DETERMINING THE DEGREE OF PLAYER ENGAGEMENT IN A COMPUTER GAME WITH ELEMENTS OF A SOCIAL CAMPAIGN USING COGNITIVE NEUROSCIENCE TECHNIQUES
Article Sidebar
Open full text
Issue Vol. 18 No. 4 (2022)
-
APPLICATION OF GILLESPIE ALGORITHM FOR SIMULATING EVOLUTION OF FITNESS OF MICROBIAL POPULATION
Jarosław GIL, Andrzej POLAŃSKI5-15
-
HOW MACHINE LEARNING ALGORITHMS ARE USED IN METEOROLOGICAL DATA CLASSIFICATION: A COMPARATIVE APPROACH BETWEEN DT, LMT, M5-MT, GRADIENT BOOSTING AND GWLM-NARX MODELS
Sheikh Amir FAYAZ, Majid ZAMAN, Muheet Ahmed BUTT, Sameer KAUL16-27
-
DETERMINING THE DEGREE OF PLAYER ENGAGEMENT IN A COMPUTER GAME WITH ELEMENTS OF A SOCIAL CAMPAIGN USING COGNITIVE NEUROSCIENCE TECHNIQUES
Konrad BIERCEWICZ, Mariusz BORAWSKI, Anna BORAWSKA, Jarosław DUDA28-52
-
ANALYSIS OF THE POSSIBILITY OF USING THE SINGULAR VALUE DECOMPOSITION IN IMAGE COMPRESSION
Edyta ŁUKASIK, Emilia ŁABUĆ53-67
-
PREDICTION OF THE COMPRESSIVE STRENGTH OF ENVIRONMENTALLY FRIENDLY CONCRETE USING ARTIFICIAL NEURAL NETWORK
Monika KULISZ, Justyna KUJAWSKA, Zulfiya AUBAKIROVA, Gulnaz ZHAIRBAEVA, Tomasz WAROWNY68-81
-
NUMERICAL AND EXPERIMENTAL ANALYSIS OF A CENTRIFUGAL PUMP WITH DIFFERENT ROTOR GEOMETRIES
Łukasz SEMKŁO, Łukasz GIERZ82-95
-
A COUGH-BASED COVID-19 DETECTION SYSTEM USING PCA AND MACHINE LEARNING CLASSIFIERS
Elmehdi BENMALEK, Jamal EL MHAMDI, Abdelilah JILBAB, Atman JBARI96-115
-
IDENTIFICATION OF THE IMPACT OF THE AVAILABILITY FACTOR ON THE EFFICIENCY OF PRODUCTION PROCESSES USING THE AHP AND FUZZY AHP METHODS
Piotr WITTBRODT, Iwona ŁAPUŃKA, Gulzhan BAYTIKENOVA, Arkadiusz GOLA, Alfiya ZAKIMOVA116-129
Archives
-
Vol. 20 No. 4
2025-01-31 12
-
Vol. 20 No. 3
2024-09-30 12
-
Vol. 20 No. 2
2024-08-14 12
-
Vol. 20 No. 1
2024-03-30 12
-
Vol. 19 No. 4
2023-12-31 10
-
Vol. 19 No. 3
2023-09-30 10
-
Vol. 19 No. 2
2023-06-30 10
-
Vol. 19 No. 1
2023-03-31 10
-
Vol. 18 No. 4
2022-12-30 8
-
Vol. 18 No. 3
2022-09-30 8
-
Vol. 18 No. 2
2022-06-30 8
-
Vol. 18 No. 1
2022-03-30 7
-
Vol. 17 No. 4
2021-12-30 8
-
Vol. 17 No. 3
2021-09-30 8
-
Vol. 17 No. 2
2021-06-30 8
-
Vol. 17 No. 1
2021-03-30 8
-
Vol. 16 No. 4
2020-12-30 8
-
Vol. 16 No. 3
2020-09-30 8
-
Vol. 16 No. 2
2020-06-30 8
-
Vol. 16 No. 1
2020-03-30 8
Main Article Content
DOI
Authors
Abstract
Due to the popularity of video games in various applications, including both commercial and social marketing, there is a need to assess their content in terms of player satisfaction, already at the production stage. For this purpose, the indices used in EEG tests can be used. In this publication, a formula has been created based on the player's commitment to determining which elements in the game should be improved and for which graphic emblems connected with social campaigns were more memorable and whether this was related to commitment. The survey was conducted using a 2D platform game created in Unity based on observations of 28 recipients. To evaluate the elements occurring in the game at which we obtain a higher memory for graphic characters, a corresponding pattern was created based on player involvement. The optimal Index for moving and static objects and the Index for destruction were then selected based on the feedback. Referring to the issue of graphic emblems depicting social campaigns should be placed in a place where other activities such as fighting will not be distracted, everyone will be able to reach the level where the recently placed advertisement is. This study present the developed method to determine the degree of player's engagement in particular elements in the game using the EEG and to explore the relationship between the visibility of social advertising and engagement in a 2D platform game where the player has to collect three keys and defeat the ultimate opponent.
Keywords:
References
D Platformer—Asset Store. (b.d.).Unity Asset Store. Retrieved September 2, 2019 from https://assetstore.unity.com/packages/essentials/tutorial-projects/2d-platformer-11228
Berka, C., Levendowski, D. J., Lumicao, M. N., Yau, A., Davis, G., Zivkovic, V. T., Olmstead, R. E., Tremoulet, P. D., & Craven, P. L. (2007). EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. Aviation, Space, and Environmental Medicine, 78(5 Suppl), B231–244.
Brown, E., & Cairns, P. (2004). A Grounded Investigation of Game Immersion. CHI ’04 Extended Abstracts on Human Factors in Computing Systems(pp. 1297–1300). The ACM Digital Library. https://doi.org/10.1145/985921.986048
Chang, Y., Yan, J., Zhang, J., & Luo, J. (2010). Online In-Game Advertising Effect: Examining the Influence of a Match Between Games and Advertising. Journal of Interactive Advertising, 11, 63–73. https://doi.org/10.1080/15252019.2010.10722178
Chaouachi, M., & Frasson, C. (2012). Mental Workload, Engagement and Emotions: An Exploratory Study for Intelligent Tutoring Systems. Intelligent Tutoring Systems. ITS 2012. Lecture Notes in Computer Science(vol 7315). Springer Heidelberg. https://doi.org/10.1007/978-3-642-30950-2_9
Chen, J. (2007). Flow in Games (and Everythingelse). Commun. ACM, 50(4), 31–34. https://doi.org/10.1145/1232743.1232769
Costello, B., & Edmonds, E. (2009). A Tool for Characterizing the Experience of Play. Proceedings of the Sixth Australasian Conference on Interactive Entertainment, 2, 1–10. https://doi.org/10.1145/1746050.1746052
Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience.Harper Perennial Modern Classics.
Ewing, K. C., Fairclough, S. H., & Gilleade, K. (2016). Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop. Frontiers in Human Neuroscience, 10, 223–223. https://doi.org/10.3389/fnhum.2016.00223
Filsecker, M., & Kerres, M. (2014). Engagement as a Volitional Construct: A Framework for Evidence-Based Research on Educational Games. Simulation & Gaming, 45(4–5), 450–470. https://doi.org/10.1177/1046878114553569
Freeman, F. G., Mikulka, P. J., Prinzel, L. J., &Scerbo, M. W. (1999). Evaluation of an adaptive automation system using three EEG indices with a visual tracking task. Biological Psychology, 50(1), 61–76.
Gałuszka, D. (2016). Nowy wymiar reklamy-in-game advertising oraz advergaming. Kultura i Historia, 29, 33–49.GameAnalytics. (n.d.).
GameAnalytics. Retrieved April 5, 2020 from https://gameanalytics.com/
Hofman-Kohlmeyer, M. (2017). Komunikacja marketingowa w grach komputerowych—Współczesne kierunki badań. Studia Ekonomiczne, 328, 70–82.
Hondrou, C., &Caridakis, G. (2012). Affective, Natural Interaction Using EEG: Sensors, Application and Future Directions. W I. Maglogiannis, V. Plagianakos, & I. Vlahavas (Eds.), Artificial Intelligence: Theories and Applications(s. 331–338). Springer Berlin Heidelberg.
Hyman, P. (2007). Burger King has it their way with advergame sales. Hollywood Report.
Iacovides, I., Aczel, J., Scanlon, E., Taylor, J., & Woods, W. (2011). Motivation, Engagement and Learning through Digital Games. IJVPLE, 2, 1–16. https://doi.org/10.4018/jvple.2011040101
Ijsselsteijn, W., van den Hoogen, W., Klimmt, C., De Kort, Y., Lindley, C., Mathiak, K., Poels, K., Ravaja, N., Turpeinen, M., & Vorderer, P. (2008). Measuring the experience of digital game enjoyment. Proceedings of Measuring Behavior(pp. 88–89). Noldus.
Jennett, C., Cox, A. L., Cairns, P., Dhoparee, S., Epps, A., Tijs, T., & Walton, A. (2008). Measuring and defining the experience of immersion in games. International Journal of Human-Computer Studies, 66(9), 641–661. https://doi.org/10.1016/j.ijhcs.2008.04.004
Jurcak, V., Tsuzuki, D., & Dan, I. (2007). 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems. NeuroImage, 34(4), 1600–1611. https://doi.org/10.1016/j.neuroimage.2006.09.024
Kamzanova, A. T., Matthews, G., Kustubayeva,A. M., & Jakupov, S. M. (2011). EEG indices to time-on-task effects and to a workload manipulation (Cueing). World Academy of Science, Engineering and Technology, 80, 19–22.
Kiedy reklama flirtuje z gamingiem... (2015, March20). Marketer+ przewodnik po marketingu. https://marketerplus.pl/teksty/artykuly/reklama-flirtuje-gamingiem/
Koster, R., & Wright,W. (2004). A Theory of Fun for Game Design. Paraglyph Press.
Lee, C., Kwon, J., Hong, J., & Lee, D. (2010). A Study on EEG based Concentration Power Index Transmission and Brain Computer Interface Application(s. 537–539). Springer. https://doi.org/10.1007/978-3-642-03882-2_142
Lilly, J. M., & Olhede, S. C. (2010). On the Analytic Wavelet Transform. IEEE Transactions on Information Theory, 56(8), 4135–4156. https://doi.org/10.1109/TIT.2010.2050935
Lilly, J.M., & Olhede, S.C.(2012). Generalized Morse Wavelets as a Superfamily of Analytic Wavelets. IEEE Transactionson Signal Processing, 60(11), 6036-6041. https://doi.org/10.1109/TSP.2012.2210890
Lokowanie produktów w grach komputerowych—Prawo własności intelektualnej. (b.d.). Retrieved April 3, 2020 from https://www.pwi.us.edu.pl/kategorie/prawo-reklamy/253-lokowanie-produktow-w-grach-komputerowych?jjj=1586621566826&jjj=1586626966769
Lombard, M., & Ditton, T. (1997). At the heart of it all: The concept of presence. Journal of Computer-Mediated Communication, 3(2).
Mcmahan, A. (2003). Immersion, engagement, and presence: A method for analyzing 3-D video games. The Video Game Theory Reader(pp. 67–86).Routledge, Taylor & Francis Group.
McMahan, T., Parberry, I., & Parsons, T. D. (2015). Evaluating Player Task Engagement and Arousal Using Electroencephalography. Procedia Manufacturing, 3, 2303–2310. https://doi.org/10.1016/j.promfg.2015.07.376
Pope, A.T., Bogart, E. H., & Bartolome, D. S. (1995). Biocybernetic system evaluates indices of operator engagement in automated task. Biological Psychology, 40(1–2), 187–195. https://doi.org/10.1016/0301-0511(95)05116-3
Przybylski, A.K., Scott Rigby, C., & Ryan, R. (2010). A Motivational Model of Video Game Engagement. Review of General Psychology, 14, 154–166. https://doi.org/10.1037/a0019440
Ravaja, N., Saari, T., Salminen, M., Laarni, J., & Kallinen, K. (2006). Phasic Emotional Reactions to Video Game Events: A Psychophysiological Investigation. Media Psychology, 8(4), 343–367. https://doi.org/10.1207/s1532785xmep0804_2
Rubin, B. (b.d.). Policies & Programs to Reduce Distracted Driving. Retrieved September 9, 2020 from https://www.government-fleet.com/156182/policies-programs-to-reduce-distracted-driving
Schoenau-Fog, H. (2011). The player engagement process—An exploration of continuation desire in digital games. Proceedings of DiGRA 2011 Conference: Think Design Play.
Smith, M., & Gevins, A. (2005). Neurophysiologic monitoring of mental workload and fatigue during operation of a flight simulator. Proceedings of SPIE -The International Society for Optical Engineering (5797). Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.602181
Statista. (2017). Video games advertising spending worldwide from 2010 to 2020 (in billion U.S. dollars). https://www.statista.com/statistics/238140/global-video-games-advertising-revenue/
Sweetser, P., & Wyeth, P. (2005). GameFlow: A Model for Evaluating Player Enjoyment in Games. Computers in Entertainment, 3(3), 3–3. https://doi.org/10.1145/1077246.1077253
Tamborini, R., &Skalski, P. (2006). The role of presence in the experience of electronic games. Playing video games: Motives, responses, and consequences(pp.225–240). Lawrence Erlbaum Associates Publishers.
The motion monkey. (2017). UK Advergame Design & Development. https://www.themotionmonkey.co.uk/advergames/
Tsipouras, M. G. (2019). Spectral information of EEG signals with respect to epilepsy classification. EURASIP Journal on Advances in Signal Processing, 2019(1), 10. https://doi.org/10.1186/s13634-019-0606-8
United Nations World Food Programme. (2017). Food Force. https://web.archive.org/web/20050605073447/http://www.food-force.com/Unity—Analytics. (b.d.).
Unity. Retrieved April 5, 2020 fromhttps://unity3d.com/unity/features/analytics
Vourvopoulos, A., Bermudez,I.,Badia, S., & Liarokapis, F. (2017). EEG Correlates of Video Game Experience and User Profile in Motor-imagery-based Brain—Computer Interaction. The Visual Computer, 33(4), 533–546. https://doi.org/10.1007/s00371-016-1304-2
Wachowiak, M., Smolikova-Wachowiak, R., Johnson, M., Hay, D., Power, K., & Williams-Bell, F. (2018). Quantitative feature analysis of continuous analytic wavelet transforms of electrocardiography and electromyography. Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences, 376, 20170250. https://doi.org/10.1098/rsta.2017.0250
Yamada, F. (1998). Frontal midline theta rhythm and eyeblinking activity during a VDT task and a video game: Useful tools for psychophysiologyin ergonomics. Ergonomics, 41(5), 678–688. https://doi.org/10.1080/001401398186847
Yang, M., Ewoldsen, D., Dinu, L., & Arpan, L. (2006). The Effectiveness of „in-Game” Advertising: Comparing College Students’ Explicit and Implicit Memory for Brand Names. Journal of Advertising, 35, 143–152. https://doi.org/10.2753/JOA0091-3367350410
Yee, N. (2006). Motivations for play in online games. Cyberpsychology & Behavior : The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 9(6), 772–775. https://doi.org/10.1089/cpb.2006.9.772
Yenigun, S. (2012). Presidential Campaigns Rock The Gamer Vote: NPR. https://www.npr.org/2012/10/01/162103528/presidential-campaigns-rock-the-gamer-vote?t=1582567815999
Article Details
Abstract views: 287
License
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
