Gamification and Flow
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Creating the Flow: Gamification of Higher Education Courses
![Content
• Introduction: [problem • objectives • questions]
• Theory: [gamification • flow dimensions]
• Research: [methods • cases]
• Results: [game elements • flow • model]
• Conclusions: [outcomes • limitations •
implications]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Gamification and Flow
- 1. Doctoral Dissertation Creating The Flow: The Gamification Of Higher Education Courses Martin Sillaots 15.12.2016 Supervisors: Mauri Kaipainen Kai Pata
- 2. Content • Introduction: [problem • objectives • questions] • Theory: [gamification • flow dimensions] • Research: [methods • cases] • Results: [game elements • flow • model] • Conclusions: [outcomes • limitations • implications]
- 3. Introduction [problem • objectives • research questions]
- 4. Problem Learning is perceived as boring activity (Steinberg, Brown, & Dornbusch, 1997) (Admiraal, Huizenga, Akkerman, & Dam, 2011) (Pekrun, Goetz, Daniels, Stupnisky, & Perry, 2010)
- 5. Solution Active learning methods e.g. gamification
- 6. Gamification The use of game elements in a non-gaming environment Game elements = game design elements (Deterding 2011) + gaming metaphors (Marczewski, 2013)
- 7. Purpose of Gamification Involve participants and solve problems (Fitz-Walter, Tjondronegoro, & Wyeth, 2011) (Kapp, 2012)
- 8. Involvement The act of participating in something (Brown & Cairns, 2004; IJsselsteijn et al., 2007)
- 9. Flow Optimal 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)
- 10. How to use game elements for involving students? How to measure involvement?
- 11. Research Objectives • Gamification of university level courses • Evaluation of the level of involvement • Finding causalities between game end flow elements
- 12. Research Questions RQ1: 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?
- 13. Theoretical Background [game elements • flow dimensions • instruments]
- 14. Game Elements Any element that can be found in the game (Deterding, 2011)
- 15. 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)
- 16. Flow Dimensions • Clear goals • Clear feedback • Balance between challenges and skills • Control • Concentration • Immersion (Sweetser & Wyeth, 2005)
- 17. 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)
- 19. Research Methodology [methods • process • game elements • courses] [data collection and analyze methods]
- 20. Design Based Research • Mixing existing theory with practice • Improve teaching practice • Focus on learning process
- 21. 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)
- 22. 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)
- 23. Research Process
- 24. Game Elements
- 25. 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_rewardFairness 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
- 28. Selected Game Elements • Goals • Feedback • Characters (avatars) • Risk (luck) • Extrinsic reward (points, scoreboard, levels) • Collaboration • Competition • Interaction
- 29. Case Courses 5 courses x 2
- 30. Case Courses • Research Methods – Research Seminar 1 (bachelor) – Research Seminar 2 (bachelor) – Research Methods (masters) • Computer Game Design – Computer Games (bachelor) – Game Design (masters)
- 31. 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)
- 32. Case Courses
- 33. Course Design
- 34. Gamified Course Design • Course objectives • Avatar design • Challenges – Debates – Presentations – RND – Quizzes – Big Boss • Collecting points • Scoreboard • Levels • Instant feedback • Game vocabulary
- 35. Data Collection
- 36. Data Collection Methods • Online Questionnaire • Observation diary • Group interview
- 37. 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%)
- 38. Data Analysis • Data preparation • Descriptive statistics • Validity and reliability evaluation • Compound variables • Correlation analysis • Path analysis
- 39. 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
- 40. Compound Variables • Character • Luck • Extrinsic reward • Collaboration • Competition • Interaction • Goals • Feedback • Balance • Control • Concentration • Merging • Time transformation • Losing self
- 41. 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)
- 42. Game Elements, Case Courses and Publications
- 43. Results [elements • flow • model]
- 44. Feedback to Game Elements RQ1: How do students value the game elements in different types of university courses from the viewpoint of experiencing the flow at learning?
- 45. Game Elements in Total NO YESRather No So So 0 0.2 0.4 0.6 YESRather Yes 0.8 1 Total 0.75
- 46. 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
- 47. Achieving Flow RQ2: How does course context influence the successful application of game elements for experiencing the flow in learning?
- 48. Achieving Flow in Total NO YESRather No So So 0 0.2 0.4 0.6 YESRather Yes 0.8 1 Total 0.68
- 49. 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
- 50. Model of Game and Flow Elements RQ3: How do different game elements affect the flow components? Path analysis Iterative linear Regression Analysis
- 51. Immersion = Merge + Time + Self
- 52. Control Immersion = Merge + Time + Self R2 = 0.949 Concentration
- 53. Control Immersion = Merge + Time + Self R2 = 0.949 Concentration SPSS: linear regression analysis
- 54. Control Immersion = Merge + Time + Self R2 = 0.949 Concentration Estimations of model compatibility: regression analysis R2 values
- 55. Control Immersion = Merge + Time + Self R2 = 0.949 Concentration Strength of the connection: beta weights
- 56. Control Immersion = Merge + Time + Self R2 = 0.949 Concentration Immersion = 0.5 x Control + 0.5 x Concentration Immersion can not be achieved without concentration and control
- 57. Balance GoalsFeedback Control R2 = 0.973 Immersion = Merge + Time + Self R2 = 0.949 Concentration R2 = 0.981
- 58. Balance GoalsFeedback Control R2 = 0.973 Immersion = Merge + Time + Self R2 = 0.949 Concentration R2 = 0.981 • 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
- 59. Balance GoalsFeedback Control R2 = 0.973 Immersion = Merge + Time + Self R2 = 0.949 Concentration R2 = 0.981 • 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
- 60. Balance R2 = 0.984 Goals R2 = 0.980 Feedback R2 = 0.976 Control R2 = 0.973 Immersion = Merge + Time + Self R2 = 0.949 Collaboration R2 = 0.963 Competition Reward R2 = 0.963 Luck Interaction R2 = 0.964 < 0.762 0.426 > 0.231 0.167 < 0.408 0.605 > 0.268 0.206 0.249 0.247 Concentration R2 = 0.981
- 61. 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)
- 62. • 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
- 63. Conclusions [outcomes • limitations • further studies • implications]
- 64. Main Outcomes • Map of game elements • Gamified courses • Achieving moderate level of flow • Refined model of flow • Conceptual model of game elements
- 67. Limitations • Case study • Limited number of game elements • Focus on involvement
- 68. Further Study Needed • Classification of game elements • Implementation of complex game elements • Periodical student feedback (ESM) • Influences on learning results
- 69. Implications • Classroom: for instructional designers • Games: game designers – Engineering of Flow – Involvement evaluation
- 70. martin.sillaots@tlu.ee Link to the thesis http://tinyurl.com/gamificationflow
Editor's Notes
- Thank you for the introduction Dear chairman and members of the defense committee Dear opponents and supervisors Dear colleagues and friends This is a great honor to introduce you the content of my doctoral studies.
- My presentation is divided into following sections: First I introduce the needs and objectives of the study Secondly I introduce the theoretical background of the study. Then follows shot overview about research methods More time will be spent on research results Presentation ends with the conclusions
- Lets begin with the introduction.
- Presentation based teaching is dominating Learners are mostly passive observers Reason Online media Multimedia Games Traditional teaching methods are not engaging enough
- Methods that increase students involvement and motivation Gamification is one possibility
- Metaphors = Game like thinking and game emotions
- Gamification can be used in order to achieve involvement among students and solve problems
- Generally it describes a person’s concern and curiosity about something or describes the sharing of activities of a group In the best case students concentrate on the task in hand so deeply that they lose the sense of time and stop worrying about other things -> Flow
- The theory of flow provides a general structure that is suitable for summarizing the aspects of engagement (Sweetser & Wyeth, 2005).
- 2 Involving them in the level where they feel the flow
- Flow Dimensions - aspects or properties that are required for creating an enjoyable experience Autotelic experience - doing something for its own sake Sometimes it is difficult to distinguish between merging action-awareness, losing self and time. Some researchers combine and present them with the single element – immersion
- Sometimes it is difficult to distinguish between merging action-awareness, losing self and time. Some researchers combine and present them with the single element – immersion
- Different instruments exists how to measure the flow. In general they ask questions about 8 – 9 flow dimensions They all calculate the flow as a total from all dimensions. Flow as a total value from all dimensions can generate artificially high results. e.g. goals are clear but the merging does not take place. Some of the flow dimensions seam to be enabling factors Some dimensions seem to be evidences of flow ESM – periodical (balance) FSS – end (total of 9) DFS – end (mostly total 9, some based on evidences – no consensus) GF – end + immersion, social (total 8) eGF – end + learning (total 8)
- Model of Flow Causal relationships between flow dimensions causalities mentioned in the literature No consensus
- And Instructional design [design theories that provide guidelines for helping people to learn and develop Mixed method DBR: learning results AND support learning process
- [SKIP] … elements: 1. Domain theory [theoretically justified solutions for problems in the learning domain] - Selected domain theory – gamification. 2. Design framework [design aspects that provide a solution to the problem] 3. Design methodology [DBR process – contains guidelines for the process, not for the result]
- 2012 - 2016
- Literature review – content analysis Most frequently used Game elements - interaction - goals - levels - rewards
- Network analysis - For describing the connections and for finding the central elements - Challenges
- Concept mapping for clarifying the diagram – to clarify central elements, and connections
- Gamification of 5 courses (10 cases) from 2 different contexts
- [SKIP]
- Game Flow because it is designed for measuring the flow from game-like experiences Results from different iterations were converted into percentages in order to make them comparable with each other
- Preparation - same scale, empty fields and rows, missing values - mean Descriptive – mean, SD. Flow from 3 dimensions (Time, Self, Merge). T-test (the influence of the context)
- [SKIP] Cronbach’s Alpha internal consistency of the collected data if the alpha is bigger then 0,7 then internal consistency of the data is high Alpha is higher if the test item intercorrelation is high – if all items measure the same construct T-test comparing means of randomly formed groups for every question. It was tested whether randomly generated groups would differ significantly Significant differences could indicate inconsistency of collected data None of the variables generated two-tailed p-values smaller then 0.05. differences between randomly generated group means are statistically insignificant and data internal consistency is high
- [SKIP] 45 single questions were combined in to 14 (12) compound variables Means
- No constant Independent variables with highest impact
- Total outcome was rather positive
- - Character - Used only for safe names, Not integrated with other game elements - Luck - No equal chance, Not Fair. Explain, other options ~ Reward - motivating ~ Competition – controversial thought + Collaboration – mostly OK, In one case CG 13 lot of problems + Feedback – no game without feedback (differ from class) + Interaction – student Presentations, Debates, quizzes – engagement + Goals – no difference between games and courses Lowest RM 13 – not well explained the meaning of RND and competition
- + Balance – sufficient effort, difficulty increased + Control – felt control + Concentration – easy to concentrate + Merging – Sufficiently high - Loosing Self - Not so deep immersion – in non game conditions it is difficult to achieve ~ Time - Not so deep but time was passing faster Total – average from: Time + Self + Merge Lowest in CG13 – teamwork, physical classroom, …
- Iteration 1: One by one every flow dimension was used as a dependent variable, rest of the flow elements as independent variables Finding main outcome flow element
- Iteration 2: Main outcome flow dimension was used as a dependent variable, all others as independent variables Finding flow enabling factors
- Strength of the connection: beta weights
- Iteration 3: Every enabling factor was used as an dependent variable, all others as independent variables Finding second level enabling factors
- Iteration 4: Every second level enabling factor was used as dependent variable, all other flow and game elements as independent variables Finding connections between flow dimensions and game elements 2-directional connections
- Most important game element – challenge Gamification mostly perceived well – except Avatar Flow – merge OK, Time, Self NOT
- Based on literature and empirical data.
- Concept map of Came and flow elements
- outcomes may be influenced by the nature of the course or by the skills and knowledge of the teacher Broader generalizations can’t be made Effect on learning results was not studied
- ESM – Experience Sampling Method
- Where higher level of involvement is desired:
- Dear defense committee – thank you for interesting questions Dear opponents – thank you for great debate Dear colleagues and friends – thank you for the support