An Investigation of Gamification Typologies for Enhancing

Learner Motivation

Barryl Herbert, Darryl Charles, Adrian Moore

School of Computing and Information Engineering

University of Ulster Coleraine, Northern Ireland

Therese Charles

SilverFish Studios

Coleraine, Northern Ireland

General Motivation for this Research: Virtual Learning Landscapes

Specific Focus of this Research: People are Different

http://www.custbase.com/portal/blog/wp-content/uploads/2011/05/different-people.png

People’s Temperament and Psychology Varies Keirsy

Temperament

Myers-Briggs Mapping Roles Typical Attributes

Artisan ESTP, ISTP, ESFP, ISFP Promoter, Crafter,

Performer, Composer

Fun-loving, Excitable, optimistic,

realistic, unconventional, bold, and

spontaneous.

Troubleshooting leaders.

Guardian ESTJ, ISTJ, ESFJ, ISFJ Supervisor, Inspector,

Provider, Protector

Dependable, helpful, and hard-working,

dutiful, cautious, humble. Stabilizing

leaders.

Rational INTJ, INTP, ENTP, ENTJ Field Marshall,

Mastermind, Inventor,

Architect

Pragmatic, skeptical, self-contained,

problem-solvers, ingenious,

independent, and strong willed. Strategic

leaders

Idealist INFJ, INFP, ENFP, ENFJ Teacher, Councellor,

Champion, Healer

Enthusiastic, trust intuition, kindhearted,

authentic, giving, trusting, and focused

on personal journeys. Inspirational

leaders.

Keirsey.com, “Keirsey Temperament Website - Overview of the Four Temperaments.” [Online]. Available: http://www.keirsey.com. [Accessed: 03-Jun-2014].

Learners are Different

http://www.jcu.edu.au/wiledpack/modules/fsl/JCU_090344.html#_Kolb's_learning_styles_1

Player’s are Different

Bartle’s Player

Type

Symbol (Behavior) Typical Attributes

Killers Clubs (they hit people with

them)

Acting / Players. Focus on rank and direct

competition. Leaderboards.

Acheivers Diamonds (they're always

seeking treasure)

Acting / World. Attaining status and

achieving goals. Achievements.

Explorers Spades (they dig around for

information)

World / Interacting. Discover the unknown

and understand how the game works.

Socialisers Hearts (they empathise with

other players)

Players / Interacting. Motivated by

developing a network of friends.

Knowledge and information are important.

See http://www.gamified.co.uk/?s=types and http://mud.co.uk/richard/hcds.htm

Bateman’s DGD1 Model

• Conqueror: Competitive, win-at-all-costs. Players of this type are goal-oriented and enjoy feeling dominant in the game or in social circles set around the game.

• Manager: Logistical, plays to develop mastery. Such players are process-oriented and will replay completed games if they can use their newfound mastery to unearth novelty at deeper levels of detail.

• Wanderer: Desires new and fun experiences. Less challenge-oriented than the above types, these players primarily seek constant, undemanding and novel enjoyment.

• Participant: Enjoys social (living-room) play, or involvement in an alternate world.

Principles of Good Game Design

• The Games Oriented Learning Framework (GOLF) emerged through rigorous research in the areas of games design, engagement and flow. FUN: engagement is easier if the experience is enjoyable.

SOCIAL: engagement is reinforced by the social support of others going through the same experience.

IDENTITY: engagement can be encouraged if everyone has a visible role in the learning environment.

CHALLENGE: engagement can build on human competitive drive, enhanced by social pressure.

STRUCTURE: engagement is more likely if objectives and constraints are clear and acceptable.

FEEDBACK: engagement is reinforced by making achievement explicit and timely.

Play v Game v Gameplay

• Requires a lusory attitude (and not everyone is indulgent in this way) but if you are playful you may not be a gamer: Play is not bounded by fixed rules and doesn’t require an outcome.

Some people are averse to fixed challenges and prefer self-defined challenges. Are not particularly interested in competitive reflection.

A game is a problem-solving activity, approached with a playful attitude (Schell) and typically has an observable and measurable outcome. Some people thrive on learning rules and overcoming challenges. Beating other people

or comparing performance to others.

Gameplay is derived from the combination of pace and cognitive effort required by a game (Crawford). Intellectual stimulation and progress is core. Learning, doing, mastering.

What is Gamification?

• “Gamification takes inspiration from commercial game elements, design patterns and metaphors in order to improve the design of non-game systems to positively influence behaviour, enhance engagement, and motivate people to achieve their goals. Facilitate experiences with positive emotions.

• Much of the core gamification ideas are rooted in psychology and in the simplest form resembles customer reward schemes.

• At its most effective gamification harnesses inherent, intrinsic motivation of users and is built on more complex processes than just reinforcement learning.

Tale of Two Gamifications

• Influence – what we want people to do and be like Rewards and techniques focusing on extrinsic motivation. Tasks and processes that are deemed important but are not a particular

internal desire for the user. Getting started, being consistent. E.g. Attendance for students. Can scaffold more important emergent behaviours.

• Support – what people want to do and be like Rewards and techniques focusing on intrinsic motivation. Tasks and processes lending themselves directly to outcomes that the user

inherently desires. Learning, learning how to learn. Knowing and capability of doing. Frequently more complex and process oriented. Related to learning theories.

What Really Engages? RAMP

• Self-determinism and intrinsic motivation Relatedness (social factors),

Autonomy (choice and freedom),

Mastery (learning/achievement) and

Purpose (meaning and knowing why)

Gamification Typology Experiment

• Investigate variation in learner gamification profiles using Marczewski’s gamification typology as a model for motivation.

• Context. • Two 2nd year computing degree modules (68 students co-enrolled). Web and

games based topics.

• We created a virtual world, Reflex, for the students to access content and receive feedback. The 3D world was important to the gamification process.

• The teaching mode for the games module was chosen with gamification in mind, whereas the web module had a very traditional format.

Reflex

Four screen shots from Reflex. From top left in clockwise order: A view of the learning

areas, starter point with group league table, achievement table, and avatar selection tool.

Reflex System Architecture

Motivation for a Virtual World

• Offers richer opportunities for agency (embodiment) and situated learning. • A learners avatar and the world (over time) can become a representation of their

learning state.

• Gamification features utilising aspects such as exploration and socialising are more literal in a virtual world.

• A 3D space can topographically represent the relationship between learning content (difficult, progression etc.) and visually (and physically) present a pedagogical learning process. • Landscape provides guidance • Landscape supplies feedback • Learners can be tracked through virtual learning landscape and heat and trajectory

maps subsequently utilised for analysis

Mixed Methods Approach - Convergent Parallel Design Student preferences

– Ask students to complete a questionnaire designed to gauge their gamification preference on the basis of how they say they are motivated.

– Summarise and analyse student profiles. – Perform exploratory data analysis to attempt to uncover more complex typologies based on

statistical relationships between the gamification attributes of the learner profiles.

Student behaviour – Track actual student behaviour: actions and trajectories in the virtual world. – Summarise and analyse the effect of gamification on behaviour based on actions and

trajectories.

Preferences v Behaviour – Investigate how well student preferences map to actual behaviour. – Outcome from this analysis has the potential the recommendation (or at guidelines on) a

gamification typology model based on behaviours alone (ideally eliminating the need for a questionnaire).

Gamification Types (Marczewski’s Typology)

Marczewski’s mapping of gamification support features to user types

Gamification Features Used in Reflex

Feature Description Actions and Events

Badges Awarded for performance and

progress.

Monitor when awarded. How often are they checked?

Do learners persue elusive badges?

Points Accumulation of points for

leaderboards etc.

Monitor when awarded. Do learners check points

regularly? Do they strive to get maximum points?

Visible Status Displaying user

weekly/semester progress.

Monitor updates to progress. Do learners look at

breakdown often? Provision of a target system. Do user’s

discuss their visible status?

Leaderboards Rank individual and group

performance

Monitor changes in rank and correlated behaviour over

time. Do learners discuss/check rank?

Unlockable Content Prerequisite performance

markers for content unlocks

Monitor award of this content. Do learners discuss or

pursue such content? Do learners analyse what is

required to unlock this content?

Customisation Personalisation of world and

avatar

Monitor changes to avatar and world. Frequency of

changes. Discussion of changes.

Levels Avatar/world level progress

indicators

Monitor levelling up and behaviour monitoring

Gamification User Type Identification Questionnaire (GUTIQ) – Intrinsically Motivated

User Type Main

Gamification

Emphasis

GUTIQ Statements

Philanthropist Purpose I like to help people who are struggling with progress in learning

I like to contribute to module forums to share my knowledge with others

I like to volunteer my time to help maintain online communities

I do not like sharing knowledge that may give me an edge with my classmates

Achiever Mastery I enjoy taking learning courses purely because I want to

I tend to work at learning activities until I perfect them

Winning is more important than taking part

I like to display rewards I receive

Socializer Relatedness I use social networking on a regular basis

In social media, I enjoy watching/following people as opposed to talking to others

I have more people following me than people I follow

I enjoy sharing content with my friends/followers

Free Spirit Autonomy I enjoy creating custom pictures for my online profiles

I prefer freedom to explore rather than a story when playing a game

I like to create and upload content to sites like Instagram, YouTube and Pinterest

If I found a bug in a game that let me win I would exploit it rather than report it

Gamification User Type Identification Questionnaire (GUTIQ) – Extrinsically Motivated User Type Gamification

Emphasis

GUTIQ Statements

Self-Seeker Egotistical

Reward Focus

I enjoy receiving experience points and gaining new levels in games

I enjoy having badges/avatars to display as status symbols in games

I like to use leaderboards to see how I’m performing against others

I work in groups in games purely to get rewards, not to build friendships

Consumer Attainment

and

Acquisition

I like to display badges I receive on my player profile

I enjoy playing sequels to games that reward me for playing previous games in the series

I prefer to only use a system when I can clearly see its benefits

I don’t enjoy learning when there are no rewards available

Networker Social Network

Building. Self-

Centered World

View

I enjoy playing as part of a group in gameplay

I like being identified as a member of a certain group based on its competitive reputation

I don’t enjoy playing online game modes on my own

I enjoy working on team based objectives whilst playing games

Exploiter Short-cuts and

Using Others

I like to try and find exploitable loopholes in a game

I don’t see any good reason to report a bug provided it doesn’t hamper my progress

I will engage with team based game interactions if it provides me with a reward

I like to use cheat codes to further my progress in games

Descriptive Statistics of GUTIQ Data

Descriptive Statistics of GUTIQ Data

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Mean 51.471 57.794 60.735 52.941 64.265 58.235 61.912 49.412

Median 50 60 60 50 70 60 60 50

Mode 40 60 60 50 80 60 60 60

Standard Deviation 23.197 19.382 18.634 22.729 25.761 22.655 20.389 24.304

Sample Variance 538.10 375.66 347.21 516.59 663.63 513.26 415.69 590.69

Kurtosis -0.008 -0.479 0.736 -0.682 0.323 -0.010 1.539 -0.099

Skewness 0.060 0.246 -0.067 0.355 -0.733 -0.330 -0.637 -0.148

Range 100 80 100 90 100 100 100 100

Confidence Level(95%) 5.615 4.691 4.510 5.502 6.235 5.484 4.935 5.883

Descriptive Statistics of GUTIQ Data

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Mean 51.471 57.794 60.735 52.941 64.265 58.235 61.912 49.412

Median 50 60 60 50 70 60 60 50

Mode 40 60 60 50 80 60 60 60

Standard Deviation 23.197 19.382 18.634 22.729 25.761 22.655 20.389 24.304

Sample Variance 538.10 375.66 347.21 516.59 663.63 513.26 415.69 590.69

Kurtosis -0.008 -0.479 0.736 -0.682 0.323 -0.010 1.539 -0.099

Skewness 0.060 0.246 -0.067 0.355 -0.733 -0.330 -0.637 -0.148

Range 100 80 100 90 100 100 100 100

Confidence Level(95%) 5.615 4.691 4.510 5.502 6.235 5.484 4.935 5.883

Descriptive Statistics of GUTIQ Data

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Mean 51.471 57.794 60.735 52.941 64.265 58.235 61.912 49.412

Median 50 60 60 50 70 60 60 50

Mode 40 60 60 50 80 60 60 60

Standard Deviation 23.197 19.382 18.634 22.729 25.761 22.655 20.389 24.304

Sample Variance 538.10 375.66 347.21 516.59 663.63 513.26 415.69 590.69

Kurtosis -0.008 -0.479 0.736 -0.682 0.323 -0.010 1.539 -0.099

Skewness 0.060 0.246 -0.067 0.355 -0.733 -0.330 -0.637 -0.148

Range 100 80 100 90 100 100 100 100

Confidence Level(95%) 5.615 4.691 4.510 5.502 6.235 5.484 4.935 5.883

Descriptive Statistics of GUTIQ Data

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Mean 51.471 57.794 60.735 52.941 64.265 58.235 61.912 49.412

Median 50 60 60 50 70 60 60 50

Mode 40 60 60 50 80 60 60 60

Standard Deviation 23.197 19.382 18.634 22.729 25.761 22.655 20.389 24.304

Sample Variance 538.10 375.66 347.21 516.59 663.63 513.26 415.69 590.69

Kurtosis -0.008 -0.479 0.736 -0.682 0.323 -0.010 1.539 -0.099

Skewness 0.060 0.246 -0.067 0.355 -0.733 -0.330 -0.637 -0.148

Range 100 80 100 90 100 100 100 100

Confidence Level(95%) 5.615 4.691 4.510 5.502 6.235 5.484 4.935 5.883

GUTIQ Typology Response Correlation Matrix

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Philanthropist 1.000 0.455 0.208 0.334 0.159 0.232 0.370 0.105

Achiever 0.455 1.000 0.343 0.310 0.354 0.494 0.468 0.023

Socialiser 0.208 0.343 1.000 0.559 0.345 0.332 0.153 0.130

Free Spirit 0.334 0.310 0.559 1.000 0.185 0.364 0.242 0.298

Self-Seeker 0.159 0.354 0.345 0.185 1.000 0.675 0.314 0.185

Consumer 0.232 0.494 0.332 0.364 0.675 1.000 0.547 0.266

Networker 0.370 0.468 0.153 0.242 0.314 0.547 1.000 0.069

Exploiter 0.105 0.023 0.130 0.298 0.185 0.266 0.069 1.000

Principal Component Analysis of Typologies

GUTIQ Typology PC1 PC2 PC3 PC4 CP5 PC6 PC7 PC8

Philanthropist -0.451 -0.401 -0.121 -0.298 0.723

Achiever -0.308 -0.184 0.526 -0.374 0.504 0.412 0.168

Socialiser -0.181 0.557 -0.277 -0.662 0.105 -0.260 0.248

Free Spirit -0.354 0.464 0.340 -0.347 0.133 -0.575 -0.272

Self Seeker -0.364 -0.418 -0.246 -0.628 0.171 0.390 -0.238

Consumer -0.400 -0.313 0.206 0.189 -0.789 -0.162

Networker -0.369 -0.534 0.240 0.411 0.303 -0.503

Exploiter -0.338 0.396 0.206 0.544 0.595 0.193

Exploratory Factor Analysis of GUTIQ

GUTIQ Attribute Factor 1 Factor 2 Factor 3

Philanthropist 0.60

Achiever 0.32 0.72

Socialiser 0.49

Free Spirit 0.96

Self-Seeker 0.65

Consumer 0.93

Networker 0.44 0.47

Exploiter 0.32

3D Scatterplot of Exploratory Factor Analysis Projections

K-Means Clustering of GUTIQ Responses C

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1 19 2,12,17,29,30,40, 41,50,55,61,65,71,85,87,93,101,102,110,111 50.53 61.05 60.00 47.37 74.74 65.79 64.74 48.95

2 2 44,81 10.00 35.00 60.00 40.00 5.00 5.00 0.00 5.00

3 2 94,106 85.00 90.00 75.00 60.00 100.00 100.00 100.00 0.00

4 2 10,18 70.00 70.00 50.00 45.00 30.00 25.00 70.00 0.00

5 1 31 60.00 60.00 40.00 50.00 0.00 30.00 60.00 100.00

6 3 23,27,63 16.67 53.33 50.00 40.00 30.00 56.67 63.33 30.00

7 6 19,59,62,80,105, 115 48.33 65.00 75.00 90.00 90.00 80.00 56.67 75.00

8 15 4,11,22,24,42,54,57,68,69,70,88, 107,109,114,116 43.33 38.00 56.00 43.33 60.67 45.33 52.00 50.00

9 3 25,26,82 46.67 36.67 26.67 20.00 46.67 30.00 56.67 36.67

10 2 76,84 85.00 90.00 65.00 65.00 100.00 95.00 100.00 90.00

11 3 37,60,72 33.33 76.67 83.33 56.67 93.33 73.33 86.67 33.33

12 1 67 40.00 30.00 30.00 80.00 30.00 80.00 90.00 100.00

13 7 3,49,73,74,78,92,98 84.29 70.00 80.00 81.43 52.86 58.57 70.00 58.57

14 2 39,112 60.00 80.00 45.00 20.00 60.00 50.00 30.00 65.00

Relationship between Gamification Profile and Behaviour • We are still working on the analysis of the tracking but initial

indications are that most clusters are reasonably well correlated between GUTIQ responses and behavior.

• An exception are the 16 learners in clusters 11 and 12 displayed unexpected levels of activity.

Average Number of Resources used Per Area

0

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1 2 3 5 6 7 8 9 10 11 12 13 14

Number of Resources Used

Web Prepare Web Learn Web Test Games Prepare Games Learn Games Test

Cluster Number

Conclusion

• We have used Marczewski’s Typology as the basis for investigating variation in motivating factors between learners with a virtual world. • We have proposed the use of a questionnaire, GUTIQ, to acquire the

gamification type of learners

• There is some evidence of interesting variation between learner gamification type and good correlation with behavior.

• It was also found that behavior of each gamification type was consistent between two separate learning modules.

• Further investigation is required to analyse tracked behaviour and to examine the relationship between gamification attributes, and to build a more robust typology.