Rising to the Challenge: An Emotion-Driven Approach Toward Adaptive Serious Games

  • Claudia SchraderEmail author
  • Julia Brich
  • Julian Frommel
  • Valentin Riemer
  • Katja Rogers


Serious games are steadily becoming a powerful tool for educational purposes as their challenging characteristics are suggested to make them particularly appealing to learn with. This challenging nature, however, comes at a price, namely, the need to maintain the optimal balance according to players’ emotional experiences. By focusing on players’ emotions as main player characteristic considered to be important for learning processes and performance, this chapter surveys empirical research and current game development that contributes to an emotion-adaptive framework for games. The goal of this chapter is to clarify the importance of continuously adjusting game characteristics to players’ emotional states. As the interaction between game characteristics and players’ emotions highlights the need for continuously assessing at what point gameplay becomes more or less positively or negatively affected, methods for emotion recognition are presented. A summary of adaptable game design elements as well as implementation methods for adaptivity are provided.


Adaptivity Adaptive games Emotion recognition Serious games Procedural content generation 



This work was conducted as part of the project “Serious Games—Skill Advancement Through Adaptive Systems”, funded by the Carl Zeiss Foundation, as well as “EffIS—Efficient and Interactive Studying” (FKZ: 160H21032), funded by the German Federal Ministry of Education and Research (BMBF).


  1. Andersen, E.: Optimizing adaptivity in educational games. In: Proceedings of the International Conference on the Foundations of Digital Games, pp. 279–281. ACM (2012)Google Scholar
  2. Andersen, E., Gulwani, S., Popovic, Z.: A trace-based framework for analyzing and synthesizing educational progressions. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 773–782. ACM (2013)Google Scholar
  3. Anolli, L., Mantovani, F., Confalonieri, L., Ascolese, A., Peveri, L.: Emotions in serious games: from experience to assessment. iJET 5 (SI3), 7–16 (2010)Google Scholar
  4. Åström, K.J., Wittenmark, B.: Adaptive Control. Addison-Wesley, Reading (1995)Google Scholar
  5. Azevedo, R., Witherspoon, A., Chauncey, A., Burkett, C., Fike, A.: MetaTutor: a MetaCognitive tool for enhancing self-regulated learning. In: 2009 AAAI Fall Symposium Series (2009)Google Scholar
  6. Banavar, G., Bernstein, A.: Software infrastructure and design challenges for ubiquitous computing applications. Commun. ACM 45 (12), 92–96 (2002)CrossRefGoogle Scholar
  7. Barab, S., Arici, A., Jackson, C.: Eat your vegetables and do your homework: a design-based investigation of enjoyment and meaning in learning. Educ. Technol. 65, 15–21 (2005)Google Scholar
  8. Becker, K., Parker, J.R.: The Guide to Computer Simulations and Games. John Wiley & Sons, Indianapolis (2011)Google Scholar
  9. Bendel, O., Hauske, S.: E-Learning: Das Wörterbuch (in German). Sauerländer Verlage, Oberentfelden, (in German) (2004)Google Scholar
  10. Bianchi-Berthouze, N.: Understanding the role of body movement in player engagement. Hum. Comput. Interact. 28, 40–75 (2013)Google Scholar
  11. Bianchi-Berthouze, N., Cairns, P., Cox, A., Jennett, C., Kim, W.W.: On posture as a modality for expressing and recognizing emotions. In: Emotion and HCI Workshop at BCS HCI London (2006)Google Scholar
  12. Breuer, J.S., Bente, G.: Why so serious? On the relation of serious games and learning. Eludamos J. Comput. Game Cult. 4 (1), 7–24 (2010)Google Scholar
  13. Brich, J., Rogers, K., Frommel, J., Weidhaas, M., Brückner, A., Mirabile, S., Dorn, T., Riemer, V., Schrader, C., Weber, M.: LiverDefense: using a tower defense game as a customisable research tool. In: 7th International Conference on Games and Virtual Worlds for Serious Applications (VS-Games), pp. 1–8 (2015)Google Scholar
  14. Bruni, R., Corradini, A., Gadducci, F., Lafuente, A.L. Vandin, A.: A conceptual framework for adaptation. In: de Lara, J., Zisman, A. (eds.) Fundamental Approaches to Software Engineering, pp. 240–254. Springer, Berlin (2012)Google Scholar
  15. Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web, pp. 3–53. Springer, Berlin (2007)CrossRefGoogle Scholar
  16. Byun, J., Loh, C.S.: Audial engagement: effects of game sound on learner engagement in digital game-based learning environments. Comput. Hum. Behav. 46, 129–138 (2015)CrossRefGoogle Scholar
  17. Cacioppo, J.T., Berntson, G.G., Larsen, J.T., Poehlmann, K.M., Ito, T.A.: The psychophysiology of emotion. In: Lewis, R., Haviland-Jones, J.M. (eds.) The Handbook of Emotion, pp. 173–191. Guilford Press, New York (2000)Google Scholar
  18. Campos, M.S.F, de Oliveira, K.S., Brawerman-Albini, A.: The use of video games in the teaching-learning process of English as a foreign language. In: International Conference on Interactive Computer Aided Blended Learning, pp. 218–223 (2013)Google Scholar
  19. Chanel, G., Rebetez, C., Bétrancourt, M., Pun, T.: Emotion assessment from physiological signals for adaptation of game difficulty. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 41, 1052–1063 (2011)CrossRefGoogle Scholar
  20. Connolly, T.M., Boyle, E.A., MacArthur, E., Hainey, T., Boyle, J.M.: A systematic literature review of empirical evidence on computer games and serious games. Comput. Educ. 59 (2), 661–686 (2012)CrossRefGoogle Scholar
  21. Corno, L., Snow, R.E.: Adapting teaching to individual differences among learners. In: Wittrock, M.C. Association, A.E.R. (eds.) Handbook of Research on Teaching, pp. 605–629. American Educational Research Association, Washington, DC (1986)Google Scholar
  22. Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W., Taylor, J.G. Emotion recognition in human-computer interaction. Signal Process. Mag. IEEE 18 (1), 32–80 (2001)CrossRefGoogle Scholar
  23. Cronbach, L.J.: The two disciplines of scientific psychology. Am. Psychol. 12, 671 (1957)CrossRefGoogle Scholar
  24. Cronbach, L.J., Snow, R.E.: Aptitudes and Instructional Methods: A Handbook for Research on Interactions. Irvington, New York (1977)Google Scholar
  25. Dewey, J.: The child and the curriculum. In: Archambault, R.D. (ed.) John Dewey on Education: Selected Writings, pp. 339–358. Modern Library, New York (1902/1964)Google Scholar
  26. D’Mello, S., Graesser, A.: AutoTutor and affective AutoTutor: learning by talking with cognitively and emotionally intelligent computers that talk back. ACM Trans. Interact. Intell. Syst. (TiiS) 2, 1–39 (2012)Google Scholar
  27. Dormans, J.: Adventures in level design: generating missions and spaces for action adventure games. In: Proceedings of the 2010 Workshop on Procedural Content Generation in Games, p. 1. ACM (2010)Google Scholar
  28. Dormans, J.: Level design as model transformation: a strategy for automated content generation. In: Proceedings of the 2nd International Workshop on Procedural Content Generation in Games, p. 2. ACM (2011)Google Scholar
  29. Drachen, A., Nacke, L.E., Yannakakis, G., Pedersen, A.L.: Correlation between heart rate, electrodermal activity and player experience in first-person shooter games. In: Proceedings of the 5th ACM SIGGRAPH Symposium on Video Games, pp. 49–54. ACM, New York (2010)Google Scholar
  30. Efklides, A., Volet, S.: Emotional experiences during learning: multiple, situated and dynamic. Learn. Instr. 15, 377–380 (2005)CrossRefGoogle Scholar
  31. Ekman, P., Levenson, R.W., Friesen, W.V.: Autonomic nervous system activity distinguishes among emotions. Science 221, 1208–1210 (1983)CrossRefGoogle Scholar
  32. de Freitas, S.: Learning in Immersive Worlds: A Review of Game-Based Learning. Joint Information Systems Committee, London (2006)Google Scholar
  33. Frijda, N.H.: The laws of emotion. Am. Psycholo. 43 (5), 349 (1988)CrossRefGoogle Scholar
  34. Frommel, J., Rogers, K., Brich, J., Besserer, D., Bradatsch, L., Ortinau, I., Schabenberger, R., Riemer, V., Schrader, C., Weber, M.: Integrated questionnaires: Maintaining presence in game environments for self-reported data acquisition. In: Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play, pp. 359–368. ACM (2015)Google Scholar
  35. Gasselseder, H.P.: Dynamic music and immersion in the action-adventure an empirical investigation. In: Proceedings of the 9th Audio Mostly: A Conference on Interaction With Sound, p. 28. ACM (2014a)Google Scholar
  36. Gasselseder, H.P.: Those who played were listening to the music? Immersion and dynamic music in the ludonarrative. In: 4th International Workshop on Cognitive Information Processing (CIP) 2014, pp. 1–8. IEEE (2014b)Google Scholar
  37. Gilleade, K.M., Dix, A.: Using Frustration in the Design of Adaptive Videogames, pp. 228–232. ACM, New York (2004)Google Scholar
  38. Hainey, T., Westera, W., Connolly, T.M., Boyle, L., Baxter, G., Beeby, R.B., Soflano M.: Students’ attitudes toward playing games and using games in education: Comparing Scotland and the Netherlands. Comput. Edu. 69, 474–484 (2013)CrossRefGoogle Scholar
  39. Hamari, J., Shernoff, D.J., Rowe, E., Coller, B., Asbell-Clarke, J., Edwards T.: Challenging games help students learn: an empirical study on engagement, flow and immersion in game-based learning. Comput. Hum. Behav. 54, 170–179 (2016)CrossRefGoogle Scholar
  40. Harley, J.M., Bouchet, F., Azevedo, R.: Aligning and comparing data on emotions experienced during learning with MetaTutor. In: Artificial Intelligence in Education, pp. 61–70. Springer, Berlin (2013)Google Scholar
  41. Hartley, T., Mehdi Q.: Online action adaptation in interactive computer games. Comput. Entertain. (CIE) 7 (2):28 (2009)Google Scholar
  42. Hastings, E.J., Guha, R.K., Stanley, K.O.: Evolving content in the galactic arms race video game. In: Computational Intelligence and Games, CIG 2009, IEEE (2009)Google Scholar
  43. Hazlett, R.L.: Measuring emotional valence during interactive experiences: boys at video game play. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1023–1026. ACM, New York (2006)Google Scholar
  44. Johnson, D., Nacke, L.E., Wyeth, P.: All about that base: differing player experiences in video game genres and the unique case of moba games. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 2265–2274, ACM (2015)Google Scholar
  45. Kaukoranta, T., Smed, J., Hakonen, H.: Understanding pattern recognition methods. In: Rabin, S. (ed.) AI Game Programming Wisdom 2, pp. 579–589. Charles River Media, Hingham (2003)Google Scholar
  46. Kazmi, S., Palmer, I.J.: Action recognition for support of adaptive gameplay: A case study of a first person shooter. Int. J. Comput. Games Tech. 2010, 1 (2010)Google Scholar
  47. Khatchadourian, R.: World without end – creating a full-scale digital cosmos. [Online] The New Yorker (2015). Last Accessed 3 Aug 2016
  48. Kleinsmith, A., Bianchi-Berthouze, N.: Affective body expression perception and recognition: a survey. IEEE Trans. Affect Comput. 4 (1), 15–33 (2013)Google Scholar
  49. Kleinsmith, A., Bianchi-Berthouze, N., Steed, A.: Automatic recognition of non-acted affective postures. IEEE Trans. Syst. Man Cybern. Part B Cybern. 41, 1027–1038 (2011)CrossRefGoogle Scholar
  50. Klimmt, C., Hartmann, T., Frey, A.: Effectance and control as determinants of video game enjoyment. Cyberpsychol. Behav. 10, 845–848 (2007)CrossRefGoogle Scholar
  51. Koelsch, S.: Towards a neural basis of music-evoked emotions. Trends Cognit. Sci. 14 (3), 131–137 (2010)CrossRefGoogle Scholar
  52. Kort, B., Reilly, R., Picard, R.W.: An affective model of interplay between emotions and learning: reengineering educational pedagogy-building a learning companion. In: Proceedings of the IEEE International Conference on Advanced Learning Technologies, pp. 43–46 (2001)Google Scholar
  53. Lang, P.J., Greenwald, M.K., Bradley, M.M., Hamm, A.O.: Looking at pictures: affective, facial, visceral, and behavioral reactions. Psychophysiology 30, 261–273 (1993)CrossRefGoogle Scholar
  54. van Lankveld, G., Spronck, P., van den Herik, H.J., Rauterberg, M.: Incongruity-based adaptive game balancing. In: van den Herik, H.J., Spronck, P. (eds.) 12th International Conference on Advances in Computer Games (ACG 2009), 11–13 May 2009. Revised Papers, pp. 208–220. Springer, Berlin (2010)Google Scholar
  55. Larsen, J.T., Berntson, G.G., Poehlmann, K.M., Ito, T.A., Cacioppo, J.T. The psychophysiology of emotion. In: Lewis, M., Haviland-Jones, J.M., Feldman Barrett, L. (eds.) The Handbook of Emotions, 3rd edn., pp. 180–195. Guilford Press, New York (2010)Google Scholar
  56. Lee, J., Park, O.: Adaptive instructional systems. In: Spector, J.M., Merril, M.D., van Merrienboer, J.J.G, Driscoll, M. (eds.) Handbook of Research on Educational Communications and Technology, 3rd edn. Taylor & Francis, New York, p. 469–484 (2008)Google Scholar
  57. Levy, H.M. Meeting the needs of all students through differentiated instruction: helping every child reach and exceed standards. Clearing House J. Educ Strateg Issues and Ideas 81 (4), 161–164 (2008)CrossRefGoogle Scholar
  58. Linnenbrink, E.A.: Emotion research in education: theoretical and methodological perspectives on the integration of affect, motivation, and cognition. Edu. Psychol. Rev. 18, 307–314 (2006)CrossRefGoogle Scholar
  59. Lopes, R., Bidarra, R.: Adaptivity challenges in games and simulations: a survey. IEEE Trans. Comput. Intell. AI Games 3, 85–99 (2011a)Google Scholar
  60. Lopes, R., Bidarra, R.: A semantic generation framework for enabling adaptive game worlds. In: Proceedings of the 8th International Conference on Advances in Computer Entertainment Technology (ACE’11), pp. 6:1–6:8. ACM, New York (2011b). doi:  10.1145/2071423.2071431.
  61. Magerko, B., Heeter, C., Fitzgerald, J., Medler, B.: Intelligent adaptation of digital game-based learning. In: Proceedings of the 2008 Conference on Future Play: Research, Play, Share, pp. 200–203. ACM, New York (2008)Google Scholar
  62. Malone, T.W.: Toward a theory of intrinsically motivating instruction. Cogn. Sci. 5 (4), 333–369 (1981)CrossRefGoogle Scholar
  63. Malone, T.W., Lepper, M.R. Making learning fun: a taxonomy of intrinsic motivations for learning. Aptit. learn. instr. 3 (1987), 223–253 (1987)Google Scholar
  64. Mandryk, R.L., Inkpen, K.M., Calvert, T.W.: Using psychophysiological techniques to measure user experience with entertainment technologies. Behav. Inf. Tech. 25, 141–158 (2006)CrossRefGoogle Scholar
  65. Manslow, J.: Learning and adaptation. In: Rabin S (ed) AI Game Programming Wisdom, pp. 557–566. Charles River Media, Hingham (2002)Google Scholar
  66. Mateas, M., Stern, A.: Façade: an experiment in building a fully-realized interactive drama. In: Game Developers Conference, vol. 2 (2003)Google Scholar
  67. Mauss, I.B., Robinson, M.D.: Measures of emotion: a review. Cognit. Emot. 23 (2), 209–237 (2009)CrossRefGoogle Scholar
  68. McMahan, T., Parberry, I., Parsons, T.D.: Modality specific assessment of video game player’s experience using the Emotiv. Entertain. Comput. 7, 1–6 (2015)CrossRefGoogle Scholar
  69. Meinhardt, J., Pekrun, R.: Attentional resource allocation to emotional events: an ERP study. Cognit. Emot. 17, 477–500 (2003)CrossRefGoogle Scholar
  70. Mountain, G.: Psychology profiling in Silent Hill: Shattered Memories. In: Video Presented at the Paris Game/AI Conference (2010)Google Scholar
  71. Müller, P., Wonka, P., Haegler, S., Ulmer, A., Van Gool, L.: Procedural modeling of buildings. ACM Trans. Graph. (TOG) 25 (3), 614–623 (2006)Google Scholar
  72. National Association of State Boards of Education (2001) Report of the NASBE Study Group on e-learning: the future of education. Technical report, University of VirginiaGoogle Scholar
  73. Nelson, M.J., Mateas, M.: Towards automated game design. In: AI* IA 2007: Artificial Intelligence and Human-Oriented Computing, pp. 626–637. Springer (2007)Google Scholar
  74. Nguyen, L., Do, P.: Learner model in adaptive learning. In: Proceedings of World Academy of Science, Engineering and Technology, vol. 45, pp. 395–400 (2008)Google Scholar
  75. Novak, K., Nackerud, R.: Choosing a Serious Game for the Classroom: an Adoption Model for Educators, pp. 291–308. Springer, London (2011). doi:  10.1007/978-1-4471-2161-9_15.
  76. Orji, R., Vassileva, J., Mandryk, R.L.: Modeling the efficacy of persuasive strategies for different gamer types in serious games for health. User Model. User-Adap. Inter. 24, 453–498 (2014)CrossRefGoogle Scholar
  77. Pagulayan, R.J., Keeker, K., Wixon, D., Romero, R.L., Fuller, T.: User-centered design in games. CRC Press, Boca Raton (2002)Google Scholar
  78. Parkin, S.: No man’s sky: the game where you can explore 18 quintillion planets. [Online] theguardian (2015). Last Accessed 3 Aug 2016
  79. Pedersen, C., Togelius, J., Yannakakis, G.N.: Modeling player experience for content creation. IEEE Trans. Comput. Intell. AI Games 2 (1), 54–67 (2010)CrossRefGoogle Scholar
  80. Picard, R.W.: Affective computing, vol. 252. MIT Press, Cambridge (1997)Google Scholar
  81. Plass, J.L., Heidig, S., Hayward, E.O., Homer, B.D., Um, E.: Emotional design in multimedia learning: effects of shape and color on affect and learning. Learn. Instr. 29, 128–140 (2014)CrossRefGoogle Scholar
  82. Pozderac-Chenevey, S.: A direct link to the past: nostalgia and semiotics in video game music. CeReNeM J. 2 (2), 1–26 (2014)Google Scholar
  83. Raibulet, C.: Facets of adaptivity. In: Morrison, R., Balasubramaniam, D., Falkner, K. (eds.) Software Architecture, pp. 342–345. Springer, Berlin (2008)CrossRefGoogle Scholar
  84. Raibulet, C., Masciadri, L.: Evaluation of dynamic adaptivity through metrics: an achievable target? In: Joint Working IEEE/IFIP Conference on Software Architecture & European Conference on Software Architecture (WICSA/ECSA 2009), pp. 341–344. IEEE (2009)Google Scholar
  85. Ravaja, N., Saari, T., Laarni, J., Kallinen, K., Salminen, M., Holopainen, J., Järvinen, A.: The Psychophysiology of video gaming: phasic emotional responses to game events. In: Proceedings of DiGRA 2005 Conference: Changing Views Worlds in Play (2005)Google Scholar
  86. Ravaja, N., Saari, T., Salminen, M., Laarni, J., Kallinen, K.: Phasic emotional reactions to video game events: a psychophysiological investigation. Media Psychol. 8, 343–367 (2006)CrossRefGoogle Scholar
  87. Ravaja, N., Turpeinen, M., Saari, T., Puttonen, S., Keltikangas-Järvinen, L.: The psychophysiology of James Bond: phasic emotional responses to violent video game events. Emotion 8 (1), 114 (2008)CrossRefGoogle Scholar
  88. Ricci, K.E., Salas, E., Cannon-Bowers, J.A.: Do computer-based games facilitate knowledge acquisition and retention? Mil. Psychol. 8, 295–307 (1996)CrossRefGoogle Scholar
  89. Risi, S., Togelius, J.: Neuroevolution in games: state of the art and open challenges. IEEE Trans. Comput. Intell. AI Games. IEEE (2014)Google Scholar
  90. Roberts, D.L., Isbell, C.L.: A survey and qualitative analysis of recent advances in drama management. Int. Trans. Syst. Sci. Appl. Spec Issue Agent Based Syst. Hum. Learn. 4 (2), 61–75 (2008)Google Scholar
  91. Rodrigo, M., Baker, R.: Comparing learners’ affect while using an intelligent tutor and an educational game. Res. Pract. Tech. Enhanc. Learn. 6, 43–66 (2011)Google Scholar
  92. Russell, J.A.: A circumplex model of affect. J. Personal. Soc. Psychol. 39, 1161–1178 (1980)CrossRefGoogle Scholar
  93. Russoniello, C.V., O’Brien, K., Parks, J.M.: The effectiveness of casual video games in improving mood and decreasing stress. J. Cyber Ther. Rehabil. 2, 53–66 (2009)Google Scholar
  94. Ryan, R.M., Deci, E.L.: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55 (1), 68 (2000)CrossRefGoogle Scholar
  95. Schrader, C., Nett, U.: The perception of control as a predictor of emotional trends during gameplay (2016, in press)Google Scholar
  96. Schutz, P.A., Pekrun, R.: Introduction to emotions in education. In: Emotion in Education, 22nd edn., pp. 3–10. Elsevier Academic Press, Burlington (2007)Google Scholar
  97. Shaffer, D.W., Squire, K.R., Halverson, R., Gee, J.P.: Video games and the future of learning. Phi Delta Kappan 87 (2), 104–111 (2005)CrossRefGoogle Scholar
  98. Shaker, M., Shaker, N., Togelius, J.: Evolving playable content for cut the rope through a simulation-based approach. In: AIIDE (2013)Google Scholar
  99. Shaker, N., Asteriadis, S., Yannakakis, G.N., Karpouzis, K.: A game-based corpus for analysing the interplay between game context and player experience. In: D’Mello, S., Graesser, A., Schuller, B., Martin, J.C. (eds.) Affective Computing and Intelligent Interaction, pp. 547–556. Springer, Berlin (2011)CrossRefGoogle Scholar
  100. Shaker, N., Nicolau, M., Yannakakis, G.N., Togelius, J., Neill, M.O.: Evolving levels for Super Mario Bros using grammatical evolution. In: IEEE Conference on Computational Intelligence and Games (CIG), pp. 304–311. IEEE (2012)Google Scholar
  101. Shute, V.J.: Stealth assessment in computer-based games to support learning. Comput. Gamesinstr. 55 (2), 503–524 (2011)Google Scholar
  102. Shute, V.J., Zapata-Rivera, D.: Adaptive educational systems. Adapt. Tech. Train. Edu. 7, 27 (2012)Google Scholar
  103. Shute, V.J., D’Mello, S., Baker, R., Cho, K., Bosch, N., Ocumpaugh, J., Ventura, M., Almeda, V.: Modeling how incoming knowledge, persistence, affective states, and in-game progress influence student learning from an educational game. Comput. Educ. 86, 224–235 (2015)Google Scholar
  104. Smelik, R., Tutenel, T., de Kraker, K.J., Bidarra, R.: Integrating procedural generation and manual editing of virtual worlds. In: Proceedings of the 2010 Workshop on Procedural Content Generation in Games, p. 2. ACM (2010)Google Scholar
  105. Smith, G., Whitehead, J., Mateas, M.: Tanagra: a mixed-initiative level design tool. In: Proceedings of the Fifth International Conference on the Foundations of Digital Games, pp. 209–216. ACM (2010)Google Scholar
  106. Smith, G., Gan, E., Othenin-Girard, A., Whitehead, J.: PCG-based game design: enabling new play experiences through procedural content generation. In: Proceedings of the 2nd International Workshop on Procedural Content Generation in Games, p. 7. ACM (2011)Google Scholar
  107. Sobkin, V., Evstigneeva, I.M.: Chapter 4. Student’s Attitudes Toward Computer Games. Russ. Edu. Soci. 46, 3–35 (2004)Google Scholar
  108. Soflano, M.: Modding in Serious Games: Teaching Structured Query Language (SQL) Using NeverWinter Nights, chap. 18, pp. 347–368. Springer, London (2011). doi:  10.1007/978-1-4471-2161-9_18.
  109. Sorenson, N., Pasquier, P.: Towards a generic framework for automated video game level creation. In: Applications of Evolutionary Computation, pp. 131–140. Springer (2010)Google Scholar
  110. Spronck, P., Ponsen, M., Sprinkhuizen-Kuyper, I., Postma, E.: Adaptive game AI with dynamic scripting. Mach. Learn. 63 (3), 217–248 (2006)CrossRefGoogle Scholar
  111. Tellegen, A., Watson, D., Clark, L.A.: On the dimensional and hierarchical structure of affect. Psychol. Sci. 10, 297–303 (1999)CrossRefGoogle Scholar
  112. Thorndike, E.L.: Individuality. Houghton Mifflin, Boston (1911)Google Scholar
  113. Tijs, T., Brokken, D., IJsselsteijn, W.: Creating an emotionally adaptive game. In: Entertainment Computing – ICEC 2008: 7th International Conference, Pittsburgh, 25–27 Sept 2008. Proceedings, pp. 122–133. Springer, Berlin (2008)Google Scholar
  114. Togelius, J., De Nardi, R., Lucas, S.M.: Towards automatic personalised content creation for racing games. In: IEEE Symposium on Computational Intelligence and Games, CIG 2007, pp. 252–259. IEEE (2007)Google Scholar
  115. Tognetti, S., Garbarino, M., Bonarini, A., Matteucci, M.: Modeling enjoyment preference from physiological responses in a car racing game. In: IEEE Symposium on Computational Intelligence and Games (CIG), pp. 321–328. IEEE (2010)Google Scholar
  116. Vachiratamporn, V., Legaspi, R., Moriyama, K., Fukui, K.I., Numao, M.: An analysis of player affect transitions in survival horror games. J. Multimodal User Interfaces 9, 43–54 (2015). CrossRefGoogle Scholar
  117. Van Eck, R.: A guide to integrating COTS games into your classroom. Handb. Res. Eff. Electron. Gaming Educ. 1. IGI Global, Hershey (2009)Google Scholar
  118. Vandewaetere, M., Clarebout, G.: Advanced technologies for personalized learning, instruction, and performance. In: Spector, J.M., Merrill, M.D., Elen, J., Bishop, M.J. (eds.) Handbook of Research on Educational Communications and Technology, pp. 425–437. Springer (2013)Google Scholar
  119. Vandewaetere, M., Desmet, P., Clarebout, G.: The contribution of learner characteristics in the development of computer-based adaptive learning environments. Comput. Hum. Behav. 27, 118–130 (2011)Google Scholar
  120. Walker, A.: ‘no man’s sky’ isn’t out until next week, but this guy may have already beaten it. [Online] VICE (2016). Last Accessed 3 Aug 2016
  121. Wenger, E.: Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. Morgan Kaufmann, Los Altos/Calif (2014)Google Scholar
  122. Westera, W.: Performance assessment in serious games: Compensating for the effects of randomness. Educ. Inf. Technol. 21 (3), 681–697 (2014)CrossRefGoogle Scholar
  123. Wiklund, M., Rudenmalm, W., Norberg, L., Westin, T., Mozelius, P.: Evaluating educational games using facial expression recognition software: measurement of gaming emotion. In: European Conference on Games Based Learning, pp. 605–612. Academic Conferences and Publishing International (2015)Google Scholar
  124. Wong, W.L., Shen, C., Nocera, L., Carriazo, E., Tang, F., Bugga, S., Narayanan, H., Wang, H., Ritterfeld, U.: Serious video game effectiveness. In: Proceedings of the International Conference on Advances in Computer Entertainment Technology, pp. 49–55. ACM (2007)Google Scholar
  125. Wouters, P., van Nimwegen, C., van Oostendorp, H., van der Spek, E.D.: A meta-analysis of the cognitive and motivational effects of serious games. J. Edu. Psychol. 105, 249 (2013)Google Scholar
  126. Wu, D., Courtney, C.G., Lance, B.J., Narayanan, S.S., Dawson, M.E., Oie, K.S., Parsons, T.D.: Optimal arousal identification and classification for affective computing using physiological signals: virtual reality stroop task. IEEE Trans. Affect. Comput. 1 (2), 109–118 (2010)CrossRefGoogle Scholar
  127. Yannakakis, G.N., Hallam, J.: Ranking vs. preference: a comparative study of self-reporting. In: Affective Computing and Intelligent Interaction, pp. 437–446. Springer (2011)Google Scholar
  128. Yannakakis, G.N., Paiva, A.: Emotion in Games. Oxford Handb. Affect. Comput. p. 459. Oxford University Press, USA (2014)Google Scholar
  129. Yannakakis, G.N., Togelius, J.: Experience-driven procedural content generation. IEEE Trans. Affect. Comput. 2 (3), 147–161 (2011)CrossRefGoogle Scholar
  130. Zentner, M., Grandjean, D., Scherer, K.R.: Emotions evoked by the sound of music: characterization, classification, and measurement. Emotion 8 (4), 494 (2008)CrossRefGoogle Scholar

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Authors and Affiliations

  • Claudia Schrader
    • 1
    Email author
  • Julia Brich
    • 2
  • Julian Frommel
    • 2
  • Valentin Riemer
    • 1
  • Katja Rogers
    • 2
  1. 1.Institute for Psychology and EducationUlm UniversityUlmGermany
  2. 2.Institute of Media InformaticsUlm UniversityUlmGermany

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