The Future of Gamification
The word gamification may have only received its name in 2002,
but the practice of making everyday tasks fun by making them game-like has been
around for millennia. The word “gamification” has emerged in recent years as a
way to describe interactive online design techniques where designers insert
gameplay elements in non-gaming settings so as to enhance user engagement with
a product, service or educational activity. Gamification, as a 21st-century phenomenon is a powerful tool for designers to drive user engagement for
several reasons. Firstly, you use it to inject fun elements into applications
and systems that might otherwise lack immediacy or relevance for users and
incentivize them to achieve goals. Users enjoy challenges, whether challenging
themselves (e.g., using step-tracking devices) or trying to win awards (e.g.,
virtual “trophies” for completing work-based e-learning). Secondly, the
dynamics designers incorporate in successful gamification serve as effective
intrinsic motivation, themselves – meaning users engage with the system because
they want to. Knowing the users and identifying the mission is key to getting
gamification right.
To understand the scale of the gaming industry, according to
Newzoo’s Global Games Market Report, the video game industry will have reached
a global market value of $139 billion by the end of 2018 and is already far
bigger than the Film & Music industry put together.
Machine learning is revolutionizing almost every industry,
from crop planning in agriculture to cancer diagnosis in healthcare. Machine
learning is the ability for a system to learn and improve from experience,
without being explicitly programmed. Machine Learning is also more commonly
known as AI. Machine learning, therefore, could have a huge impact on the way
games are developed. At the same time, control of non-player characters and the
building of unique environments could all be automated if we can develop
reliable algorithms for them. Modeling the real world is incredibly difficult,
but a machine learning algorithm could help with predicting the downstream
effects of a player’s actions or even modeling things the player can’t control,
like the weather. A machine learning algorithm’s strength is its ability to
model complex systems, and that is helping the developers to make their games
to be more immersive and realistic.
There are still major challenges facing machine learning
applications in gaming. One major challenge is the lack of data to learn from. Another
major challenge in building a realistic virtual world is how players interact
with friendly NPCs. In many games, you need to talk to scripted characters in
order to complete your objectives. However, these conversations are limited in
scope and usually follow on-screen prompts.
Using natural language processing could allow a player to
talk out loud to in-game characters and get real responses. In addition, games
that incorporate VR haptics or imaging of the player could allow computer
vision algorithms to detect body language and intentions, further enhancing the
experience of interacting with the game. But while we may agree that much of
gamification is weird, the question remains: in an educational context, is it
useful? Do games and gamified platforms actually help students learn? One
parent was quoted in the New York Times as saying: “the devil lives in our
phones.” The children of the tech elite are being kept away from the very
“innovations” their parents are pushing. The disconnect is troubling, and the
reasons behind it are worth examining. In reality, what doesn’t work is
expecting a game or app to perform the act of teaching on our behalf. We cannot
outsource the work of teaching to SimCity. We cannot expect an app to fix our
educational ills. Games are limited. They are maps, not places; tools, not
teachers. If we’re going to use them, we need to make sure we aren’t being
played.
Comments
Post a Comment