This document describes the development of an educational game to teach immunology. The game uses a "tower defense" paradigm where the player controls immune system cells to defend against pathogens. The game was designed based on research into effective educational games. It was created to teach the adaptive immune system, unlike a similar existing game which focused on the innate immune system. The document provides background on immunology concepts and the game development process. It concludes that the game aligns with principles of effective educational games and could be improved in the future with additional features.
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The specific aim of the project was to design, develop and pilot a prototype game platform that might be used to efficiently develop games for m-learning. The basic idea is to use the mobile phone to implement games bridging the real and virtual world. These games are firstly intended to directly support learning via opportunities to develop knowledge and cognitive skills in an exciting and inspiring – and hence in a highly emotional – way, and secondly to indirectly motivate users to refer to other media (e.g. “classic” libraries, scripts, etc.) for learning purposes.
A video game that teaches biology and chemistry, cell biology and nanotechnology... Immune Defense is a real time strategy game. Designed to engage 16 year old students, Immune Defense is fun for ages 10 through 110. Designed upon data about what makes people confident with molecular biology, Immune Defense is also designed to be engaging to a broad audience (casual/midcore game style). Added to this talk are 4 slides of learning objectives and how they are presented in the game.
Navigation Control and Path Mapping of a Mobile Robot using Artificial Immune...Waqas Tariq
This study aims to apply Artificial Immune Systems (AIS) to a mobile robot making it capable of traversing an unknown environment and mapping it while looking for the target. We have implemented a mixture of Antibody-Antibody (Ab-Ab) interaction algorithm coupled with negative selection algorithms to develop the proposed AIS controller. We have also developed a method for random generation of antibodies to make the system more similar to the actual biological process. Finally, a generalized architecture for representation of antibodies and antigens in a standard mobile robot using proximity sensors for interaction with the environment has been introduced. The results show that the proposed algorithm was able to explore the unknown environments while learning from past behavior and look for the target. It was also able to successfully map the traversed path and plot the obstacles based on their type.
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Presentation for the VII International Seminar of the UOC UNESCO Chair in e-Learning: Mobile Technologies for Learning & Development.
The project mobile Game Based Learning (mGBL) is coordinated by evolaris next level GmbH and: has been implemented from October 2005 until December 2008, has been conducted by 30 researchers from 11 project partners from 5 European countries (Great Britain, Italy, Croatia, Austria and Slovenia), used nearly 600 person-moths resources with a budget of 2.5 Mio EUR, was supported by the EU under the FP6 IST.
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A video game that teaches biology and chemistry, cell biology and nanotechnology... Immune Defense is a real time strategy game. Designed to engage 16 year old students, Immune Defense is fun for ages 10 through 110. Designed upon data about what makes people confident with molecular biology, Immune Defense is also designed to be engaging to a broad audience (casual/midcore game style). Added to this talk are 4 slides of learning objectives and how they are presented in the game.
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2. The biological information dispensed during the gameplay is both
correct and useful for the player to achieve the stated goals, which
are usually tasks related or complementary to those of the cells the
player is learning about.
With all this information in mind, we began to devise our game.
We wanted to ensure that our game was distinct from Immune
Attack, and we came up with several differences: for one, Immune
Attack focuses on the innate immune system, while our goal was
to teach the adaptive immune system, which will react differently
to different antigens. In addition, the complexity of Immune
Attack has a steep learning curve to effectively control the
nanobot, especially if the player has never played a “space
combat” game before. Finally, there is little incentive to play
Immune Attack again once it has been completed, as the level
designs and objectives do not change. While this game appeared
to fulfill most of the qualities Malone laid out, it did not contain
an adjustable difficulty level, nor were most elements of the game
random (which could lead to players quickly becoming bored with
repetition).
3. IMMUNE SYSTEM
The immune system includes many interdependent systems of the
body, which act to stop invasions by pathogens. Pathogens are any
object that causes disease and include bacteria and viruses.
When a pathogen enters the bloodstream either through a cut or
the mucous membranes in the nose and mouth, it is first
recognized by phagocytic cells like macrophages (“big
eaters”)(Figure 1 step 1). Phagocytes recognize objects as being
either “self” or “non-self” through a protein complex on the
surface of all vertebrate cells called the Major Histocompatibility
Complex (MHC). After partially digesting any “non-self” cells
the phagocyte will present portions of the cell called antigens on
its surface using MHC (Figure 1 step 2). Helper T cells then use
this information to direct the immune responses of the body [3].
The immune system acts to remove pathogens from the body by
two methods called the cell mediated response and the humoral
response. Both responses are triggered by Helper T cells. A
macrophage that has digested a “non-self” body will then secrete
chemicals called cytokines (regulatory molecules that activate
cells of the immune system). Specifically, the cytokine secreted
by macrophages is called Interleukin-1 (IL-1) (Figure 1 step 3).
IL-1 signals Helper T cells to bind to the macrophages presenting
the antigen-MHC of pathogens. The Helper T then releases more
cytokines, this time Interleukin-2 (IL-2) (Figure 1 step 4). IL-2
triggers both the humoral (B Cells) and cell-mediated (Cytotoxic
T Cells) responses of the immune system. For the humoral
response IL-2 stimulates B Cells, but for the cell-mediated
response it stimulates Cytotoxic T cells [3].
B Cells bind to antigen presenting cells (ATCs) and remember the
specific antigen for targeting. Once activated by IL-2 (Figure 1
step 5), B cells respond by developing into either Plasma cells
(Figure 1 step 7) or Memory cells (Figure 1 step 8). Plasma cells
produce Antibodies (Figure 1 step 9), which bind to the specific
pathogens and infected cells that contain the antigen from the
ATC (Figure 1 step 10), marking them for destruction by
macrophages (Figure 1 step 11). Memory cells “remember” the
specific antigen that they were signaled for and immediately
produce antibodies if a pathogen with those antigens enters the
body again (this leads to “immunity”) [3].
Figure 1. Immune Response Process [3].
Cytotoxic T cells also bind to ATCs and remember a specific
antigen. They respond to IL-2 by dividing into more Cytotoxic T
cells [3]. Cytotoxic T cells are responsible for destroying cells
that are infected by pathogens with the antigens from the ATC in
order to stop the multiplication of pathogens (Figure 1 step 6).
Another type of cell that aids the immune system is the Natural
Killer (NK) cell, which acts much like a Cytotoxic T cell,
destroying cells that do not have “self” MHC presentations or
have damaged MHC presentations (such as cancerous cells) [3].
4. SOFTWARE PROCESS
We knew from the start that our game would not be able to match
Immune Attack in terms of technical prowess, but could appeal to
a more “lighthearted” gamer. We envisioned a game with two
dimensional graphics, controls that were very simple to learn,
constantly-updating circumstances, a difficulty setting, a list of
high scores, and randomly generated levels to move about in.
This would satisfy all of Malone’s points except for the fantasy
element. While Immune Attack dispensed the biological facts
around a fantasy story, we wanted to keep non-realism to a
minimum so that the biological processes and facts would remain
the focus of the game. When devising the actual gameplay, we
considered the idea of a Real-Time Strategy Game (in which the
different cells were directed around in turn-based combat), a
shooter (in which a single white blood cell would move around
and shoot down antigens), and a Tower of Defense type game (in
which the player could supply a number of units to automatically
fend off attackers and, depending on how well they do, add more
as the game moves on). Eventually, we settled on the third
exclusively, as it had the most potential to simulate the biological
system as accurately as possible. In our game, the player
essentially controls an immune system, which is responsible for
creating and sending the correct cells to the pathogens’ locations.
Depending on how many pathogens the player is able to help
3. defeat, s/he will have the option to send more help.
Our idea adapted a traditional “tower-defense” game into a novel
cell-based approach with immune system cells taking the place of
towers. One of our main concerns with this idea though was
maintaining a fun and involved game that was also educational.
The automated, strategic nature of this game could bore players if
they were not interacting enough or did not feel their actions made
a difference in game play. To counter this we made a few
additions that increased user input, which will be discussed in
more detail later.
Normally in a Tower Defense game, a player must defend a castle
with citizens inside it by strategically placing different types of
defensive towers along the path of the incoming attackers. The
towers automatically shoot at attackers in their vicinity and the
player receives points for destroying attackers. After each “wave”
of attackers the player can purchase more advanced towers or
upgrade existing towers with the points they have earned. Players
can save up points over several waves to buy more advanced
towers. An attacker that makes it all the way to the castle kills
one citizen. The game is over when all of the player’s citizens
have been destroyed.
In our adaptation, the player has immune system cells to defeat
attacking pathogens in the bloodstream. The pathogens enter the
bloodstream at random positions and search for cells to infect.
The cells available for the player are macrophages, Cytotoxic T
cells, Helper T cells, and B Cells (B Cells are capable of
developing into Plasma and Memory Cells). These cells act as the
“towers” only instead of being stationary they move about in the
bloodstream and automatically interact with any pathogens in
their vicinity. Also floating in the blood stream are generic cells
that act as the “citizens.” Once a pathogen binds to a cell however,
it multiplies into several more pathogens. After a wave of
pathogens is defeated by the immune system cells, the player can
add more cells choosing from those listed above by using points
received. In each successive stage, the user’s “citizen” cells
regenerate and the number of pathogens increases.
Additionally, more user control during each stage has been
included to increase both the interaction and interest level of the
player as previously mentioned. These additions allow the player
to select an immune system cell and direct it towards a pathogen
or other cell. When the user selects a target for a cell, it overrides
any automatic movements that the cell would normally make.
Because the cells cannot “see” other cells outside their range, it is
critical that the user directs them at times. The user may also use
this feature to protect “citizen” cells from coming into contact
with pathogens as they float around in the bloodstream.
In order to code these ideas, we organized our thoughts into use-
case scenarios, and a state diagram for the overall game.
For all of the actors in the game, we had a base class containing
information about their position, velocity, their primary target,
and data pertaining to cells they had bound with. In addition to
this base class, we used two interfaces to consolidate functions
that many of the cells would have in common such as the
capability to divide. Each of the specific cells were then derived
from combinations of these three items and extended to contain all
of the specific movements and interactions that each cell
undergoes with the others.
During game play, all of the cells are placed in a list and looped
through, first updating their positions and then checking their
interactions with other cells. Cells can react to other cells by either
colliding (“binding”) or by being within a certain distance of
another cell.
The player earns points for buying cells based on the number of
“citizen” cells remaining at the end of each wave of pathogens.
The player’s score is calculated by adding 20 points every time a
pathogen is destroyed, and giving a 221 point bonus for each
“citizen” cell that remains at the end of a stage.
5. FUTURE WORKS
After playing the game, we found many ways in which it could be
improved upon in future versions. With more time, the game
could be expanded to include features such as randomly generated
levels, different difficulty levels, and several different types of
pathogens.
Randomly generated levels would allow for both increased size
(levels could be partially out of view) and make each game
experience unique. Some time was spent with this idea, but we
were unable to be complete it in the time we had available. The
levels would be similar to a vein network generated from nodes.
The nodes would generate branches based on a probability and
have a maximum number of branches allowed for each node.
Around each line connecting nodes, a box would be created in
which the cells float around inside these connected boxes in a
network of nodes.
With the addition of several different types of pathogens, the
game would gain biological accuracy by including immunity as
well as an extra fun factor to gameplay. This system would work
by making it so that immune responses by the immune cells target
specific antigens on the surface of pathogens and pass on these
antigens as targets for the Cytotoxic T Cells and B Cells. In this
way, each different pathogen would require a separate immune
response.
Varying degrees of difficulty could use the different types of
pathogens to make sure the game fits the abilities of more users. If
several types of pathogens were introduced to the game, the
difficulty level could increase or decrease the number of types of
pathogens that would attack (it would be more difficult to defend
against several types of pathogens). The difficulty could also be
adjusted by raising or increasing the threshold distance of
activation for cells.
Separate from the game itself, a framework could be created that
would use scripting to allow the user to extend the game by
modeling any similar cellular system of the body in a very short
period of time.
6. CONCLUSION
The effectiveness of our immune defense game could be most
definitively measured through actual human testing of what
players learned by playing the game, but due to restraints on
project time and the availability of testers this was not possible.
Therefore we have evaluated our game by comparing it to
Malone’s observed components of effective educational games
[2]:
1) Clear goals that students find meaningful.
The immune defense game has a clear goal of defending cells
from infection. Students can relate to this because everyone has
4. been sick and realizes the importance of eliminating viruses and
bacteria.
There is also a high scores list that encourages students to try for
the highest score. This is one of the most basic elements of
motivation in a game and helps create competitiveness among
peers.
2) Multiple goal structures and scoring to give students feedback
on their progress.
As previously noted the students' highest scores are tracked. At
the end of each stage the student receives immediate point
feedback based on how well they defended their cells during that
wave. They receive more or less depending on their performance.
3) Multiple difficulty levels to adjust the game difficulty to learner
skill.
Unfortunately we did not have time to add multiple difficulty
levels, so our game runs the risk of being too hard for some and
too easy for others. Neither of these scenarios is acceptable as the
student will quickly become either frustrated or bored and be
hindered in their learning.
4) Random elements of surprise.
Although the random elements in the game are not full of
surprises, the game plays differently every time because of the
random placement and movement of cells. This area could be
improved with added plot details such as having multiple
pathogens that enter perhaps in later stages. The result of upgrades
in this area could allow the game to be fun for multiple sittings
rather than a few.
5) An emotionally appealing fantasy and metaphor that is related
to game skills.
Our game is based very strongly in reality, so the most fantastic
element is the appearance of the cells. Though they are in some
ways true to the real appearance, they are cartoon-like and two-
dimensional. However this does not preclude the game from
having emotional appeal, because most students wish that they
could help their immune system so they can get better quicker.
Our immune attack game matches at least three of the five
elements outlined by Malone and partially fits the others. As
much as these elements of good educational games are believable,
there are many types of games which can be successful with little
use of these components. For example simulation games are
educational but lack many fantasy elements. They are made
successful by their detail and ability to customize several different
aspects of a player's game. Games can be successful as long as
they are engaging and allow players to learn something during
their play.
In light of this, our immune defense game is actually a fairly close
simulation of the immune system's processes. Our game's ability
to educate students on the processes of the immune system
depends heavily on how engaging and entertaining the game is for
actual students; many studies have shown that different types of
games can be entertaining. However, entertainment is not our
main goal and therefore the real value of the game will only be
assessed after testing its ability to teach students.
7. ACKNOWLEDGEMENTS
This work was done at the University of South Carolina as part of
the Research Experiences for Undergraduates in Multidisciplinary
Computing project and supported in part by the National Science
Foundation (Award #0649105) and the Office of Naval Research
(Award # N00014-07-1-0686). We would also like to thank Dr.
Jijun Tang, Dr. John Bowles, Dr. Caroline Eastman, Matt
Mitman, Mike McLaughlin, and Kimberly Yonce for their help
and guidance with this project.
8. REFERENCES
[1] KIERKEGAARD, P. 2008. Video Games and Aggression.
International Journal of Liability and Scientific Inquiry, 411-
417.
[2] MALONE, T. W. 1981. Toward a Theory of Intrinsically
Motivating Instruction. Cognitive Science: A
Multidisciplinary Journal, 333-369.
[3] RAVEN, P. H., AND JOHNSON, G. B. 2002. Biology, 6th
ed. McGraw-Hill, New York, NY.
[4] SQUIRE, K. 2003. Video Games in Education. International
Journal of Intelligent Simulations and Gaming, 49-62.