scientific argumentation.
In this work, two separate classes were given the same computer-based simulation curriculum. While students and teachers from each class worked to satisfy their learning objectives, Berland observed and compared the course cultures of each classroom.
This study helps see the architecture of the networked relationships that exist in a classroom. While the curriculum (medium) itself led to changes in the how often students justified scientific claims, Berland argued that the social relationships established between teacher and student best accounted for the increased student-to-student interactions.
The first class established authority in students as technology experts and physically removed the teacher from control (i.e., sat in the back of class). The students in this class had a strong grasp of the technology and took control from the less tech savvy instructor.
The second class used explicit student roles and provided scaffolding for behavior. Roles helped reduce the need for teacher intervention and a list of appropriate questions—to ask other students during argumentation—scaffolded behavior.
The networked student attends a networked class. Oversimplified models—teachers transmit material to awaiting students—fail to account for the rich relationships that mediate exactly what and how students learn.
What are the boundaries of knowledge?
CommentaryReplace the concept of a human with a bundle of neurons. This collection of cells contains information and can produce and redefine knowledge through relationships with other neuron groups. Is that neuron independent of all the others? Are humans independent from all the others? It does not make sense to say that parts of the brain are internal or external from each other. We say brain parts are in different locations—they form one brain. Should we see humans from this shared knowledge perspective?
PaperThe division in knowledge between what is internal and what is external is most significant when considering a student as an isolated and self-contained individual. However, if the student and their surrounding elements are made the focus, then internal and external form into a networked relationship.
The previous work has established that individuals can be seen through this more complex view—not as separate students each pursuing the capture of information—but as participants in the definition and implementation of a local learning network (i.e., a networked student). Within these networks, students can be visualized as a node, and this node is where artifacts mediate learning on a personal level with the student.
What does learning look like?
CommentaryThe structures, behaviors, and functions of systems are often obscure and hidden. We can reveal information about systems with deep analysis. A growing trend is that you do not work with single systems, but constellations of different systems which can have systems within them. The text below comes from a section in my paper that contrasts our simplified model of education to a view of complex systems.
PaperThis Community of Practice ideology is exhibited in Berland’s (2011) work, where social structures guided how student-to-student interactions took place. In the school courses, the same curriculum was interpreted and used in markedly different contexts. But it should be noted that it was together—students and teachers—that determined how scientific argumentation would be practiced.
We can also reflect on the visually rich space provided by Hutchins’ narrative of the sociotechnical airline cockpit. We could focus on the community of pilots that fly and teach co-pilots, or use an extended frame to consider how pilots interact with engineers to improve flight instruments and procedures. Lastly, Pacheco’s work advocates that practice is not confined by the classroom walls, but extends tendrils into all manner of students’ personal lives.
Human learning is ostensibly rich in connections and interactions—what else but a network? If we conclude that information stored in explicit ways is only a small part of knowing, and that knowing involves active participation in social communities, then the traditional format of learning does not look so productive. (Wenger, 1998)
Giving what you see a label
CommentaryThis is one of my takeaways from interacting with sociocultural theory. I identified patterns as I engaged with the theory and created meaningful explanations. In this case, I created a label for what I was thinking about. Through a label, I organized my thoughts and critiqued what value they added to the theory.
PaperStructure norms represent a system of elements that influence how an agent in the system will interact with: other agents, elements, and themselves. For example, the stricter classroom from Berland’s (2011) work established norms that influenced how students should respond when practicing scientific dialogue: students didn’t question the teacher, the students energetically debated, and power shifted from teacher to students with physical positioning (i.e., the teacher sat in the back of class).
Berland attributes this shift in norms to the social and class culture. While Berland did not isolate or discuss structure norm systems at length, the presence of structure norms significantly influenced the learning outcomes, as well as how those outcomes were achieved.
Artifact influence is similar in focus to structure norms, but more emphasis is placed on the paradigmatic shifts it can have on an entire system. Changing deep rooted norms within a community, organization, or person is typically met with heavy resistance. Artifacts can instantaneously affect established norms and influence the creation of new ones. The qualitative data of Berland’s classes provides a distinctive illustration.
In the stricter class, the students were technology experts with the newly added artifact (i.e., curriculum software). This relationship sapped power from the teacher and provided students with confidence about their skills. The swap in power may also have boosted their willingness to practice scientific argumentation. Additionally, the artifact led the teacher to going to the back of the classroom, something that was not consistent with the traditional social structures in the classroom. The artifact could be argued to be a major influencer in this paradigm shift.