Gamification and Flow

Doctoral Dissertation

Creating The Flow:The Gamification Of Higher Education Courses

Martin Sillaots15.12.2016

Supervisors:Mauri Kaipainen

Kai Pata

Content• Introduction: [problem • objectives • questions]• Theory: [gamification • flow dimensions]• Research: [methods • cases]• Results: [game elements • flow • model]• Conclusions: [outcomes • limitations •

implications]

Introduction

[problem • objectives • research questions]

Problem

Learning is perceived as boring activity(Steinberg, Brown, & Dornbusch, 1997)

(Admiraal, Huizenga, Akkerman, & Dam, 2011)(Pekrun, Goetz, Daniels, Stupnisky, & Perry, 2010)

Solution

Active learning methodse.g. gamification

GamificationThe use of game elements in a non-gaming

environmentGame elements = game design elements (Deterding 2011) + gaming metaphors (Marczewski, 2013)

Purpose of Gamification

Involve participants and solve problems(Fitz-Walter, Tjondronegoro, & Wyeth, 2011)

(Kapp, 2012)

Involvement

The act of participating in something(Brown & Cairns, 2004; IJsselsteijn et al., 2007)

FlowOptimal experience in the level of mind and

body where the user becomes absorbed in the activity and senses a deep level of enjoyment

(Csikszentmihalyi, 1990)

How to use game elements for involving students?

How to measure involvement?

Research Objectives• Gamification of university level courses• Evaluation of the level of involvement• Finding causalities between game end flow

elements

Research QuestionsRQ1: How students value game elements?

How do students value the game elements in different type of university courses from the viewpoint of experiencing the flow in learning?

RQ2: Was the flow achieved?How does course context influence the successful application of game elements for experiencing the flow in learning?

RQ3: How game elements influence flow dimensions?How do different game elements affect the flow components?

Theoretical Background

[game elements • flow dimensions • instruments]

Game Elements

Any element that can be found in the game(Deterding, 2011)

Flow Dimensions• Clear goals• Clear feedback• Balance between challenges and skills• Control• Concentration• Action-awareness merging• Losing self-consciousness • Time transformation• Autotelic experience

(Csikszentmihalyi, 1990)

Flow Dimensions• Clear goals• Clear feedback• Balance between challenges and skills• Control• Concentration• Immersion

(Sweetser & Wyeth, 2005)

Instruments for Measuring the Flow• ESM: Experience Sampling Method

(Hektner, Schmidt, & Csikszentmihalyi, 2007)

• FSS: Flow State Scale (Jackson & Marsh, 1996)

• DFS: Dispositional Flow Scale (Jackson, Ford, Kimiecik, & Marsh, 2008)

• GameFlow (Sweetser & Wyeth, 2005)

• eGameFlow(Fu et al., 2009)

FlowAutotelic Experience

Skill-challengeBalance

UnambiguousFeedback

ClearGoals

Control

LosingSelf-consciousness

Timetransformation

Concentration

MergingAction-awareness

Research Methodology

[methods • process • game elements • courses] [data collection and analyze methods]

Design Based Research• Mixing existing theory with practice• Improve teaching practice• Focus on learning process

DBR Provide• New theories – RQ3: How game elements affect flow

dimensions?• Implementation of existing theories – gamified course

designs• Adjust the context – RQ2: How course context influence the

application of game elements and experiencing the flow?• Assess the design – RQ1: How students value the game

elements in courses design?(Edelson, 2002)

Instructional Design Theory• Domain theory - how to involve students? • Design framework - selection and

implementation of game elements in the course design

• Design methodology(Edelson, 2002)

Research Process

Game Elements

Achievements Actions Aesthetics Altruism Art Atmosphere Attitudes Autonomy Autotelic_experience

Avatar Badges Balance Big_Boss_Fight Challenges Characters Cheating Cognitive_needs Collaboration Communication Community Competences Competition

Concentration Control Creativity Culture Curiosity Decision_making Difficulty Dimensions

Discovering Emotional_needs Engagement Engrossment Enjoyment Environmental_needs

Ethics Events Extrinsic_motivation Extrinsic_reward Fairness Fantasy Feedback Fight Flow Followership Fun Gameplay Goals Identity Immersion Importance Interaction

Intrinsic_motivation Intrinsic_reward Involvement Knowledge Levels Loosing self

Loyalty Luck Meaningfulness Merging_action-awareness Messages Motivation Narrative NPC

Non_essential Opponent Performance Player Points Progress Psychological_needs Recruiting Relatedness Relationship Reputation Resource acquisition

Reward Risk Roles Rules Scoreboard Self_Expressions Skills Social_needs Socialization

Sound Space Stile Story Support Surprise Teams Teamwork Time Time_Transformation Turns Utility Variety

Voluntariness World

Selected Game Elements• Goals• Feedback• Characters (avatars)• Risk (luck)• Extrinsic reward (points, scoreboard, levels)• Collaboration• Competition• Interaction

Case Courses

5 courses x 2

Case Courses• Research Methods

– Research Seminar 1 (bachelor)– Research Seminar 2 (bachelor)– Research Methods (masters)

• Computer Game Design– Computer Games (bachelor)– Game Design (masters)

Reason for Gamification• Research Methods

– Many students experience research methods as dry and boring (Winn, 1995)

– Gamification for achieving involvement

• Game Design– Game like course design supports content delivery

(Sheldon, 2011)

Case Courses

Course Design

Gamified Course Design• Course objectives• Avatar design• Challenges

– Debates– Presentations– RND– Quizzes– Big Boss

• Collecting points• Scoreboard• Levels• Instant feedback• Game vocabulary

Data Collection

Data Collection Methods• Online Questionnaire• Observation diary• Group interview

Online Questionnaire• Based on model of GameFlow

(Sweetser & Wyeth, 2005)

• + questions about game elements– Pilot: 17 questions, 4 point scale– 1st iteration: 47 questions, 4 point interval scale– 2nd iteration: 45 questions, 5 point interval scale

• 198 answers (75%)

Data Analysis• Data preparation• Descriptive statistics• Validity and reliability evaluation• Compound variables• Correlation analysis• Path analysis

Validity and Reliability • Construct validity: multiple data sources• Internal validity: in and cross case comparison• External validity: referencing to similar case studies• Reliability: triangulation of different researchers• Reliability of the questionnaire: Cronbach’s Alpha• Internal consistency of the data: 2 independent samples T-test• Retention: data accessible in Internet

Compound Variables• Character• Luck• Extrinsic reward• Collaboration• Competition• Interaction• Goals

• Feedback• Balance• Control• Concentration• Merging• Time transformation• Losing self

Path Analysis• Find causalities among game and flow elements• Iterative linear regression analysis• No constants• Independent variables with highest impact• Connection Strength: linear regression β weights• Model compatibility: regression R2 values(Garbin, n.d.; Olobatuyi, 2006)

Game Elements, Case Courses and Publications

Results

[elements • flow • model]

Feedback to Game ElementsRQ1: How do students value the game elements in different types of

university courses from the viewpoint of experiencing the flow at learning?

Game Elements in TotalTotal0.75

Game Elements in Details GD 13 GD 14 CG 13 CG 15 RS1 13 RS1 14 RS2 13 RS2 14 RM 13 RM 14 Total

Character 0.49 0.43 0.41 0.46 0.41 0.44 0.40 0.35 0.25 0.41

Luck 0.82 0.71 0.75 0.66 0.78 0.63 0.77 0.44 0.71 0.69

Reward 0.84 0.76 0.79 0.89 0.76 0.73 0.75 0.76 0.63 0.74 0.75

Collaboration 0.79 0.80 0.65 0.82 0.85 0.73 0.83 0.82 0.79 0.82 0.79

Competition 0.33 0.61 0.70 0.73 0.81 0.77 0.86 0.74 0.58 0.72 0.74

Interaction 0.93 0.96 0.89 0.85 0.79 0.83 0.81 0.69 0.82 0.85

Goals 0.90 0.94 0.82 0.94 0.91 0.96 0.92 0.94 0.83 0.92 0.91

Feedback 0.74 0.80 0.86 0.89 0.87 0.85 0.86 0.91 0.79 0.87 0.84

TOTAL 0.72 0.77 0.74 0.79 0.77 0.75 0.76 0.77 0.64 0.73 0.75

Achieving FlowRQ2: How does course context influence the successful application of

game elements for experiencing the flow in learning?

Achieving Flow in TotalTotal0.68

Achieving Flow in Details GD 13 GD 14 CG 13 CG 15 RS1 13 RS2 14 RS2 13 RS2 14 RM 13 RM 14 Total

Goals * 0.90 0.94 0.82 0.94 0.91 0.96 0.92 0.94 0.83 0.92 0.91

Feedback * 0.74 0.80 0.86 0.89 0.87 0.85 0.86 0.91 0.79 0.87 0.84

Balance 0.75 0.75 0.80 0.80 0.79 0.80 0.75 0.81 0.70 0.78 0.78

Control 0.75 0.74 0.67 0.87 0.70 0.73 0.65 0.74 0.60 0.77 0.72

Concentration 0.78 0.88 0.75 0.89 0.85 0.88 0.86 0.87 0.78 0.78 0.83

Losing Self 0.54 0.44 0.65 0.51 0.38 0.54 0.36 0.44 0.48 0.48

Merging 0.82 0.80 0.66 0.85 0.73 0.71 0.73 0.73 0.78 0.72 0.75

Time 0.70 0.44 0.77 0.74 0.63 0.83 0.62 0.53 0.66 0.65

TOTAL 0.82 0.72 0.55 0.78 0.64 0.63 0.68 0.63 0.65 0.66 0.68

Model of Game and Flow Elements

RQ3: How do different game elements affect the flow components?

Path analysisIterative linear Regression Analysis

Immersion =Merge + Time + Self

Control


R2 = 0.949

0.510

Concentration

0.470

Control


R2 = 0.949

0.470

Concentration

SPSS: linear regression analysis

0.510

Control


R2 = 0.949

0.470

Concentration

Estimations of model compatibility:regression analysis R2 values

0.510

Control


R2 = 0.949

0.470

Concentration

Strength of the connection: beta weights

0.510

Control


R2 = 0.949

0.470

Concentration

Immersion = 0.5 x Control + 0.5 x Concentration

Immersion can not be achieved without concentration and control

0.510

Balance GoalsFeedback

ControlR2 = 0.973


R2 = 0.949

0.470

0.4930.3170.564

0.612

0.186

ConcentrationR2 = 0.981

0.510


ControlR2 = 0.973


R2 = 0.949


• For control feedback and clear goals are needed– e.g. setting or accepting the goals, tracking them– e.g. feedback provides control over the process

0.470 0.510

0.4930.3170.564

0.612

0.186


ControlR2 = 0.973


R2 = 0.949


• For concentration balance and clear goals are needed– e.g. concentration is highest if the challenges are little bit above

the level skills (balance)– e.g. concentration is easier when goals are clear

0.470 0.510

0.4930.3170.564

0.612

0.186

BalanceR2 = 0.984

GoalsR2 = 0.980

FeedbackR2 = 0.976

ControlR2 = 0.973


R2 = 0.949

CollaborationR2 = 0.963

Competition

RewardR2 = 0.963

Luck

InteractionR2 = 0.964

< 0.7620.426 >

0.231 0.167

< 0.4080.605 >

0.268< 0.5340.544 >0.206

0.249

0.1690.247

< 0.500

0.465 >


0.470 0.510

0.4930.3170.564

0.612

0.186

Discussion …• Feedback depends on balance and interaction

– e.g. difficulty (balance) is important feedback information– e.g. interaction provides feedback

• Balance depends on feedback, goals and reward– e.g. feedback enables balancing– e.g. it’s challenging (part of balance) to achieve the goals– e.g. balanced scoring system (reward)

• Clear goals depend on balance and collaboration– e.g. challenges (part of balance) have goals– e.g. defining joint objectives for group work (collaboration)

• Interaction is created through collaboration, competition and luck– e.g. collaboration and competition are type of interaction– e.g. luck (randomly pointed tasks) can trigger interaction

• Extrinsic reward is affected by collaboration, interaction and competition– e.g. social acceptance (extrinsic reward) is a part of collaboration– e.g. scoreboard (competition) is extrinsically rewarding

• Collaboration is affected by the reward and interaction– e.g. possibility to earn points (reward) motivated to participate in

teamwork– e.g. no collaboration without interaction

… Discussion

Conclusions

[outcomes • limitations • further studies • implications]

Main Outcomes• Map of game elements• Gamified courses• Achieving moderate level of flow• Refined model of flow• Conceptual model of game elements

FlowAutotelic Experience

Skill-challengeBalance

Control

LosingSelf-consciousness

Timetransformation

Concentration

MergingAction-awareness

ClearGoals

UnambiguousFeedback

Refined Model of Flow

Limitations• Case study• Limited number of game elements• Focus on involvement

Further Study Needed• Classification of game elements• Implementation of complex game elements• Periodical student feedback (ESM)• Influences on learning results

Implications • Classroom: for instructional designers• Games: game designers

– Engineering of Flow– Involvement evaluation

[email protected]

Link to the thesishttp://tinyurl.com/gamificationflow

Gamification and Flow

Education

Transcript of Gamification and Flow