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Games of Data (Type 1 of 4) - Simple Learning Machines

An in-depth look at the first of the four categories of game-based learning: Games of Data, or "Puzzles". This will include a definition, how it connects to Bloom's Taxonomy, several examples, and what instructors can learn from their use.

 

Last Time

Last week we examined Bloom's Taxonomy and developed a hierarchy for understanding learning objectives. We then investigated the learning activities and assessment activities required as teachers move from the first level of learning (Remember) towards the top of Bloom's Taxonomy. We learned that as learning becomes more complex, the activities it takes to instruct or assess students becomes more difficult or costly to implement.

 

Games Of Data - "Pattern Puzzles"

Games of data are the simplest form of game-based learning because it only takes two steps to create them:

1. Take an established game that people will understand, and steal its mechanics.

2. Require players to complete your desired cognitive activity in order to play that game.

Take a look at the above screenshot. Before I spoil this game for you, I've got two challenges for you:

  • What is the name of this game? Guess it right now.

  • How do you think this game works? For which age group?

Let's see how you did:

Math Vs. Undead is a game for 5-10 year old children in which players solve math problems in order to defeat hordes of zombies and other monsters.

Pretty straightforward, right?

If you were to read PeakselGames' description of the game in the Google Play store, you would notice that the inspiration for this game is pretty expected:

This cool math game for kids combines zombie games with educational games for more fun while learning! Use your math vs zombies! Learning math with cool math games has never been easier! Kids love zombie games especially if they are shooter games, and parents love educational games for kids, so we decided to satisfy both sides and make a combination of the two - Math vs. Undead: Math Workout.

The appeal of Math Vs. Undead is the primary selling argument of all Games of Data:

  • Students are more likely to complete their schoolwork if it is fun.

  • Games are fun.

  • Therefore, turning schoolwork into games must make learning easier for students.

However, there is a problem with this line of reasoning that explains the strengths and limitations of Games of Data. The following questions seem to cast doubt on educational games like Math Vs. Undead:

  • Do students still play and enjoy games if they are layered with academic content?

  • Do students remember what they learn from games and can apply them in other settings?

  • What kinds of learning are games capable of fostering? How high can they go?

Fortunately, we have enough research to provide definitive answers to those questions. The answers are:

  • Yes

  • Yes

  • And Right Here:

Games of Data are extremely useful at ensuring that students can remember content, recognize patterns, and recall information. They enable students to memorize information that can be best described as data: names, letters, shapes, colors, dates, numbers, locations, and other pieces of simple information.

Before we define Games of Data, let's instead start by showing several examples of it. As we look at the following samples from this category (all of which earned high praise from reviewers and critics alike), ask yourself the following question: what will students learn as a result of playing this game?

(Hover over the images below to see their descriptions)

As you can tell, the most successful educational games are used for learning simple pieces of information. Now let's define both Data and Games of Data:

 

Defining Our Terms

Data:

Things known or assumed as facts, making the basis of reasoning of calculation.

(Oxford Dictionary)

Data (In Education):

Simple, assumed information that must be memorized in order to use them for reasoning or calculation.

Examples of Data:

  • Letters

  • Colors

  • Shapes

  • Numbers

  • Names

  • Dates

  • Spelling

  • Vocabulary

  • Facts

  • Trivia

Games of Data:

Activities which use game mechanics to reinforce student acquisition of relevant data, often through repetition and shaping of student's recognition and recall of information.

 

Games of Data: Top Strengths

1. Remembering Data

When it comes to the first level of Bloom's Taxonomy, games are exemplary at helping students achieve learning objectives. They are self-paced, offer rapid feedback, and shape student learning patterns with such specificity that they are likely the most cost-effective solution at teaching 1st-order information. This makes Games of Data ideal for young children or in the early stages of study within a given field.

2. Understanding Data

Regarding the second level of Bloom's Taxonomy, games provide opportunities for students to see simple information presented in multiple ways. Games of Data can test student recognition and recall of information by using patterns of gameplay and rewarding the steady growth of user understanding with a difficulty curve. This results in the student's ability to detect the usefulness of data in more complex environments.

3. Time/Cost To Implement

Thanks to the simplicity and linear learning required for data acquisition, Games of Data are relatively easy to develop and, as a result, are very cheap to implement. Many websites offer these games for free, while other site make it easy for teachers to generate their own educational arcade games for their students.

 

Games of Data: Top Weaknesses

1. Analysis, Evaluation, and Creation

While some Games of Data have opportunities for students to apply their learning, the levels of higher-order thinking like analysis, evaluation, and creation cannot take place with the linear and simplistic learning they offer.

2. Comprehensive Assessment

While Games of Data are great at providing instant feedback for students, they do not offer options for instructors to glean deep and meaningful information about the patterns of learning for their individual students. While some eLearning sites like Khan Academy are developing opportunities to use artificial intelligence to achieve this, these games can leave teachers relatively unaware of their individual student's needs.

 

Conclusion: What Did We Learn?

  1. Data is made up of simple information that students must remember in order to achieve more complex learning.

  2. Games of Data are excellent and cost-effective resources for helping students remember and understand data.

  3. Games of Data are ineffective at helping students achieve higher-order thinking or assessing their learning patterns.

However, as the complexity of learning and engagement increases, so too does the complexity of game design. As we climb up the ladder of Bloom's Taxonomy, we must let go of our friends in the Games of Data in order to take hold of a new ally.

 

Next Time

We will investigate Games of Concept ("Applications") and discuss the role it plays in helping students achieve application and analysis in learning. We'll then provide several examples and weigh the advantages and disadvantages it plays in educational settings.

Next Post:

 

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