A Critique of the Proposed National Education Policy Reform
IEEE Game Innovation Conference 2013 - Tuning Mobile Game Design Using Data Mining
1. Tuning Mobile Game Design
Using Data Mining
PL Lanzi, D Loiacono, E Parini, F Sannicolo’,
C Scamporlino, & M Pirovano
Game Innovation Conference 2013 – Vancouver September 23-25
2. Traditional Game Development
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Development of video games on traditional platforms
(PC/console) follows well-defined best practices
Significant portions of the overall cycle are devoted
to playtest and testing
The final product is generally expected to be almost
perfect and well-polished
concept
1-2 years
Game Innovation Conference 2013 – Vancouver September 23-25
final
product
3. Mobile Game Development
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Several companies follow the same development used for
traditional platforms and invest 1-2 years on large projects
However the approach is infeasible for most mobile/indie
companies which cannot sustain such a “long” cycle
Success in the mobile market appears not to follow
established criteria
Long projects are perceived as too risky
Recent strategies favor the rapid exploration of new ideas
and follow up only the more successful ones
Development 2-3 months (4-6 applications per year)
Follow up only to the most successful ones
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Game Innovation Conference 2013 – Vancouver September 23-25
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4. our experience
the task
develop one video game for Windows Phone
to participate to the 2012 Microsoft Imagine Cup
the challenges
short development (four months from start to end)
small user base (almost nobody we knew had a Windows Phone)
variety of platform with rather different features
secrecy! the app could not be distributed before submission
Game Innovation Conference 2013 – Vancouver September 23-25
5. our approach
instrument the application code
to trace almost everything the users do
perform very short playtesting sessions (1-2 days)
apply data mining to the collected data to
extract typical users’ behavior to evaluate gameplay
check users’ behavior on different platforms
Game Innovation Conference 2013 – Vancouver September 23-25
6. Bad Blood – A Serious Game About Diseases
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Casual game for Windows phones developed during the
Videogame Design and Programming course at the
Politecnico di Milano
Bad Blood aims at spreading the knowledge about human
diseases through a series of games settled in blood
vessels, in the respiratory system, and in the brain
Five continents, in which players can select a specific
region (e.g., West Australia) that also corresponds to a
disease and thus to a specific scenario
Four game mechanics: attack, tap, survive and puzzle
Game Innovation Conference 2013 – Vancouver September 23-25
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8. Collecting Game Data
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Our analysis focused on the two game modes with the highest interactivity
(attack and tap)
Before playing, users were asked for age and gender
Code was instrumented to collect any possible information (raw data) about
user behavior every 200ms
The raw data were then elaborated to compute several variables including
length and direction of the swipe gesture
center position of the players’ cells during collisions
number of opponents in every screen
the number of hits and misses in every seconds
the positions of the hits and misses
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Game Innovation Conference 2013 – Vancouver September 23-25
9. Mining Users’ Data: Population
Game Innovation Conference 2013 – Vancouver September 23-25
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10. Attack Mode: Trajectory of Users’ Swipes
Game Innovation Conference 2013 – Vancouver September 23-25
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11. Good Taps & Bad Taps
Game Innovation Conference 2013 – Vancouver September 23-25
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13. How We Solved the Issue in
Time for Submission
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We modified the gameplay before the final
submission to the competition
Each level in attack mode has a random instant
mini boss fight involving bigger bacteria and
viruses
The users has to instantly increase the firing
rate to be able to destroy the enemy before it
can hit the player or disappear at the bottom
of the screen
Game Innovation Conference 2013 – Vancouver September 23-25
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14. Conclusions and Take-Home Message
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We would never make the submission with a more traditional approach to
playtesting
Completely Instrumenting the code helped us getting the best out of the
relatively few users we could test our game with
The analysis of the collected data helped us
Improving the touch interface (and colliders’ placement)
Discovering a major design flaw that would have made the game boring
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We did not win the Microsoft Imagine Cup 2012! L
But we won “Share Care” a major national competition for serious games
devoted to blood donation and a special prize for innovation J
Game Innovation Conference 2013 – Vancouver September 23-25
15. Thank You!
download it @ http://www.badbloodgame.net/
Game Innovation Conference 2013 – Vancouver September 23-25
Editor's Notes
Qui ho messo due cover una di GTA V (ovviamente un successoneche non e’ statoancoracriticato) e SimCity che e’ statomassacrato.
in questocaso ho messo ungiocotradizionale (Deadspace e dots, piu’ sempliceche ha venduto di piu’).
sopra e’ attack, sotto e’ survive
Figure 3a shows the distribution of the swipe angle where 0 corresponds to the vertical direction, negative angles correspond to swipes toward the upper left corner and positive angles correspond to swipes toward the upper right corner of the screen; we also note a slight bias toward the right side of the screen (the skewness of the distribution is −1.82). Figure 3b shows the distribution of the length of the swipe gestures performed by the users. As it can be noticed, gestures tend to be very short (typically less than 40 pixels long) and long gestures are rare.
Figure 4d shows the distribution of taps on good (i.e., enemy) targets (placed in position ⟨0,0⟩). We note that the distribution is not centered on the origin but it has its peak at the lower left of it; this can be easily explained by noting in mobile games, players rarely cover the target with their full finger and that since the enemies arrive from the top of the screen so users tend to tap them from the lower bottom side. Figure 4e shows the distribution of wrong taps around enemies (assuming them in position ⟨0,0⟩) and include two types of mistakes: voluntary taps on wrong target (the players did not get the game mechanic correctly) or involuntary taps (the players aimed at something else but hit the wrong target). First, the distribution of the good taps (Figure 4d) around enemies is very different from the distribution of the wrong taps (Figure 4d). In fact, while good taps are more frequent in the areas very close to the target center, the bad taps are not centered around the target and are very frequent also in areas quite far from the target, i.e., at the edge of the collider box. This suggests that most of the wrong taps are involuntary and that players are able to clearly distinguish the good targets from the bad ones. Second, collected data show that players are much more accurate on the upper part of the screen with respect to the lower part (see Figure 4c) coherently with the designed mechanics. In fact, the targets should reach the bottom of the screen only when the player is busy with other targets and, thus, we expect a decrease in the tap accuracy. However, this finding also suggests that we could extend the design (and perhaps increasing the difficulty) by adding new enemy entering directions (e.g, having some enemies appearing from the left of the screen and exiting on the right).
Nell’analisi ci siamoaccortiche per la modalita’ di attackl’utentecontinuava a lanciareglobulibianchi con un ritmocostanteindipendentemente dal numero di nemicipresenti.Per variareilritmoabbiamointrodottoil boss. Il Globulonedellaprossima slide.our analysis identified a serious flaw in the attack mode: the collected game data showed that players keep firing the white blood cell at a rather steady rate and almost uniformly all over the screen. Therefore, players’ behavior is almost the same, disregarding the actual number of targets on the screen and time passed from the beginning of the level (see Figure 6), i.e., there are neither changes in the pace of the games nor thrills. Based on this analysis we decided to modify the gameplay before the final submission to the competition by adding, to each level in attack mode, an instant mini boss fight consisting of bigger bacteria and viruses randomly scheduled. These requires that the users instantly increase the firing rate to be able to destroy the enemy before it can hit the player or disappear at the bottom of the screen. Figure 7 shows a screenshot of the new boss fight element that can be randomly introduced during an attack mode level.