COTS Games: what and how they can teach – and how to test it

by Brenton Burchmore

http://thinkspace.csu.edu.au/brenton

 


COTS Games

 

Introduction

A great deal has been said on the power and potential of Digital Game Based Learning (DGBL) and how itcan be effective for children. Some have evoked case studies and research to show evidence of learning outcomes (Tuzun, et al, 2008), whilst others turn to pedagogy and psychology to unlock the secrets of games’ success (Bottino, et al, 2007). The Internet showcases lesson plans, personal blogs, teacher testimonials and a litany of subjective and circumstantial evidence and supporting documentation of how DGBL worked somewhere, somehow. Much of this is interesting, but the practical answers of what to teach using games, and how to teach it, remain hard to locate amid the noise. Even when we do find it, how do we know if it works?

In 1967 Marshall McLuhan gave us this quote (Logan, 2012):

“Anyone who tries to make a distinction between education and entertainment doesn’t know the first thing about either.”

Have we come so far in almost 50 years only to remain so unsure about game-based learning? Some educators are waiting for more educational games to be built, but commercial off the shelf (COTS) games have much to offer already.

What this document aims to provide is a single unified philosophy of what COTS games are most capable of teaching, and then provide a mechanism to test it. We break down the intellectual process of learning in a way that allows DGBL, teacher-led instruction, and online learning to work together as synergistic components. This is then showcased in a practical test that any school can perform – to compare a DGBL method directly against traditional teacher-led instruction.

The outcomes should offer a theory, a process, and a measurement all contained in one place.

 

Pedagogy

One of the most common challenges to GBL is the test of being pedagogically sound (DeFrietas, et al, 2013, Chap 5). Does it teach? This question is entirely appropriate, but perhaps a better question is: can we learn from games? This creates the comparative questions of; can we learn from games like we learn from teachers or books? Do we learn the same things from games as we do from teachers and books?

The answer to both of these questions is a complicated no (Hanghøj, 2013). But what if we simply askedwhat it is that we can learn from games?

This open question has led to what this author has dubbed the “3CON” model of learning. It divides the process into three layers that are sufficiently distinct to allow us to apply different mechanisms, tools and processes to each. This lets us make the most of the strengths of each method (modality) as they relate to each layer of learning.

 

3 CON Layers of Learning

3 CON Layers of Learning

Image 1. Copyright 2015 Conperior Pte Ltd. Used with permission. Published: Serious Games Keynote, CAMT Conference, Thailand (2016). Source: Author.

 

The 3CON Layers of Learning is a deconstruction of the learning process by this author which gives us a way to align learning with different modalities. These three layers; Concept, Context and Content – form the basis of the breakdown of the learning process that we are using for this model. This is not the only deconstruction of learning that has been proposed (Prensky, 2001),(Kafai, 2006) but this one gives us a useful handle on how GBL can be compared to other modalities of learning.

A similar breakdown was discussed by Paul Halmos in 1994 when he defined knowledge as the what(content), the how (concept) and the why (context). His 58 years of teaching experience had distilled this as being the three pillars of intent that should define teaching in general (Halmos, 1994).

 

3CON EXAMPLE

Imagine this article as a wiki document and how it might fit into this 3CON model:

3CON EXAMPLE

Image 2. Copyright 2015 Conperior Pte Ltd. Used with permission. Published: Serious Games Keynote, CAMT Conference, Thailand (2016). Source: Author.

 

We know what a wiki is, how it works and what it might do. Its a concept we understand which can apply to a limitless range of contexts. DGBL is one context within that, a specific set of subjective boundaries within which we apply the rules of the wiki concept. This particular document forms the specific content or detailswith which we can answer specific questions.

Here we can see that each layer offers not only a greater level of detail to the one before it, but that it becomes more specific. Thus the conceptual layer is the most versatile, offering a generalised platform of understanding that can apply to a wide range of contexts. Each context then sets a range of boundaries that allows us to focus into a subset of knowledge, whilst the content gets into the specifics of any one issue, decision or outcome.

 

Applying 3CON to Learning Modalities

In this model we are looking at the three most dominant modalities of learning relevant in the debate; digital game-based learning, teacher-led instruction, and student-led online learning. We look at the strengths and weaknesses of each.

GAMES THAT TEACH

Game play is a repetitive activity that is experiential in nature. Players participate in a process of play and learn through this immersion in the process (Bouvier, et al, 2014). However games are invariably aboutsomething in particular, and not always fun or interesting to the player (Fu, at al, 2009). Games also do not have a lot of details outside of their own narrative (Bouvier, et al, 2014).

Concepts: Games teach concepts well because they allow for these rules to be explored by experience and repeated exposure to the consequences. Players can learn these concepts through trial and error.

Context: Games are usually stuck in the single context in which the game has been designed. As the context is locked in at the production stage it is difficult for the game to teach outside of that context.

Content: Game play must be fast enough to be entertaining. Whilst some games are complex it is difficult to share large amounts of data with a player during a game as details can get in the way of momentum.

Games are best at: CONCEPTS

TEACHERS AT WORK

The human process is a combination of prepared material, skilled delivery and experienced adjustment along the way. Knowledge is expressed by the teacher in a way that promotes its acceptance and synthesis by the learner.

Concepts: Teachers must craft a situation or scenario which embeds the concepts within it in order to teach them. Thus enough content must first be taught and learned for the concept to then be revealed.

Context: The human imagination and its ability to extrapolate and re-imagine is uniquely suited at showing relationships between one situation and another. Only a human teacher can see the imagination gap in a learner’s thinking and help bridge it.

Content: With a few exceptions, humans do not have perfect memories. It is accepted that no teacher can accurately memorise a single text book, let alone an entire library of potential details.

Teachers are uniquely capable at teaching: CONTEXT.

ONLINE LEARNING

In 2002 the masses of information available from various digital and online sources exceeded what humanity has ever stored in analogue versions (Hilbert & Lopez, 2011). The Internet is a vast repository of raw data.

Concepts: Like teachers, understanding a concept from online media needs a sufficient amount of content with the concepts embedded within. It is going to require a lot of reading, browsing and thinking.

Context: No amount of reading or watching is going to show the learner where their imagination gap may lie. Without a human’s help the learner must rely on their own imagination to spark the leap to an unfamiliar context.

Content: The Internet supposedly holds hundreds of exabytes of data, and enough raw knowledge to satisfy any thirst for details. Thus online media is the ideal source of pure content-based information.

Online learning is the undisputed king of: CONTENT.

 

Modality/Layer Matrix

If we accept the strengths and weaknesses of each modality as outlined above, then aligning these with the three layers of the 3CON model looks something like this.

Modality/Layer Matrix

Image 3. Copyright 2015 Conperior Pte Ltd. Used with permission. Published: Serious Games Keynote, CAMT Conference, Thailand (2016). Source: Author.

 

Focusing in particular on games we can see that this model tells us we should be using games only to teachconcepts. This allows the context of the game to focus solely on being fun, immersive and engaging.

We then get the teachers to re-contextualise those concepts into other situations so that the learner can leverage that understanding outside of the narrow context presented by the game.

Finally we rely upon the masses of online data already at our fingertips to call upon the details we need whenever we need something specific.

 

EXAMPLE OF RE-CONTEXTUALISATION


Video 1. Copyright 2015 Conperior Pte Ltd (used with permission). Source: Author

 

A Learning Strategy to Test

At this point we can now devise a learning strategy for something that games might be good at (and for which we currently use other methods) and create a side-by-side test of these two methods to measure the results. This is the school-based test of DGBL using the methods, materials and process contained below.

This test is aimed at higher primary students (primary 5-6) but can be adapted to similar age groups. This test uses a free commercial off the shelf (COTS) game which was built solely for fun with no educational intentions. As per the above we are teaching fundamental concepts, but to raise the challenge those concepts will be advanced financial principles normally only taught in secondary schools.

THE CONCEPTS

This test will aim to teach year 5-6 students how to understand and use the following financial concepts:

  1. Sunk cost
  2. Opportunity cost
  3. Diminishing returns
  4. Asset leverage

This is positioned as a conceptual understanding more than a mathematical one. Students would learn the principles and impact of these concepts and how they might affect their own decision making. They are not expected to express this in calculated mathematical terms.

THE GAME

THE GAME

Image 4. Copyright (2013) Electronic Arts. Used without permission

 

The game used in this study is Real Racing 3 (EA, 2013) by Electronic Arts. First published in 2013 it is available on the Apple Store and Google Play Store for both iOS and Android tablet/phone devices. The initial download is free, and although it contains micro-transactions and in-game currency none of this is needed to play the game extensively.

In this game the player holds the device like a wheel, turning left and right to simulate driving mechanics. The player takes part in car races at simulated race tracks from around the world, earning prize money, upgrading their car (and buying better ones) and eventually qualifying for more advanced (and more challenging) racing tournaments.

Watch this YouTube gameplay trailer by AG Gameplay

Game Mechanics

The key game mechanics that are of most interest are the finance management elements. Players earn prize money from their race results which they must manage using traditional financial principles. Those who manage their funds the best will have the easiest path through the game.

The key is in how the money is spent. Any car can be upgraded, with components such as engine, tires, suspension etc being upgraded several times. Each successive upgrade of the same component on the same car costs more than the one before it – but yields a smaller relative increase in car performance. This is all clearly laid out in the information given and shows the effect of diminishing returns.

RR3-upgrades-2kvx2tl

Image 5. Copyright (2013) Electronic Arts. Used without permission

 

Players can choose to buy a new car instead of upgrading an old one. Deciding to do so means abandoning the investment previously made in upgrading the old car – thus encountering the sunk cost problem. This also highlights opportunity cost since funds are finite and decisions between which car to purchase must be made.

Image 6. Copyright (2013) Electronic Arts. Used without permission

Image 6. Copyright (2013) Electronic Arts. Used without permission

 

Finally, certain races offer more lucrative rewards but can only be done with certain cars. Spending their time on the most advanced races earns more cash with that time spent, but players must invest in the right car to enter the best races for best rewards – thus maximising their asset leverage.

Image 7. Copyright (2013) Electronic Arts. Used without permission

Image 7. Copyright (2013) Electronic Arts. Used without permission

 

Comparing Teaching Methods

Two separate methods of teaching are used side by side with two separate (small) groups of students. One method uses traditional classroom style tuition with paper handouts and prescribed homework. The other uses game play followed by teacher-led debriefing discussions with the students. In both cases the in-class time spent is kept strictly equal, whilst students are given freedom to spend as much (or as little) time on homework as they wish.

To measure the results the students first perform a standard test using multiple choice questions to assess their initial understanding of these concepts. The questions are worded in a context related to their age group (and could be altered to suit other ages). This sets a baseline for both groups to be compared against re-testing at the end of the project.

This comparison project is expected to last anywhere from a few days to a couple of weeks depending upon teaching schedules. Total in class time is planned for only two hours spread over two to four separate lessons. This avoids it being a major time burden and limits the potential for either student boredom or over-teaching distorting results.

The Classroom Model

This is a traditional model where handouts are given to students and the teacher can explain these concepts in whatever way they deem appropriate. Homework can be given but it is optional for the student to perform if they wish. There are no consequences outside of the student’s own preferences.

Creative freedom is given to allow the teacher to conduct this lesson to their strengths (without the use of games).

The DGBL Model

Students are given access to the game and a basic instruction on how to play it. They are encouraged to teach each other so that those who master it quickly help those who struggle. The game is played for an hour of in-class time and students are given homework to play the game as little or as much as they wish. Note that the game play is in solo mode – students cannot race against each other.

On another day a half hour class discussion takes place where the teacher discusses the concepts in the game and explains them in a financial context. Examples are given outside of the game context to show how those concepts can apply to real world situations. Students are invited to play more at home with this new understanding.

A final half hour class discussion then takes place to embed this understanding. Students are invited to make their own examples of these concepts at work, and to share any other revelations they have learned.

Final Testing

Both groups then re-sit the test at the same time. This time however an additional opinion survey is also included to measure their reaction to their particular teaching method, their opinions of their own learning, and their wishes for future learning.

Test results before and after are compared, and it is expected that both methods would yield improvements in scores. The question is how much improvement is shown in each method.

This is read alongside the survey results which reveal enjoyment and engagement comparisons.

 

Conclusions

The intentions from this exercise are as follows:

  1. Have a clear plan and intention for what COTS games can teach, and how
  2. Implement that plan to teach concepts normally considered advanced
  3. Compare DGBL results against traditional and accepted teaching methods
  4. Use this to influence policy and further action within the school

At the conclusion of this test the school will have results that show comparative learning outcomes from these two methods of teaching. Regardless of those results, the teachers, students, parents and administrators will all be better informed on the impact of DGBL in their own school.

If the DGBL results are positive they can be read alongside the (undoubtedly) positive survey results showing how the kids enjoyed the game play method. Even if both methods are similar in terms of learning outcomes, this should be read in the context of differing student engagement surveys.

If the school decides to explore further DGBL possibilities they will also have the 3CON method as a framework to create additional DGBL lesson plans, and to identify other suitable COTS games with valuable concepts hidden within them.

 


References:

Bouvier, P., Lavoué, E., & Sehaba, K., (2014). Defining Engagement and Characterizing Engaged-Behaviors in Digital Gaming. Simulation & Gaming August-October 2014 45: 491-507, doi:10.1177/1046878114553571

De Freitas, S., Ott, M., Popescu, M. M., & Stanescu, I. (Eds.). (2013). New pedagogical approaches in game enhanced learning: Curriculum integration. IGI Global.

EA (2013). Real Racing 3. (Digital Game) Published by Electronic Arts on Apple Store.

Fu, Fong-Ling ; Su, Rong-Chang ; Yu, Sheng-Chin (2009). EGameFlow: A scale to measure learners’ enjoyment of e-learning games. Computers & Education, 2009, Vol.52(1), pp.101-112

Halmos, Paul R. (1994). What is teaching? The American Mathematical Monthly. Vol. 101, No. 9 (Nov., 1994), pp. 848-854. DOI: 10.2307/2975131

Hanghøj, T. (2013). Game-based teaching: Practices, roles, and pedagogies. In S. de Freitas, M. Ott, M. Popescu, & I. Stanescu (Eds.) New pedagogical approaches in game enhanced learning: Curriculum integration (pp. 81-101). Hershey, PA: . doi:10.4018/978-1-4666-3950-8.ch005

Hilbert, M., & López, P. (2011). The World’s Technological Capacity to Store, Communicate, and Compute Information. Science, April 1, 2011, Vol.332(6025), p.60(6). DOI: 10.1126/science.1200970

Kafai, Y. B. (2006). Playing and making games for learning: Instructionist and constructionist perspectives for game studies. Games and Culture, 1(1), 36–40.

Logan, K. (2012). Setting the Record Straight – McLuhan Misunderstood:Setting the Record Straight 2. International Journal of McLuhan Studies. Retrieved from: (online)

Papastergiou, M., (2009). Digital Game-Based Learning in high school Computer Science education: Impact on educational effectiveness and student motivation, Computers & Education, Volume 52, Issue 1, January 2009, Pages 1-12, ISSN 0360-1315, http://dx.doi.org/10.1016/j.compedu.2008.06.004.

Prensky, M. (2001). Digital game-based learning. New York: McGraw-Hill Companies.

 

 

Part 3: Invitation

Part 3: Invitation

Inviting organisations, systems or workplaces to meet, respond & adopt the challenge of game-based learning.

In this section:

Master of Education (Knowledge Networks and Digital Innovation) developed by the
School of Information StudiesCharles Sturt University, 2016.
Charles Sturt University
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