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Gamification and data mining problems

By: Umer Nasim Rammay

What is Gamification

Gamification is becoming the buzz word with the marketing, in order to motivate the users. Gamification uses the elements of games to motivate and engage the learner. From instructional context Gamification is using game based mechanics, aesthetics and game thinking to engage people, motivate action, and promote learning and solve problems in non-game based context.

Gamification may seem like a strange and scary word but the concepts behind are the gaming momentums. The term was coined in 2002 by Nick Pelling. In 2013 Gamification was 421 million dollar industry and by 2018 it is expected to go 5.5 billion dollar industry that is the growth rate of 67%.

Gamification uses parts of games; another way of thinking of Gamification is as a continuum, on one end is simply adding points to learning event and on the other end is a fully immersive 3D hero. Most Gamification efforts somewhere clear in the middle.

In order to better understand the concept, let’s look at the elements that comprise most basic games.

  1. Achievement
  2. Competition
  3. Fun
1. Achievement

Achievement can be broken down into further topics:

  1. Progress:  Gamification tactic of using progress, tell the people how much they have achieve some goal or task.
  2. Rewards / Badges: Rewards or Badges are another form of achievement. People earn rewards for different things, unlocking certain thing because they have done some thing or they have completed some level or task.
  3. High Score: High scores tell the people that the people who achieve this high score have some type of proficiency in the game or in a specific level.
2. Competition

Competition is really the next factor, and divided into two sub elements.

  1. Opponent: Somebody else who is playing against you, and maybe s/he is using your strategies and efforts. You are competing with him in progress, rewards or in high score.
  2. Pride: We can also see the pride element here, be at the first place or second or third.
3. Fun

There is also a fun element in the Gamification.

  1. Easy: It means easy to learn how to do it, you don’t need of use long manuals try to figure out how to play the game.
  2. Challenging: At the same time you want to be challenging, one uses some sort of Gamification technique some type of challenges are involved in it.
Types of Gamification

Gamification can be refined into further two types:

  • Structural Gamification
  • Content Gamification
Conclusion

Gamification is simply applying game elements, game thinking and game mechanics when designing instructions.

 

Data mining issues in Gamification

We use data mining because player alone feedback gives a one side of picture, and it can’t guide us a better guide to find out a effective game design. But at the same time during this data mining process we face many issues that are briefly describe here:
1-    Highly Production Cost
First of all production of these types of games demands a lot of expert people that are highly trained and must have good command on their skills at the same time we need costly equipment. These parameters increase the production cost.  To overcome these issues we do compromises on many things like in designing phase, production phase or on  data quality.
2-    Diversity of Data Types
The data of players is very complex in its nature because we are handling text, images and videos all at the same time, and many times data nature differ from user to user so sometimes it becomes very difficult to compute all data at the same time.
3-    Social Issues
It is one of the most common issue in data mining and it becomes a question for individual’s privacy. When data is collected from player directly, we are storing their personal information, their sensitive transactions information, daily activities, their behavior and so forth. So it becomes very important how we will deal with this data, in such a way privacy of individuals should sustain.
4-    Data Cleaning
Data can only be useful if it is noise free. Data cleaning is required due to many factors present in the raw data; it may be due to wrong input from the player, presence of wrong data, incomplete data and data coming from multiple sources. On such type of data, data cleaning is very necessary because if we do not perform data cleaning methods, it will lead us to wrong interpretation.
5-    Sampling of data
It becomes very difficult when we have millions of users and we are getting data from them approximately every day so in this case the size of data goes to terabytes, so it becomes very difficult to handle such a big data especially when we have number of dimensions in our data. In this case we take a sample from our dataset. Sampling has its own limitations and challenges, for example selecting a sample that represents the properties of entire data.
6-    Security
Sometimes it is the important issue with the Gamification data because we are dealing with very sensitive information. Data should be kept safe and we should define the rules how data will be accessed and handled.
7-    Time Series Data
A particular issue that is faced in data mining of Gamification data is related to time series data. Time series data used for prediction and it can be polluted by noise in data. By using different techniques to remove noise in the data but reduce the accuracy of our results.

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