Can Gee’s Good (Digital) Game Design
Features Inform Game-Based Sport
Coaching?
RESEARCH
RJSS
JOURNAL OF
SPORT SCIENCES
Vol 4 (8): 257-269
http://www.rjssjournal.com
ISSN: 2148-0834
Copyright © 2016
Amy Price1, Shane Pill2*
1St.
Mary’s University, Waldegrave Road, Twickenham, TW1 4SX England
University, GPO Box 2100, Adelaide 5001, South Australia
2Flinders
*Corresponding
Author Email: [email protected]
ABSTRACT This action research (AR) study investigates the coach-asresearcher's (Author 1) development of coaching pedagogy from a games
based approach (GBA) informed by Gee's (2013) good digital game design
features with a female soccer team in the United Kingdom (UK). Over 16
weeks observation data was collected weekly from the coach-asresearcher's practice, and from one player's situated game play. Data was
collected from Author 1 in the role of the coach via practice plans with
evaluative notes, which were used as a context for dialogue between
Author 1 the coach-as-researcher and Author 2 acting in the role of
collaborative sport pedagogue. The research found that the three
principles of good digital game design were consistent with pedagogical
underpinnings of a GBA (empowerment, problem solving and
understanding). However, it was difficult to meaningfully translate Gee's
(2013) features of the principles into the coach enactment of practice
sessions. The main pedagogical challenge encountered was the multiplayer pedagogical context of an invasion game like soccer. Sports
practitioners concerned with being architects of designer games in a GBA
for combined technical, tactical and conditioning training may benefit
from considering Gee's (2013) good game design features, however, it
was not clear in this study how all elements of Gee’s good game design can
be meaningfully translated from the digital to the ‘physical’ sport coaching
practice context.
KEYWORDS Action Research, Coaching Pedagogy, Digital Games, Game
Based Approach, Learning, Soccer.
INTRODUCTION
This research investigates the coach-as-researcher’s (Author 1) development of game-based coaching pedagogy
when informed by with Gee’s (2013) good digital game design features. The category of games to which this
study has been conducted is invasion games (Den Duyn, 1997), where the aim is to invade an opposition’s
territory to score points or a goal. Invasion games can be tactically understood from three moments of play: 1.
Offense or attack when a team has possession of a ball and tries to score; 2. Defense when a team does not have
possession of the ball and tries to deny the opposition a scoring opportunity; and 3. Starts and restarts of play
(Mitchell, Oslin & Griffin, 2006). Research from the field of digital games design suggests that the game player
can be considered a ‘learner’. The game player as ‘learner’ chooses to play digital games because the design of
these games is deliberate, to capture the way humans enjoy to learn (Gee, 2013; McGonnigal, 2012; Prensky,
2007; Shaffer, 2006). According to Gee (2003), the question that digital game designers work with is: “How do
you get someone to learn something long, hard, and complex, and yet enjoy it?” The claim is that the design of
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the (successful) digital game probes high levels of intrinsic motivation to play and learn the game
(Brockmyer et al., 2009; Ryan, Rigby & Przybylski, 2006). The practice design ambition for digital game
designers is in many ways similar to the aim of coaches developing sports performance and
understanding through environments that promote high levels of intrinsic motivation to play and learn
the game (Pill, 2014). The digital game experience and games learning experience has previously been
theorised through the conceptualization of ‘game-as-teacher’, a phrase used to explain the way in which
game forms can be constrained (modified) to manipulate players’ game behaviors and decisions (Hopper,
2009, Hopper, 2011; Hopper, Sanford & Clarke, 2010; Richardson, Sheehy & Hopper, 2013). The
pedagogical skill of balancing play with purpose and function (Hastie, 2010; Lindley, 2003; Pill, 2013;
Salen & Zimmerman, 2004) shared by sport coaches in the design of coaching plans and digital game
designers includes the deliberate inclusion of specific design features maintained as having high potential
to promote and enjoy learning in order to encourage and sustain participation (Gee, 2003, 2007, 2013).
Pill (2014) suggests sport as a form of game playing and digital gaming have similar intentions to provide
an environment to engage in something that is complicated, not easily mastered and takes time to learn.
Gee (2007) suggests his ‘good game’ theory holds whether games are played digitally or ‘face to face’. This
led to the research question – Can Gee’s (2013) good digital game design features inform sport pedagogy
to enhance levels of engagement by young players learning to play sport? In this research, the sport was
Association Football/Soccer. This research is unique in that it the research question explores an area that
is under theorised and under-developed in sport pedagogy literature – the application of (digital) game
design learning theory to sport coaching pedagogy.
Gee’s ‘Good Game’ Theory
Gee argues that “a game’s design is inherently connected to designing good learning for players” (Gee,
2008). Similar claims are made for sport coaching (Charlesworth, 1993, 1994). Both digital games and
sport exist as a set of experiences a player participates in from a particular perspective. In a digital game
that perspective is that of the character whilst in sport that perspective is provided by the playing
position, which in invasion games we can place into three broad categories – forwards, midfields, and
backs or defenders. In both formats (digital and ‘physical’), digital games and sport are constrained by
task, performer and environment rules designed to establish certain goals for players, while leaving those
players some freedom of action to achieve those goals. Similar to descriptions of sport as a social practice
(Coakley, 2007), Gee (2008) explains that digital games often organize into communities of practice that
construct distinctive social identities. However, for this study we adopt Charlesworth (1993, 1994) sport
pedagogy advice to design games as learning spaces deliberately developed to combine technical and
tactical game components in one practice task and digital games as both contexts that are “richly designed
problem spaces” (Gee, 2008). We adopt Gee’s (2008) definition of context as a “goal-driven problem
space” (Gee, 2008) to explain how in both digital game play and game-based sport practice players move
through contextualized practice using skills, procedural principles, decision-making and perception of
information to solve problems in the game form. This study used the design features from Gee’s ‘good
games’ theory (Gee, 2007). This overview has been formatted using Gee’s (2013) game design principles –
empowerment, problem solving and understanding. The features associated with each principle are:


Empowerment: co-design, customise, identity, manipulation and distributed knowledge;
Problem Solving: well-ordered problems, pleasantly frustrating, cycles of expertise, information
on demand and just in time, fish tanks, sand boxes, skills as strategies; and
 Understanding: system thinking, meaning as action image.
These features are summarized in Tables 1-3.
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Table 1. Gee’s (2013) empowerment principle with related ‘good game’ design features.
Co-design
Customize
Identity
Manipulation and
distributed knowledge
Empowerment
Learners feel like active agents (producers)
Different styles of learning available and players try styles by choice
An extended commitment is powerfully recruited as player identity is
customizable
Players feel empowered as they can manipulate tools in ways that
extend their area of effectiveness
Table 2. Gee’s (2013) problem solving principle with related ‘good game’ design features.
Well-ordered problems
Pleasantly frustrating
Cycles of expertise
Information “on demand”
and “just in time”
Fish tanks
Sandboxes
Skills as strategies
Problem Solving
If learners face problems early on that are too free-form, they often form
creative hypotheses about how to solve these problems, but hypotheses
that don't work well for later problems
Game players feel pleasantly frustrated during game play, which occurs
when the game feels hard, but doable, and when effort is paying off
Expertise is formed by repeating the practice of a skill until nearly
automatic, then having those skills fail in ways that encourage the
learner to re-think and re-learn
Human beings use verbal information most effectively when they can see
how it applies in actual situations
Leaning is good when a complex system can be simplified
Learning is good when learners are placed situations that feels like the
real thing, and where risks are alleviated
Humans do not enjoy practicing skills out of context because they find
this meaningless. However, skill practice is needed to become efficient at
the skill be learned
Table 3. Gee’s (2013) understanding principle with related ‘good game’ design features.
System thinking
Meaning as action image
Understanding
Humans learn skills and strategies best, when they can see how these fit
into an overall larger system, or the whole (bigger) picture
Concepts have their deepest meaning for humans when they are
attached to perception and action
Games Based Coaching Approach
Author 1 identified the coaching approach prior to the intervention as ‘game-based’ for the team Author 1
coached, whereby players were predominately engaged in competitive but modified game play simulation
throughout training sessions. An example of a game-based coaching approach is the Australian Game
Sense approach (Australian Sports Commission, 1996). The word limits for a journal paper prevent a
detailed description and analysis of previous research on game-based coaching (also referred to as gamecentered coaching), and so readers are directed to Harvey and Jarrett (2006) and Zuccolo, Spittle and Pill
(2014) who have published reviews of the literature on game-based or game-centered teaching and
coaching for more detailed information. A game-based coaching approach like the Game Sense approach
is distinguished from more historically common practice and transmission coaching by the deliberate use
of teaching in and through game forms the tactical and technical dimensions of skill performance. There is
a partiality to a coaching preference for contextual game based practice tasks rather than the separation
of technical practice to drills leading to game play (Australian Sports Commission, 1996). Author 1’s use
of a GBA was validated with Author 2 in discussions about the intervention prior to practice commencing
and Author 1’s practice plan was then used during the study to substantiate implementation of the GBA
with Author 2.
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MATERIALS AND METHODS
This study adopted a form of practitioner-as-researcher self-study, informed by the method adopted by
Casey & Dyson (2008) and Casey, Dyson & Campbell (2009) in their self-study research of adoption of a
cooperative learning approach in physical education (PE). Practioner-as-researcher research is
characterised by a practitioners studying themselves usually with the aim to evaluate or improve
(Campbell & McNamara, 2009). Practioner research is distinguished by being undertaken by practitioners
as part of their ‘normal work’. Advocates of practitioner-as-researcher self-study suggest it is more
‘authentic’ because of its proximity to the reality of the natural setting of the work (McWilliam, 2004).
This study falls into what Kemmis (1993) called technical action research which Kemmis describes as
conducted “under the eye of university researchers” (p. 3) due to the role played by Author 2. The
position of the practioner-as-researcher has potential to influence the relations of the researcher with
other people normally in the work space, and therefore raise questions about the data trustworthiness.
Informed by Casey and Dyson (2008) and Casey et al. (2009), Author 1 endeavoured to counteract this by
having ‘free dialogues’ with players. Author 1 would ask the players questions that encouraged them to
respond naturally, rather than responding in a way that they thought Author 1 would want. In all other
ways, Author 1 attempted to maintain a ‘natural’ relationship with players as would occur without the
focus on self-study that was in action during practice sessions. This awareness aimed to account for
Author 1’s presence as researcher and participant in the study. The jurisdiction for this research study is
the United Kingdom (UK), where coach self-reflective and assisted reflective practice is advocated by
major sporting bodies such as Sports Coach UK (2012) and the Football Association (FA) as a national
governing body (Moon, 2014) However, there is still a noticeable scarcity in research involving coach
reflective practice dedicated to a sports coaching context. Studies that have reported evidence of a change
in coaching pedagogy have tended to be framed using a ‘critical’ problematizing approach (see Zhu, Ennis
& Chen, 2011; Harvey et al., 2010).
Ethics approval
The research commenced following both researcher 1’s university institutional ethics approval and club
ethical approval. Participation was via voluntary informed consent (British Educational Research
Association, 2011). Given the game of participants this involved parent/guardian approval as well as
player approval. In order to protect participants’ anonymity, participants in this study were de-identified
through the use of pseudonyms, and descriptions of the club were not involved in the writing of this
manuscript.
The research process
Author 1 acted as a coach-as-researcher aiming to self-study in order to close the gap between theory and
practice by developing ideas about pedagogy (specifically, ‘good game’ design theory) into Author 1’s
coaching. The research therefore presents an ‘up close and personal approach’ (Casey & Dyson, 2008)
typical of practitioner-as-researcher self-study, where the dividing line between the researcher and coach
is blurred. This meant that the core challenge to this self-study was the possibility of author 1 reverting
back to familiar ideas of pedagogy, and actually being able to learn and coach through Gee’s (2013) ‘good
game’ theory features. Two strategies were employed to avert a possible reversion scenario. Firstly, the
action of repeating the pattern of constructing game based soccer practice (planning), executing the
practice (acting), collecting data (fact finding), and analysing this data (analysis), before planning the next
game based practice (Lewin, 1946). Secondly, Author 2 as the experienced sport pedagogue. This
collaboration was informed by the role of the sport pedagogue in research described by Evans and Light
(2008). Similarly to Casey, Dyson & Campbell (2009) and Evans and Light (2008), it was considered
important that Author 1 was able to share a thinking and reflection space with a more pedagogically
experienced ‘other’, in this case Author 2. Author 2 was approached by Author 1 to participate because of
Author 2’s practitioner and research experience with game-based sport coaching. Through regular indepth discussions with Author 2, Author 1 became more overt in design, implementation and report of
the intervention coaching approach.
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Research setting
For this study, the club will be referred to as Bluebell Warriors. Soccer practice occurred weekly, with
each session lasting 90 minutes. There was a total of 50 registered female soccer players (<17 years) at
the club at the time of the study. The practioner-as-researcher (Author 1) is a participant in this study had
ten years’ experience of coaching soccer, and seven years’ experience of coaching soccer to a similar age
and ability to the team involved in this study. Author 1 was qualified at UEFA (Union of European Football
Association) B Licence level, and had completed the English FA Youth Award (module three).
The intervention
The intervention consisted of a game-based pedagogical approach deliberately informed by Gee’s (2013)
‘good game’ features of digital game design. These features are encapsulated into three principles;
empowerment, problem solving and understanding earlier summarised in Tables 1-3. The design of game
practices attempted to use all of Gee’s (2013) design features.
Data collection
Data collection tools consisted of other coaches’ (Author 1’s assistants) observations of Author 1’s
practice, Author 1’s observations and annotations of one player’s game play, and document analysis of
practice plans with retrospective evaluative notes. Observation data was collected on a week-on-week
basis, for the duration of 16 weeks (for the first half of the soccer season). Therefore, data were collected
for a total of 16 practices, equating to 24 hours of practice time. The learning focus of practices 1-4 was
attacking, practices 5-8 was defending deep, practices 9-12 defending high, and practices 13-16 counter
attacking. This is summarised in Tables 4-7 below. Author 1 wore a small body camera so that her verbal
and non-verbal aspects of pedagogy could be video recorded. The primary focus was to provide data for
self-reflection of Author 1’s pedagogical intervention into game-based coaching with ‘good game’ design
features, and the players’ reactions to the pedagogical actions. One player was selected at random to be
observed as a participant in the intervention coaching approach. For this study, she will be named ‘Kay’.
The primary focus of these observations was to observe Kay’s understanding of the learning focus of
practice, so that it could be understood whether the pedagogical intervention was impacting on player
participation and learning. Whilst observing the video footage, Author 1 took evaluative notes on the
practice plan, with a primary focus on comparing the practice plan with how the practice actually
transpired. The purpose of this was twofold; 1. Record any alterations to game design, and, 2. Record a
commentary of Author 1’s thoughts based upon the intervention coaching approach.
Data analysis
Informed by the methodology adopted by Casey & Dyson (2008) and Casey et al. (2009), data analysis
maintained a cyclical process comprising of Lewin’s (1946) planning – action - fact-finding - and analysis,
on a weekly basis for the 16 weeks. Therefore, data analysis was not a rigid linear process, but occurred
on three levels. The first level of analysis involved Author 1 sustaining a constant awareness of the
learning needs of the players relative to the weekly learning focus. Therefore, data collection and analysis
was not always formalised but often conducted ‘on the spot’. The second level consisted of a formalised
process conducted by Author 1 and Author 2 collaboratively, whereby data analysis was carried out using
an inductive approach to generate themes relating to pedagogy of ‘good game design’ within a gamesbased coaching approach. During this process, there was regular comparison for similarities and
dissimilarities between observation data and documentary data. At this level, Author 1 was able to plan
alterations to the weekly coaching pedagogy, resembling the essence of an action research approach. The
final level of data analysis was present in a collaborative conversation between with Author 2 acting as an
‘experienced sports pedagogue’ (Evans & Light, 2008), where there were discussions of data collection,
analysis and demonstration of findings.
Extensive planning process
Author 1 endeavoured to interpret all of Gee’s (2013) features into practice. This consisted of designing a
game form that was aligned to the relevant learning focus. For this study, a game was defined as having
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three key characteristics; rules, a strong element of play, and a clear aim (Hastie, 2010; Salen &
Zimmerman, 2004).
DISCUSSION AND CONCLUSION
The purpose of this study was to investigate the intervention challenges of practicing a coaching approach
that uses Gee’s (2013) good digital game design features. Specifically, the authors attempted to
understand how each of Gee’s (2013) features might actually look and work within invasion games
‘game-based’ coaching pedagogy. As the study involved a ‘team sport’ invasion game, soccer, an emergent
context from a digital games pedagogy consideration was the challenge of ‘multi-player’ pedagogy, rather
than the traditional one-player digital game design. Practice plans with evaluative notes were inductively
analysed. The themes that emerged from data analysis are presented together with the Discussion.
Individualizing learning in a game is challenging!
Observation of players during practice is part of coaching pedagogy, and in this study also served a
purpose of providing Gee’s (2013) ‘Information Just in Time and On Demand’ feature of good game
design. The pedagogical purpose was so that players were able to use relevant game hints from Author 1
to improve game play performance. In digital games, information is provided at a time in the game where
players can see how information applies to their own performance. It is difficult to advance the learning
of all players in every sport practice. Factors contributing to this difficulty included; coach to player ratio,
range of player abilities and managing players’ game play progress. From Author 1’s perspective, this
meant that pedagogical compromises were made to accommodate these challenges, whilst managing
Gee’s (2013) features. For example, the coaching setting comprised of eight players and one coach. Whilst
this coach to player ratio is somewhat small in comparison to the typical elite youth coaching ratio,
Author 1 found that consistent (on-task silent) observation of all players’ performance was problematic,
particularly during the main activity phase of practice. As a result, Author 1 was not always able to make
appropriate ‘on the spot’ adjustments to pedagogy to suit the customization of players experience, or
what one might describe as the individual needs of players. Author 1 attempted to adopt an observation
protocol whereby there was observation players’ performance systematically. For example, usually for
around 60 seconds at a time, Author 1 would observe player one, followed by player two, and so on.
However, there were occasions where Author 1 would observe a player outside of the systematic
sequence, usually when a significant event was occurring in the game.
During the first eight weeks of the coaching approach, Author 1’s practice mostly showed the ‘Information
Just in Time and On Demand’ feature through: a) direct instructions (during play and in breaks of play),
and b) use of deductive questioning before re-starts of play – this being similar to a ‘pause’ in digital game
play. However, Gee’s (2013) idea of ‘on time’ became problematic in this study due to the issue of
‘pausing’ the game for one player to have a learning engagement with the coach, whilst the remaining
players continue to play without being observed. Author 1 became conscious of the amount of time
pausing the game to engage in dialogue with a player was occurring, and suspected this reduced the time
available for the player to actually learn by playing the game. In digital games, players are not forced by a
coach to have a pause on play to discuss performance, although they may choose pause on the game.
Learning in digital games therefore follows the idea that learning occurs when dialogue is completely
connected to perception and action, which Gee (2013) describes as the ‘Meaning as Action Image’ feature.
Therefore, Author 1’s practice adoption of ‘good game’ design was challenged twofold; firstly,
understanding how to encourage the player to initiate dialogue, and secondly, coach intervention when
‘teachable moments’ are observed by the coach leading to external to the player control of when the game
is paused.
The activation phase of practice was less problematic for Author 1, due to the implementation of Gee’s
(2013) ‘Fish Tank’ feature (Figure 1). This was the first of Gee’s (2013) features to be clearly interpreted
by Author 1 into pedagogy because of its resemblance to a ‘warm-up’ (activation) phase that includes an
early ‘practice task’ component, typical of the coaching process. Observation of performance was easier
when the Fish Tank feature was implemented because all players were beginning the ‘warm-up’ game at
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the same level of game complexity, all at the same time. In ‘good game’ design, the Fish Tank feature is
considered a ‘tutorial’ which is present before the first level game engagement, or which is available at
the beginning of a new level. The Fish Tank feature, interpreted pedagogically in this study as a ‘tutorial’
involving the coach simplifying the game with scenarios that use a minimal number of players (1v1, 2v1,
1v2), then allowing players to identify or re-engage with tactical relationships with teammates and
opponents. Learning Focus: Team has possession of all three balls at the same time
Rules:
1. Each grid has one player from each team at all times.
2. Coach decides which team starts with two balls in possession, and which team with one.
3. Teams can pass the ball to spare (not in possession) team mates.
4. When team has possession of the three balls the fourth team member without the ball yells ‘go for goal’.
5. Goal is cored if player with the ball successfully brings the ball to a stop on the goal line.
Figure 1. Activation Phase – Fish Tank Activity.
Kay, the player selected at random to be observed during game play, was observed to work out and
applied a fundamental principle of attack during week two’s activation phase of practice; namely, width
and depth in attack. She realized implicitly through the game that by ‘asking’ for the ball in wide positions
as an attacker during a 2v1 offensive overload scenario either meant that she could receive a pass to play
forward, or if marked, her teammate has space to play forward. Kay then transferred use of this tactic
during the main activity phase when the game became in-balance (2v2 and 3v3), by drawing the defender
out wide, and then attempting a sharp movement into space to receive the ball. As stated earlier, Author
1’s practice plans aimed to use concepts of invasion games in attack and defense as an underpinning
framework for game development. For example, in attack, the game used common concepts; width and
depth to create space, playing forward as a priority, movement to eliminate the opponent and
maintaining possession. In defense, the common concepts were; being compact as a team to deny
dangerous space to the opponent, press to gain possession early, delay and divert opponent away from
dangerous space, and recovery lines to deny a counter attack. The importance of game design that
consistently uses attack and defense principles is reflected in Gee’s (2013) System Thinking feature (see
Figure 2). Gee (2007, 2013) argues that learning happens when humans can see the relationship between
a skill or strategy, and the ‘bigger picture’, ‘whole system’ or game genre. In this study, Author 1’s practice
plans considered the whole system as the game of soccer (which could be any size, 1v1, 2v2, 3v3 etc.).
Attacking and defending concepts are components of the whole system, which can be further isolated and
using more specific parts of the game in attack and defense. For example, attacking centrally or forcing
play into wide areas.
Learning Focus: Attack the goal
Rules: A goal is cored by stopping the ball on the goal line. 3 points for use of the
central goal; 1 point for use of an outside goal
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Figure 2. Activity Phase Game to Develop System Thinking.
Due to the nature of soccer as an invasion game, where gains and regains of possession (transitions) are
somewhat unpredictable as they emergent from the action of the play moment-to-moment, it was
important that practice design allowed players to learn strategies for in-possession and loss of possession
scenarios. In ‘good game’ design theory this would be known as ‘Skills as Strategies’, which refers to the
idea that in digital games players learn skills the skills needed to play the game by actually playing the
game itself (Gee, 2013). An example of the benefit of adopting a ‘skills as strategies’ pedagogical focus was
again highlighted by an example from observation of Kay’s practice. In game play during week 8 (see
Figure 3) the game was designing deliberately to challenge players in two ways: firstly, as a defender and
the question, “how can I prevent the ball from going behind me?” This led to observing Kay pressing the
ball – coming at the ball player to limit their ability to move forward, movements that forced the pass
sideways. Secondly, “how can I use the space in behind the defenders?” As an attacker, Kay seemed aware
how the defenders were likely to be thinking and acting, and therefore her observed strategy became one
of passing the ball forward before the defender could press-up at her. This example showed the player
implicitly learning by joined up thinking between roles in defense and attack, anticipated as a result of
designing a game that meant attackers and defenders were balanced (equal numbers), and consequently,
encouraged to see the relationship between attacking and defensive strategies by the learning intention.
Catering for the range of player abilities
During the main activity phase, in order for Author 1 to make worthwhile observations of performance,
Author 1 had to ensure that the game was pitched at the appropriate level for all players. In digital games,
Gee (2013) describes playing at the “outer edge of, but within their regime of competence” (p. 28), a term
used to explain optimal challenge. Optimal challenge is the point at which the challenge point extends the
player however, the player believes the challenge is achievable. The ‘good game’ design notion of
‘Pleasantly Frustrating’ (Gee, 2013) is similar to the concept of optimal challenge in that it explains the
way in which digital game design aims to make players feel like the task is hard, but doable, and that
effort is ultimately rewarded with further skill development that enables progress towards achievement
of the level. In sport pedagogical research, this may be captured in the notion of ‘game as teacher’
(Hopper, 2009; 2011, Hopper, Sanford & Clarke, 2010).
The idea of designing practice to achieve the appropriate difficulty level, and thus a ‘pleasantly
frustrating’ experience for players, proved problematic due to the vast differences in game play ability
levels of the players. For example, this deliberately design intention is shown in Figure 3. Figure 4
illustrates how each player was to accumulate points by performing game challenges, recording in real
time on their team’s whiteboard the results. This flexible challenge structure was hypothecated to align
with Gee’s (2013) advice that pleasant frustration occurs when players have an individualized and
adjustable end goal and method by which to attain this goal.
Learning Focus: Defending High
Aim: Defending – Win the ball high up the field
Attacking – Play the ball into the attacking third with control
Rules:
1. Goal is cored by stopping the ball on the goal line
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2. Wing players only move along middle third side line
3. Designated defender always plays defense (to create a 3v2 defensive overload)
Figure 3. Activity Phase Game to Designed to be ‘Pleasantly Frustrating’.
Positive outcomes from game play at practice were considered as: scoring a goal/preventing a goal (4
points), having a shot/preventing a shot (3 points), playing forward/preventing forward play (2 points),
maintaining possession/forcing play sideways or backwards (1 points). This framework was employed to
represent how digital games advise the player on their game play progress, using clear criteria for success
and failure (Pill, 2014).
Table 4. Challenge Grid for Counter Attacking.
Try to use the space on the outside and inside
of the opponents
I scored a goal
I had a shot
I played forward
I kept the ball
Try to play the ball ‘safe side’
I scored a goal
I had a shot
I played forward
I kept the ball
Try to take minimal touches
I scored a goal
I had a shot
I played forward
I kept the ball
Show how many ways you can play forward
I scored a goal
I had a shot
I played forward
I kept the ball
Show different ways of using your body to play
forward quickly
I scored a goal
I had a shot
I played forward
I kept the ball
Try to use the space behind the opponent
I scored a goal
I had a shot
I played forward
I kept the ball
Try to beat your opponent on one or two touch
I scored a goal
I had a shot
I played forward
I kept the ball
Show different ways of combining with your
team mates
I scored a goal
I had a shot
I played forward
I kept the ball
!
Using the challenge points grid (Table 4) with a point-scoring framework was to provide players the
ability to choose what they would practice (the challenge), decide how difficult or easy they wanted this to
be -similar to digital game design that commonly ask the player to select from beginner, intermediate or
advanced levels of challenge. Author 1 implemented this choice to be in a better position to manage a
range of ability levels within a common game form for all players. However, based upon collaborative
conversation with Author 2, the issue was raised of how this point scoring system might discourage
players from taking risks in the game (i.e. attempting new skills). Therefore, Author 1 used the idea of
Gee’s (2013) ‘Sandbox’ feature. This is commonly represented in digital games through the idea of ‘lives’,
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which encourage players to explore the game even when they are not yet competent as players have a
number of ‘lives’ that can be expended before having to regress to a lower level. The way in which
Sandboxes were used in this study involved players being able to save their scores weekly over a fourweek period, with the intention of providing a longer period of time for players to accumulate points.
Observation of Kay’s game play confirms that during the period that the Sandbox feature was in place was
that Kay achieved 40% more high scoring challenges (3-4 points) than low scoring challenges (1-2
points), meaning that she was more inclined to take risks by attempting more complex skills.
Managing players’ progress
As mentioned earlier, a significant challenge to managing learning effectively was the idea of ‘multiplayer’. In digital games, players are required to practice skills until they are nearly automatic, with forms
of mastery tests embedded within the level, and which confirm mastery of a new skill. Gee (2013) refers
to this good game design feature as ‘Cycles of Expertise’. Author 1 attempted to achieve this feature by
paced practice of skills using the challenge grid. Discussion with Author 2 led Author 1 to adapt practice
plans so that players were to choose from four challenges over the four-week period. Players could
choose a challenge, and when the player felt competent enough (usually determined from the score
board), she could move on to another challenge. Players were able to come back to a challenge if they felt
like their performance needed refining. This is illustrated in Table 5.
!
I
I
I
I
Table 5. Revised Challenge Grid for Counter Attacking [week 14].
Try to use the space on the outside and inside
of the opponents
Show different ways of using your body to play
forward quickly
scored a goal
had a shot
played forward
kept the ball
I
I
I
I
Try to beat your opponent on one or two touch
I
I
I
I
scored a goal
had a shot
played forward
kept the ball
scored a goal
had a shot
played forward
kept the ball
Try to use the space behind the opponent
I
I
I
I
scored a goal
had a shot
played forward
kept the ball
Using this design feature, players were able to choose what they learned (the challenge), how they learnt
it (with reference to the outcome based scoring system), and when they would learn something new
(pace of learning). Gee (2013) highlights that empowering players in their learning is critical to the
conception of digital game design. Author 1 further attempted to empower player learning by using
‘smart rules’, a term adapted from Gee’s (2013) ‘smart tools’. In digital games, ‘smart tools’ refers to
players ability to manipulate elements such as the choice of character, or objects (e.g. weapons or special
powers), to help achieve the game’s goal in a customized fashion.
When is a practice game no longer representative of the game?
Author 1 also adopted the use of specific game rules for individual players, theorizing that this would
provide a short term boost towards achieving the game’s aim or successfully completing a game challenge
(smart rules). In digital game design this is known as ‘Manipulation and Distributed Knowledge’ (Gee,
2013). For example, during play focused on the ‘defending high’ learning focus, Author 1 introduced a
smart rule (player x cannot be tackled). This posed the question of “how do I win the ball back from a
player who can’t be tackled?” Observation of Author 1’s practice confirmed that smart rules seemed to
lasted for short periods (1-2 minutes), and were most effective when assigned to players (or a team) who
needed an advantage.
Author 1 raised concern in conversation with Author 2 in regards to how using a smart rule as a shortterm fix to boost success for an individual player (achieving the game’s aim or completing a challenge)
may sacrifice learning of the other players. Author 1 felt it a struggle to consistently implement smart
rules into practice, because of a belief that games be realistic to the game of soccer, in other words, to
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“learn and develop skills in a match-like context” (Zuccolo, Spittle & Pill, 2014). Author 1 struggled with the
question of what is ‘realistic practice’, and at what point does adaption of rules, equipment and set-up
make a practice ‘unrealistic’ as the logic of play is disrupted. Digital game designers aspire to create game
worlds that simulates places in the real or imagined world. At what point is player identity lost as the
game is no longer ‘real’ due to the modification of the game design to constrain or promote specific
behaviors, such as in the use of ‘smart rules’.
Adopting a playing identity
In digital game design, Gee (2013) refers to the feature of ‘Identity’ as a mean to augment virtual reality,
and consequently encourage deep learning of a domain. The role of ‘play’, or ‘role-play’ in any kind of
game is an integral part of games (Salen & Zimmerman, 2004), and in coaching pedagogy, is considered
the difference between a game-based approach and non-game-based. In this study, Author 1 used the idea
of ‘role-play’ by asking players to take on the role of a chosen soccer player, or a made up (imagined)
soccer player. For example, Kay chose to play like Steph Houghton (England Ladies), and therefore the
idea was to fully commit to playing how Houghton would actually play, and make decisions in the game
based upon understanding of the soccer characters they took on. Similar to Launder’s (2001) idea of
‘fantasy games’, Author 1 provided a handout with an overview of each soccer characters’ playing traits
(see Table 6) – attempting to replicate what would be expected prior to beginning playing a digital game
when players are able to customize their character and its abilities.
Table 6. Identity (feature 3) Soccer Role-play Overview.
Player
Jordan
Henderson
Game Actions &
Interaction
Open body stance to
receive
Attitude
Values
Hardworking
Getting the ball from
defenders
Beating opponent
1v1
Range of passing
Modesty
Creating goal
scoring chances
Free kick taker
Lucy Bronze
Crossing the ball
Resilience
Fara
Williams
Disguising the pass
Leadership qualities
Cristiano
Ronaldo
Using both feet
Controlled and
composed
Lionel Messi
Steph
Houghton
Bravery
Creating 2v1’s in
wide areas
Controlling tempo of
play
Scoring goals in a
variety of ways
Create a
player
!
However in practice, Author 1 found it challenging to develop a ‘virtual reality’ in the soccer practice
environment, therefore, the attempt at blending ‘virtual’ and ‘physical’ worlds together were ineffective.
On occasions, Author 1 was forced to disregard the use of soccer characters ‘on the spot’, due to some
players not wanting to, or not being able to because of their level of ability, fully commit to the traits of
their character. This is not surprising in retrospect, as Gee (2013) explains that the Identity feature
requires ‘heavy investment’, which in a multi-player pedagogy environment like soccer practice requires
all players to do so for the idea of ‘role play’ to occur. Discussions with author 2 concluded that due to the
soccer environment at Bluebell Warriors, some players could not extend their role play to this level of
‘playfulness’. Again, the difficulty of managing a continuum of player ability in game design for
individualized challenge within soccer practice emerges.
The main pedagogical challenge encountered in this study was the idea of multi-player pedagogy, which
contrasts to the more common one-player pedagogy of digital gaming. The discussion demonstrated how
the coach in this study attempted to individualize learning for all soccer players playing the same game,
creating micro games that involve accumulation of points through challenges.
We suggest that there are distinct similarities between Gee’s (2013) good digital game design and the
intentions of coaching using game-based invasion games coaching pedagogy, as both seek to maximize
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engagement in skill learning. However, the environments – virtual and physical, are suitably different to
make the application of all features of ‘good game’ design theory difficult to translate meaningfully into
the sport practice environment. However, in this study that may be due to the age and stage of learning of
the players and perhaps it was relevant to consider the study with some and not all of the ‘good game’
design features. We recommend further studies attempting to translate ‘good game’ design features into
sport coaching at other levels of player development and using other games from across the game
categories.
Conflict of interest
The authors declare no conflict of interest
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