Transforming Society through Creative Technology: Case Studies of Social Innovation in Game Design and Virtual Reality
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Game Design, Social Innovation, Virtual Reality
Abstract
The advent of creative technologies such as game design and virtual reality (VR) has opened new avenues for social innovation. These technologies offer immersive and interactive experiences that can address various societal challenges, from education to mental health. Despite their potential, there is limited comprehensive research on how these technologies are being utilized in social innovation. This research aims to explore how creative technologies in game design and virtual reality are transforming society through social innovation. The study seeks to identify successful case studies and analyze the impact of these technologies on different social sectors. The research employs a qualitative case study approach, examining six social innovation projects that leverage game design and VR. Data were collected through in-depth interviews with project leaders, direct observation, and analysis of project outcomes. This approach provides a detailed understanding of the implementation processes, challenges, and successes of each project. The findings indicate that game design and VR have significant potential to create positive social change. Projects in education showed enhanced student engagement and learning outcomes, while mental health initiatives reported improved therapeutic experiences and patient well-being. Other projects addressed issues such as social inclusion and environmental awareness, demonstrating the versatility and effectiveness of these technologies. The study concludes that creative technologies in game design and VR can play a transformative role in social innovation. By providing engaging and immersive experiences, these technologies can effectively address a wide range of societal challenges. Continued research and investment in these areas are recommended to fully harness their potential for social good.
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References
Alzheimer’s Association. (2018). 2018 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 14(3), 367–429. https://doi.org/10.1016/j.jalz.2018.02.001
Armitage, N. P., Mele, E. J., & Vishwanath, A. (2018). Weyl and Dirac semimetals in three-dimensional solids. Reviews of Modern Physics, 90(1), 015001. https://doi.org/10.1103/RevModPhys.90.015001
Chen, J. S., Ma, E., Harrington, L. B., Da Costa, M., Tian, X., Palefsky, J. M., & Doudna, J. A. (2018). CRISPR-Cas12a target binding unleashes indiscriminate single-stranded DNase activity. Science, 360(6387), 436–439. https://doi.org/10.1126/science.aar6245
Elgrishi, N., Rountree, K. J., McCarthy, B. D., Rountree, E. S., Eisenhart, T. T., & Dempsey, J. L. (2018). A Practical Beginner’s Guide to Cyclic Voltammetry. Journal of Chemical Education, 95(2), 197–206. https://doi.org/10.1021/acs.jchemed.7b00361
Fajgenbaum, D. C., & June, C. H. (2020). Cytokine Storm. New England Journal of Medicine, 383(23), 2255–2273. https://doi.org/10.1056/NEJMra2026131
Funder, D. C., & Ozer, D. J. (2019). Evaluating Effect Size in Psychological Research: Sense and Nonsense. Advances in Methods and Practices in Psychological Science, 2(2), 156–168. https://doi.org/10.1177/2515245919847202
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., & Chen, T. (2018). Recent advances in convolutional neural networks. Pattern Recognition, 77, 354–377. https://doi.org/10.1016/j.patcog.2017.10.013
Guan, W., Ni, Z., Hu, Y., Liang, W., Ou, C., He, J., Liu, L., Shan, H., Lei, C., Hui, D. S. C., Du, B., Li, L., Zeng, G., Yuen, K.-Y., Chen, R., Tang, C., Wang, T., Chen, P., Xiang, J., … Zhong, N. (2020). Clinical Characteristics of Coronavirus Disease 2019 in China. New England Journal of Medicine, 382(18), 1708–1720. https://doi.org/10.1056/NEJMoa2002032
Hansen, K., Breyer, C., & Lund, H. (2019). Status and perspectives on 100% renewable energy systems. Energy, 175, 471–480. https://doi.org/10.1016/j.energy.2019.03.092
Huang, Y., Wang, Y., Wang, H., Liu, Z., Yu, X., Yan, J., Yu, Y., Kou, C., Xu, X., Lu, J., Wang, Z., He, S., Xu, Y., He, Y., Li, T., Guo, W., Tian, H., Xu, G., Xu, X., … Wu, Y. (2019). Prevalence of mental disorders in China: A cross-sectional epidemiological study. The Lancet Psychiatry, 6(3), 211–224. https://doi.org/10.1016/S2215-0366(18)30511-X
Kermany, D. S., Goldbaum, M., Cai, W., Valentim, C. C. S., Liang, H., Baxter, S. L., McKeown, A., Yang, G., Wu, X., Yan, F., Dong, J., Prasadha, M. K., Pei, J., Ting, M. Y. L., Zhu, J., Li, C., Hewett, S., Dong, J., Ziyar, I., … Zhang, K. (2018). Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning. Cell, 172(5), 1122-1131.e9. https://doi.org/10.1016/j.cell.2018.02.010
Kucharski, A. J., Russell, T. W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., Eggo, R. M., Sun, F., Jit, M., Munday, J. D., Davies, N., Gimma, A., van Zandvoort, K., Gibbs, H., Hellewell, J., Jarvis, C. I., Clifford, S., Quilty, B. J., Bosse, N. I., … Flasche, S. (2020). Early dynamics of transmission and control of COVID-19: A mathematical modelling study. The Lancet Infectious Diseases, 20(5), 553–558. https://doi.org/10.1016/S1473-3099(20)30144-4
Lai, J., Ma, S., Wang, Y., Cai, Z., Hu, J., Wei, N., Wu, J., Du, H., Chen, T., Li, R., Tan, H., Kang, L., Yao, L., Huang, M., Wang, H., Wang, G., Liu, Z., & Hu, S. (2020). Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Network Open, 3(3), e203976. https://doi.org/10.1001/jamanetworkopen.2020.3976
Li, Z., Chen, D., An, Y., Chen, C., Wu, L., Chen, Z., Sun, Y., & Zhang, X. (2020). Flexible and anti-freezing quasi-solid-state zinc ion hybrid supercapacitors based on pencil shavings derived porous carbon. Energy Storage Materials, 28, 307–314. https://doi.org/10.1016/j.ensm.2020.01.028
Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2020). Focal Loss for Dense Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(2), 318–327. https://doi.org/10.1109/TPAMI.2018.2858826
Liu, B., Zheng, D., Jin, Q., Chen, L., & Yang, J. (2019). VFDB 2019: A comparative pathogenomic platform with an interactive web interface. Nucleic Acids Research, 47(D1), D687–D692. https://doi.org/10.1093/nar/gky1080
Liu, J., Lichtenberg, T., Hoadley, K. A., Poisson, L. M., Lazar, A. J., Cherniack, A. D., Kovatich, A. J., Benz, C. C., Levine, D. A., Lee, A. V., Omberg, L., Wolf, D. M., Shriver, C. D., Thorsson, V., Hu, H., Caesar-Johnson, S. J., Demchok, J. A., Felau, I., Kasapi, M., … Mariamidze, A. (2018). An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, 173(2), 400-416.e11. https://doi.org/10.1016/j.cell.2018.02.052
Metlay, J. P., Waterer, G. W., Long, A. C., Anzueto, A., Brozek, J., Crothers, K., Cooley, L. A., Dean, N. C., Fine, M. J., Flanders, S. A., Griffin, M. R., Metersky, M. L., Musher, D. M., Restrepo, M. I., & Whitney, C. G. (2019). Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. American Journal of Respiratory and Critical Care Medicine, 200(7), e45–e67. https://doi.org/10.1164/rccm.201908-1581ST
Mi, H., Muruganujan, A., Ebert, D., Huang, X., & Thomas, P. D. (2019). PANTHER version 14: More genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Research, 47(D1), D419–D426. https://doi.org/10.1093/nar/gky1038
Neese, F. (2018). Software update: The ORCA program system, version 4.0. WIREs Computational Molecular Science, 8(1). https://doi.org/10.1002/wcms.1327
Perez-Riverol, Y., Csordas, A., Bai, J., Bernal-Llinares, M., Hewapathirana, S., Kundu, D. J., Inuganti, A., Griss, J., Mayer, G., Eisenacher, M., Pérez, E., Uszkoreit, J., Pfeuffer, J., Sachsenberg, T., Y?lmaz, ?., Tiwary, S., Cox, J., Audain, E., Walzer, M., … Vizcaíno, J. A. (2019). The PRIDE database and related tools and resources in 2019: Improving support for quantification data. Nucleic Acids Research, 47(D1), D442–D450. https://doi.org/10.1093/nar/gky1106
Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987–992. https://doi.org/10.1126/science.aaq0216
Rajkumar, R. P. (2020). COVID-19 and mental health: A review of the existing literature. Asian Journal of Psychiatry, 52, 102066. https://doi.org/10.1016/j.ajp.2020.102066
Rambaut, A., Drummond, A. J., Xie, D., Baele, G., & Suchard, M. A. (2018). Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7. Systematic Biology, 67(5), 901–904. https://doi.org/10.1093/sysbio/syy032
Richards, G. (2018). Cultural tourism: A review of recent research and trends. Journal of Hospitality and Tourism Management, 36, 12–21. https://doi.org/10.1016/j.jhtm.2018.03.005
Routy, B., Le Chatelier, E., Derosa, L., Duong, C. P. M., Alou, M. T., Daillère, R., Fluckiger, A., Messaoudene, M., Rauber, C., Roberti, M. P., Fidelle, M., Flament, C., Poirier-Colame, V., Opolon, P., Klein, C., Iribarren, K., Mondragón, L., Jacquelot, N., Qu, B., … Zitvogel, L. (2018). Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors. Science, 359(6371), 91–97. https://doi.org/10.1126/science.aan3706
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Schmid, P., Adams, S., Rugo, H. S., Schneeweiss, A., Barrios, C. H., Iwata, H., Diéras, V., Hegg, R., Im, S.-A., Shaw Wright, G., Henschel, V., Molinero, L., Chui, S. Y., Funke, R., Husain, A., Winer, E. P., Loi, S., & Emens, L. A. (2018). Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer. New England Journal of Medicine, 379(22), 2108–2121. https://doi.org/10.1056/NEJMoa1809615
Siegel, R. L., Miller, K. D., & Jemal, A. (2019). Cancer statistics, 2019. CA: A Cancer Journal for Clinicians, 69(1), 7–34. https://doi.org/10.3322/caac.21551
The UniProt Consortium. (2019). UniProt: A worldwide hub of protein knowledge. Nucleic Acids Research, 47(D1), D506–D515. https://doi.org/10.1093/nar/gky1049
Thorsson, V., Gibbs, D. L., Brown, S. D., Wolf, D., Bortone, D. S., Ou Yang, T.-H., Porta-Pardo, E., Gao, G. F., Plaisier, C. L., Eddy, J. A., Ziv, E., Culhane, A. C., Paull, E. O., Sivakumar, I. K. A., Gentles, A. J., Malhotra, R., Farshidfar, F., Colaprico, A., Parker, J. S., … Mariamidze, A. (2018). The Immune Landscape of Cancer. Immunity, 48(4), 812-830.e14. https://doi.org/10.1016/j.immuni.2018.03.023
Torre, L. A., Trabert, B., DeSantis, C. E., Miller, K. D., Samimi, G., Runowicz, C. D., Gaudet, M. M., Jemal, A., & Siegel, R. L. (2018). Ovarian cancer statistics, 2018: Ovarian Cancer Statistics, 2018. CA: A Cancer Journal for Clinicians, 68(4), 284–296. https://doi.org/10.3322/caac.21456
Verity, R., Okell, L. C., Dorigatti, I., Winskill, P., Whittaker, C., Imai, N., Cuomo-Dannenburg, G., Thompson, H., Walker, P. G. T., Fu, H., Dighe, A., Griffin, J. T., Baguelin, M., Bhatia, S., Boonyasiri, A., Cori, A., Cucunubá, Z., FitzJohn, R., Gaythorpe, K., … Ferguson, N. M. (2020). Estimates of the severity of coronavirus disease 2019: A model-based analysis. The Lancet Infectious Diseases, 20(6), 669–677. https://doi.org/10.1016/S1473-3099(20)30243-7
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
Wishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., Sajed, T., Johnson, D., Li, C., Sayeeda, Z., Assempour, N., Iynkkaran, I., Liu, Y., Maciejewski, A., Gale, N., Wilson, A., Chin, L., Cummings, R., Le, D., … Wilson, M. (2018). DrugBank 5.0: A major update to the DrugBank database for 2018. Nucleic Acids Research, 46(D1), D1074–D1082. https://doi.org/10.1093/nar/gkx1037
Wu, J. T., Leung, K., & Leung, G. M. (2020). Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: A modelling study. The Lancet, 395(10225), 689–697. https://doi.org/10.1016/S0140-6736(20)30260-9
Yuan, J., Zhang, Y., Zhou, L., Zhang, G., Yip, H.-L., Lau, T.-K., Lu, X., Zhu, C., Peng, H., Johnson, P. A., Leclerc, M., Cao, Y., Ulanski, J., Li, Y., & Zou, Y. (2019). Single-Junction Organic Solar Cell with over 15% Efficiency Using Fused-Ring Acceptor with Electron-Deficient Core. Joule, 3(4), 1140–1151. https://doi.org/10.1016/j.joule.2019.01.004
Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., Wu, Q., Merler, S., Viboud, C., Vespignani, A., Ajelli, M., & Yu, H. (2020). Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science, 368(6498), 1481–1486. https://doi.org/10.1126/science.abb8001
???????? (Marchenko), ?. (Roman) ?. (Aleksandrovich), ????????? (Chendylova), ?. (Larisa) ?. (Valer’yevna), ??????????? (Karetnikova), ?. (Natal’ya) ?. (Viktorovna), ??? (Pen), ?. (Robert) ?. (Zus’yevich), & ????????? (Alashkevich), ?. (Yuriy) ?. (Davydovich). (2018). PROPERTIES OF THE REFINER MECHANICAL PULP FROM FLAX SHIVE. Chemistry of Plant Raw Material, 4, 247–253. https://doi.org/10.14258/jcprm.2018043927
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