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Hero.Coli : a Video Game Empowering Stealth Learning of Synthetic Biology : a Continuous Analytics-Driven Game Design Approach Raphaël Goujet

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Hero.coli : a video game empowering stealth learning of synthetic biology : a continuous analytics-driven game design approach Raphaël Goujet To cite this version: Raphaël Goujet. Hero.coli : a video game empowering stealth learning of synthetic biology : a con- tinuous analytics-driven game design approach. Education. Université Sorbonne Paris Cité, 2018. English. NNT : 2018USPCB175. tel-02524484 HAL Id: tel-02524484 https://tel.archives-ouvertes.fr/tel-02524484 Submitted on 30 Mar 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. UNIVERSITÉ PARIS DESCARTES Frontières du Vivant Doctoral School 474 - New Frontiers PhD Program Inserm U1001 - Center for Research and Interdisciplinarity Hero.coli: a video game empowering stealth learning of synthetic biology a continuous analytics-driven game design approach By Raphaël Goujet Interdisciplinary biology PhD thesis Directed by Ariel Lindner Publicly presented and defended on 30 November 2018 In front of a jury comprising: Mr Sébastien GEORGE Reviewer Le Mans Université Mr Jean-Marc LABAT Reviewer Université Pierre et Marie Curie Mrs Patricia MARZIN-JANVIER Examiner Université de Bretagne Occidentale Mrs Melanie STEGMAN Examiner Molecular Jig Games, LLC Mr Ariel LINDNER Supervisor Université Paris-Descartes 2 Contents Contents 3 List of Figures 7 Synopsis 11 I Introduction 15 1 Video games and Learning 17 1.1 Generalities about video games . 17 1.1.1 Game . 17 1.1.2 Gameplay and Gameplay Loops . 19 1.2 Digital game-based learning . 22 1.2.1 The need for game-based learning . 22 1.2.2 Applications of digital game-based learning . 23 1.2.3 Other Serious Games and GWAPs . 28 1.2.4 Closely-related genres . 30 1.3 Learning strategies, assessment, and outcomes . 34 1.3.1 Learning strategies . 34 1.3.2 Learning assessment . 34 1.3.3 Learning outcomes and issues . 36 2 Synthetic biology 39 2.1 Definition . 39 2.1.1 The Central Dogma . 40 2.2 Principles . 42 2.2.1 Decoupling . 42 2.2.2 Standardization . 42 2.2.3 Abstraction . 47 2.3 Limitations of synthetic biology . 56 2.3.1 Complexity . 56 2.3.2 Variation . 56 2.3.3 Evolution . 57 2.4 Uses of synthetic biology . 57 3 4 CONTENTS 2.5 Dissemination . 59 2.5.1 Synthetic biology in popular culture . 60 2.5.2 Synthetic biology in academic training . 64 2.5.3 Synthetic biology in popular science on the Internet . 65 3 Questions, approaches, and objectives 71 3.1 Research questions . 71 3.2 Outlining the remaining chapters . 73 II Experimental Setup 75 4 Design and Implementation of Hero.Coli 77 4.1 Genesis . 77 4.1.1 History of the CRI . 77 4.1.2 Synthetic biology . 78 4.1.3 Education . 78 4.1.4 The Digital Synthetic Biology Club . 78 4.1.5 Citizen Cyberlab . 79 4.2 Hero.Coli 1.12: a proof-of-concept . 81 4.2.1 First design of Hero.Coli . 81 4.2.2 Simulator . 92 4.2.3 Technical implementation . 93 4.2.4 Playtesting and accolades . 96 4.3 Repurposing into a new research project: Adaptations . 99 4.3.1 Accessibility . 99 4.3.2 Metrics and analytics . 100 4.3.3 Academic use . 103 4.3.4 Game design . 104 4.3.5 Tutorial . 105 4.3.6 Interface . 106 4.3.7 Simulator . 107 III Data gathering and analysis 109 5 Data gathering campaigns 111 5.1 Survey methodology . 111 5.2 Online experiments . 114 5.3 In-class experiments . 115 5.4 Final 2018 experiment at Cité des Sciences . 119 5.4.1 Objectives . 120 5.4.2 Protocol . 120 5.4.3 Implementation . 121 CONTENTS 5 6 Data analysis 123 6.1 Exploratory analysis . 123 6.1.1 Feedbacks from the participants . 123 6.1.2 Filtering the data . 128 6.1.3 Correlations in survey answers . 129 6.1.4 Correlations between tracking data and surveys . 132 6.1.5 Surveys: Analysis of the cohort . 136 6.2 Detailed analysis . 139 6.2.1 Threshold effect: learning and checkpoints . 139 6.2.2 Comparison of the pretest and posttest pairs . 143 6.2.3 Surveys and game metrics: data mining . 155 6.2.4 Comparison of phase 1 and phase 2 . 156 6.2.5 Limitations . 158 7 Conclusions and prospectives 159 7.1 Conclusions . 159 7.1.1 Research questions . 159 7.1.2 Usefulness, Usability, Acceptability . 162 7.2 Prospectives . 162 A Annex 1: tables 179 B Annex 2: graphs 185 B.1 Figures referenced in section 6.2.2 . 186 B.2 Figures referenced in sections 6.1.3 and 6.1.4 . 187 C Annex 3: surveys 193 C.1 1.12 . 194 C.2 1.50 - 2016-06 to 2017-06 . 198 C.3 1.52 - 2017-06 to 2018-03-22 . 202 C.4 1.52.2 / 1.60 / 1.61 - 2018-03-23 onwards . 211 6 CONTENTS List of Figures 1.1 Caillois’ Ludus and Paidia . 18 1.2 Interaction cycle involving a player and a videogame . 19 1.3 A representation of the state of flow . 21 1.4 Literate world population 1800-2014 . 22 1.5 The Logo Turtle . 23 1.6 Venn diagram of video games according to Tang and Hanneghan (2007) 24 1.7 Venn diagram of video games according to Djaouti, Alvarez, and J.-P. Jessel (2011) . 24 1.8 Screenshot of CellCraft ......................... 26 1.9 A Biotic Game device developed by the Riedel-Kruse lab . 27 1.10 Typical depiction of the Forgetting Curve . 33 2.1 Consequences of the Central Dogma of molecular biology: transcrip- tion and translation . 41 2.2 Registry of Standard Biological Parts: brick functions . 43 2.3 BioBricks in the transcription process . 44 2.4 The Hill function, typical gene expression from an inducible system 45 2.5 SBOL Visual: glyphs representing functional DNA sequences . 48 2.6 BioBrick sequence producing GFP. 49 2.7 Cell mechanisms modeled in Karr’s model . 53 2.8 Model developed by Wortel et al. 54 2.9 Model developed by Weiße et al. 55 2.10 The Carlson Curve as of 2017 . 63 2.11 A screenshot of the MOOC IGEM High School page about BioBricks 67 2.12 Examples of YouTube videos of SB popularization . 68 4.1 Genetic devices as abilities (first gameplay level) . 84 4.2 Genetic devices as independent BioBrick sequences (second game- play level) . 84 4.3 Genetic devices as interacting BioBrick sequences (third gameplay level) . 84 4.4 Hero.Coli 1.12: screenshot of an action phase . 87 4.5 Hero.Coli 1.12: crafting interface . 87 4.6 Hero.Coli 1.12: inventory and equipment interfaces, and HUD . 88 7 8 LIST OF FIGURES 4.7 The first two messages displayed at the beginning of the game in the 1.12 version . 89 4.8 Device tutorial in the 1.12 version . 90 4.9 RBS BioBrick tutorial in the 1.12 version . 90 4.10 Map of Hero.Coli 1.12 with highlighted checkpoints . 91 4.11 Screenshot of a diff tool ........................ 96 4.12 Map of the game with highlighted path, checkpoints, and chapters . 104 4.13 Hero.Coli 1.50: screenshot of an action phase . 107 4.14 Hero.Coli 1.50: crafting interface . 108 5.1 Survey: randomized vertical position for possible answers . 113 5.2 Survey: constant horizontal position for possible answers . 113 5.3 Results of question 16 - pretest . 116 5.4 Results of question 16 - posttest . 116 5.5 Hero.Coli 1.12: pretest answers to "Which biobrick controls what is produced by the genetic device?" . 117 5.6 Hero.Coli 1.12: posttest answers to "Which biobrick controls what is produced by the genetic device?" . 117 5.7 Hero.Coli 1.12: pretest answers to "Which biobrick controls only the efficiency - level of expression - of the genetic device?" . 118 5.8 Hero.Coli 1.12: posttest answers to "Which biobrick controls only the efficiency - level of expression - of the genetic device?" . 119 6.1 Map of the game with highlighted the two blocking puzzles . 125 6.2 Pipeline of exploitation of the data from experimental subjects . 128 6.3 Table of correlations of demographic features and interests against scores . 130 6.4 Table of correlations of participant demographic features against their curiosity, interests, and practice . 131 6.5 Table of correlations of enjoyment against participants’ characteristics131 6.6 Table of correlations of play times.
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