Article Sidebar

Submitted
March 12, 2025
Published
August 30, 2025
Download
Download PDF
Statistic
Read Counter : 123

Main Article Content

Abstract

This study investigated AI readiness using a quantitative descriptive design with a sample of 130 faculty members. Data from a self-constructed questionnaire were analyzed using SPSS 27 and SmartPLS 4.0 for statistical treatment. Anchored on grit theory, the results show that the faculty members have a high level of AI readiness in terms of wellbeing and mental health, changing skill requirements, job automation and displacement, and low level of privacy issues. The independent samples t-test conducted to compare the AI readiness of faculty members aged 18 – 44 years and 45 – 64 years showed that younger faculty members were more ready for AI technologies than older faculty members. The Mann-Whitney U-test results and Cohen’s effect size revealed a significant difference in AI readiness for Protestants and non-Protestants, with Protestants having a higher level of readiness than their counterparts. On gender, the females had a higher level of AI readiness than the males. In terms of educational levels, postgraduate degree faculty members had a higher level of AI readiness than those with up to bachelor’s degrees.

Keywords

Artificial intelligence AI Readiness faculty adventist institutions higher education

Article Details

License

Copyright (c) 2025 Mahlon Juma

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite
Juma, M. (2025). Faculty Artificial Intelligence Readiness in Adventist Higher Institutions of Learning in Sub-Saharan Africa. Pan-African Journal of Education and Social Sciences, 6(2), 130–148. https://doi.org/10.56893/pajes2025v06i02.10
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Abd-Alrazaq, A., Safi, Z., Alajlani, M., Warren, J., Househ, M., & Denecke, K. (2019). Technical metrics used to evaluate health care chatbots: scoping review. Journal of Medical Internet Research, 21(8), e13107. https://doi.org/10.2196/18301
  2. Acquisti, A., & Varian, H. R. (2005). Conditioning prices on purchase history. Marketing Science, 24(3), 367-381. https://www.jstor.org/stable/40056968
  3. Afra, S., & Alhajj, R. (2020). Early warning system: From face recognition by surveillance cameras to social media analysis to detecting suspicious people. Physica A: Statistical Mechanics and its Applications, 540, 123151. https://doi.org/10.1016/j.physa.2019.123151
  4. Agrawal, R., Majumdar, A., Majumdar, K., Raut, R. D., & Narkhede, B. E. (2022). Attaining sustainable development goals (SDGs) through supply chain practices and business strategies: A systematic review with bibliometric and network analyses. Business Strategy and the Environment, 31(7), 3669-3687. https://doi.org/10.1002/bse.3057
  5. Akos, P., & Kretchmar, J. (2017). Investigating grit as a non-cognitive predictor of college success. The Review of Higher Education, 40(2), 163-186. https://doi.org/10.1353/rhe.2017.0000
  6. Alves, P. C., Oliveira, A. D. F., & Paro, H. B. M. D. S. (2019). Quality of life and burnout among faculty members: How much does the field of knowledge matter? PLoS One, 14(3), e0214217. https://doi. org/10.1371/journal.pone.0214217
  7. An, R., & Xi, T. (2020). Research on the service design of smart campus based on sustainable strategy–taking smart canteen as an example. In Design, User Experience, and Usability. Case Studies in Public and Personal Interactive Systems: 9th International Conference, DUXU 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part III 22 (pp. 20-30). Springer.
  8. Apaydin, Ç., & Kaya, F. (2020). An analysis of the preschool teachers' views on alpha generation. European Journal of Education Studies. http://dx.doi.org/10.46827/ejes.v0i0.2815
  9. Arora, A., Jha, A. K., Alat, P., & Das, S. S. (2020). Understanding coronaphobia. Asian Journal of Psychiatry,54, 102384. https://doi.org/10.1016/j.ajp.2020.102384
  10. Arya, B., & Lal, D. S. (2018). Grit and sense of coherence as predictors of well-being. Indian Journal of Positive Psychology, 9(1), 169–172. https://doi:10.15614/ijpp.v9i01.11766
  11. Batorski, D., & Grzywińska, I. (2018). Three dimensions of the public sphere on Facebook. Information, Communication & Society, 21(3), 356-374. https://doi.org/10.1080/1369118X.2017.1281329
  12. Bessen, J. E. (2019). AI and jobs: The role of demand. NBER Working Paper No. 24235. https://doi.org/10.3386/w24235
  13. Bergamin, P., & Hirt, F. S. (2018). Who’s in charge? —Dealing with the self-regulation dilemma in digital learning environments. Knowledge Management in Digital Change: New Findings and Practical Cases, 227-245. https:// doi.org/10.1007/978-3-319-73546-7_14
  14. Bliss, R., & Jacobson, E. (2020). Doctor of physical therapy student grit as a predictor of academic success: A pilot study. Health Professions Education. https://doi.org/10.1016/j.hpe.2020.06.006
  15. Bodo, B., Helberger, N., Irion, K., Borgesius, F., Möller, J., van de Velde, B., Bol, N., van Es, B., & de Vreese, C. H. (2017). Tackling the algorithmic control crisis – the technical, legal, and ethical challenges of research into algorithmic agents. Yale Journal of Law and Technology, 19, 133-180
  16. Borgman, C. L. (2018). Open data, grey data, and stewardship: Universities at the privacy frontier. Berkeley Technology Law Journal, 33(2), 365-412. https://www.jstor.org/stable/10.2307/26533142
  17. Braund, A., James, T., Johnston, K., & Mullaney, L. (2020). Grit-ability: Which grit characteristics enable success for mothers entering university? Student Success, 11(1), 22+. https://doi.org/10.5204/ssj.v11i1.1457
  18. Bregman, R. (2018). Utopia for realists. Bloomsbury Publishing.
  19. Brydges, C. R. (2019). Effect size guidelines, sample size calculations, and statistical power in gerontology. Innovation in aging, 3(4), igz036. https://doi.org/10.1093/geroni/igz036
  20. Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. WW Norton & Company.
  21. Bughin, J., Hazan, E., Lund, S., Dahlström, P., Wiesinger, A., & Subramaniam, A. (2018). Skill shift: Automation and the future of the workforce. McKinsey Global Institute, 1, 3-84.
  22. Caza, A., Caza, B. B., & Baloochi, M. E. (2020). Resilient personality: Is grit a source of resilience? In Research Handbook on Organizational Resilience. Edward Elgar Publishing. https://doi.org/10.4337/9781788112215
  23. Caton, M. T. (2020). The impact of spirituality, social support, and self-esteem on the resilience of Haitian nurses: Implications for nursing education. Archives of Psychiatric Nursing. https://doi.org/10.1016/j.apnu.2020.08.006
  24. Chang, J., & Lu, X. (2019, August). The study on students' participation in personalized learning under the background of artificial intelligence. In 2019 10th International Conference on Information Technology in Medicine and Education (ITME) (pp. 555-558). IEEE.
  25. Chen, M., & Li, X. (2018, November). Relevance-based automated essay scoring via hierarchical recurrent model. In 2018 International Conference on Asian Language Processing (IALP) (pp. 378-383). IEEE.
  26. Chui, M., Manyika, J., & Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly.
  27. Clark, L. T., Lanners, T., Blecha, M., Lanners, H., & Eskitch, P. (2019). Develop grit: How do you develop grit in the student who folds under pressure? American Music Teacher, 68(4), 8–10.
  28. Crane, A., DaCosta, A., Webbe, F., & Logalbo, A. (2020). A-10 Grit predicts depression, anxiety, and subjective cognitive complaints despite normal cognitive performance in college athletes. Archives of Clinical Neuropsychology, 35(5), 606-606. https://doi.org/10.1093/arclin/acaa036.10
  29. Cui, Q., Gong, Z., Ni, W., Hou, Y., Chen, X., Tao, X., & Zhang, P. (2019). Stochastic online learning for mobile edge computing: Learning from changes. IEEE Communications Magazine, 57(3), 63-69.
  30. Culnan, M. J., & Williams, C. C. (2009). How ethics can enhance organizational privacy: lessons from the ChoicePoint and TJX data breaches. MIS Quarterly, 673-687. https://www.jstor.org/stable/20650322
  31. Dale, G., Sampers, D., Loo, S., & Green, C. S. (2018). Individual differences in exploration and persistence: Grit and beliefs about ability and reward. PLoS ONE, 13(9), 1–17. https://doi.org/10.1371/journal.pone.0203131
  32. Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023, September). The impact of ChatGPT on higher education. Frontiers in Education, 8 (2023): 1-2, https://doi.org/10.3389/feduc.2023.1206936
  33. Dhiman, S. (2020). More than happiness: A stoic guide to human flourishing. The Palgrave Handbook of Workplace Well-Being. Palgrave Macmillan
  34. Drugas, M. (2022). Screenagers or "Screamagers"? Current perspectives on generation alpha. Psychological thought,15(1), 1.
  35. Duckworth, A. (2016). Grit: The power of passion and perseverance. Scribner.
  36. Duckworth, A., Peterson, C., Matthews, M., & Kelly, D. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92, 1087–1101. https:// doi:10.1037/0022-3514.92.6.1087 PMID: 17547490
  37. Duckworth, A., & Quinn, P. (2009). Development and validation of the short grit scale (Grit–S). Journal of Personality Assessment, 91(2), 166–174. https://doi:10.1080/00223890802634290 PMID: 19205937
  38. Dweck, C. S., Walton, G. M., & Cohen, G. L. (2014). Academic tenacity: Mindsets and skills that promote long-term learning. Bill & Melinda Gates Foundation.
  39. Eskreis-Winkler, L., Shulman, E. P., Beal, S. A., & Duckworth, A. L. (2014). The grit effect: Predicting retention in the military, the workplace, school and marriage. Frontiers in Psychology, 5, 36. https://doi.org/10.3389/fpsyg. 2014.00036 PMID: 24550863
  40. Louw, E. (2023, September 7). Ministry and artificial intelligence: The new frontier. Ministry Magazine, 6 – 10. https://www.ministrymagazine.org/archive/2023/09/Ministry-and-artificial-intelligence
  41. Fang, J. W., Chang, S. C., Hwang, G. J., & Yang, G. (2021). An online collaborative peer-assessment approach to strengthening pre-service teachers’ digital content development competence and higher-order thinking tendency. Educational Technology Research and Development, 69, 1155-1181. https://www.jstor.org/stable/10.2307/27285760
  42. Figueiro, M., & Overington, D. (2016). Self-luminous devices and melatonin suppression in adolescents. Lighting Research & Technology, 48(8), 966-975. https://doi.org/10.1177/1477153515584979
  43. Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological forecasting and social change, 114, 254-280.
  44. Fu, C., Jiang, H., & Chen, X. (2021). Big data intelligence for smart educational management systems. Journal of Intelligent & Fuzzy Systems, 40(2), 2881-2890. https://doi.org/10.3233/JIFS-189328.
  45. Grams, D. (2018). A quantitative study of the use of DreamBox learning and its effectiveness in improving math achievement of elementary students with math difficulties (Doctoral dissertation, Northcentral University). https://www.proquest.com/dissertations-theses/quantitative-study-use-dreambox-learning/docview/2101364451/se-
  46. Hatzius, J., Briggs, J., Kodnani, D., & Pierdomenico, G. (2023). The potentially large effects of artificial intelligence on economic growth. https://www.key4biz.it/wp-content/uploads/2023/03/.pdf
  47. Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. Guilford Publications
  48. Hill, P., Burrow, A., & Bronk, K. (2016). Persevering with positivity and purpose: An examination of purpose commitment and positive affect as predictors of grit. Journal of Happiness Studies, 17(1), 257–269. https://doi.org/10.1007/s10902-014- 9593-5
  49. Hodge, B., Wright, B., & Bennett, P. (2018). The role of grit in determining engagement and academic outcomes for university students. Research in Higher Education, 59(4), 448–460. https://doi.org/10.1007/s11162-017-9474-yv
  50. Huang, R. H., & Hew, K. F. (2018). Implementing AI in education: Challenges and solutions. Education and Information Technologies, 23, 105-121.
  51. Jha, M., Kamble, N., Lenka, A., Yadav, R., Purushottam, M., Jain, S., & Pal, P. K. (2019). Sleep disturbances in patients with Huntington’s disease: A questionnaire-based study. Annals of Movement Disorders, 2(1), 9-14.
  52. Joseph, S. (2015). Positive psychology in practice: Promoting human flourishing in work, health, education, and everyday life. (2nd ed.). John Wiley & Sons Inc.
  53. Kim, K., & Kwon, K. (2023). Exploring the AI competencies of elementary school teachers in South Korea. Computers and Education: Artificial Intelligence, 4, 100137. https://doi.org/10.1016/j.caeai.2023.100137
  54. Kwet, M., & Prinsloo, P. (2020). The ‘smart’ classroom: a new frontier in the age of the smart university. Teaching in Higher Education, 25(4), 510-526. https://doi.org/10.1080/13562517.2020.1734922
  55. Lambert, S. L., & Keegan, A. (2018). Flexible work arrangements: An international review and research agenda. International Journal of Management Reviews, 20(3), 869-885
  56. Lamberton, H., Minor, L., Zeigler, D. (2019). Human Relations: Strategies for Success, (6th Ed.), McGraw-Hill Education.
  57. Laumer, S., Maier, C., Eckhardt, A., & Weitzel, T. (2016). Work routines as an object of resistance during information systems implementations: Theoretical foundation and empirical evidence. European Journal of Information Systems, 25, 317-343.
  58. Li, L., Mu, X., Li, S., & Peng, H. (2020). A review of face recognition technology. IEEE access, 8, 139110-139120. https://doi.org/10.1109/ACCESS.2020.3011028
  59. Loftus, T. J., Filiberto, A. C., Rosenthal, M. D., Arnaoutakis, G. J., Sarosi, G. A., Jr., Dimick, J. B., & Upchurch Jr, G. R. (2020). Performance advantages for grit and optimism. The American Journal of Surgery. https://doi.org/10.1016/j.amjsurg.2020.01.057.
  60. Koch, L. (2023). ChatGPT in the Classroom: Uses, Limitations, and Student and Teacher Experiences. The Journal of Adventist Education 85(3), 4-10. https:// doi.org/10.55668/jae0046
  61. Maddi, S. R., Matthews, M. D., Kelly, D. R., Villarreal, B., & White, M. (2012). The role of hardiness and grit in predicting performance and retention of USMA cadets. Military Psychology, 24, 19–28. https://doi:10.1080=08995605.2012.639672
  62. Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P., & Dewhurst, M. (2017). A future that works: AI, automation, employment, and productivity.McKinsey
  63. Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., ... & Sanghvi, S. (2017). Jobs lost, jobs gained: Workforce transitions in a time of automation. McKinsey Global Institute, 150(1), 1-148.
  64. McClain, C., Faverio, M., Anderson, M., & Park, E. (2023). How Americans view data privacy. Pew Research Center.
  65. McCrindle, M., & Fell, A. (2020). Understanding Generation Alpha. McCrindle Research Pty Ltd.
  66. Miles, D. A. (2017). A taxonomy of research gaps: Identifying and defining the seven research gaps. Doctoral student workshop: finding research gaps-research methods and strategies. file://Miles2017.pdf
  67. Mirnig, A. G., Stollnberger, G., & Tscheligi, M. (2018). You robot, that’s creepy: exploring the influence of robot anthropomorphism on the acceptance of robots. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI’18).
  68. Muenks, K., Wigfield, A., Yang, J. S., & O'Neal, C. R. (2017). How true is grit? Assessing its relations to high school and college students’ personality characteristics, self-regulation, engagement, and achievement. Journal of Educational Psychology, 109(5), 599.
  69. Muhamad, W., Kurniawan, N. B., & Yazid, S. (2017, October). Smart campus features, technologies, and applications: A systematic literature review. In 2017 International Conference on Information Technology Systems and Innovation (ICITSI) (pp. 384-391). IEEE.
  70. Nadeak, B. (2020). The effectiveness of distance learning using social media during the pandemic period of COVID-19: A case in Universitas Kristen Indonesia. International Journal of Advanced Science and Technology, 29(7), 1764-1772
  71. Nemmi, F., Nymberg, C., Helander, E., & Klingberg, T. (2016). Grit is associated with structure of nucleus accumbens and gains in cognitive training. Journal of Cognitive Neuroscience, 28(11), 1688–1699. https://doi.org/10.1162/jocn_a_01031
  72. Nelson, J. A. (2016). Not-so-strong evidence for gender differences in risk taking. Feminist Economics, 114–142. https://doi.org/10.1080/13545701.2015.1057609
  73. Ophir, Y., Rosenberg, H., Lipshits-Braziler, Y., & Amichai-Hamburger, Y. (2020). Digital adolescence: The effects of smartphones and social networking technologies on adolescents’ well-being. Online peer engagement in adolescence, 122-139.
  74. Pereira, A. C., & Romero, F. (2017). A review of the meanings and the implications of the industry 4.0 concept. Procedia Manufacturing, 13, 1206-1214. https://doi.org/ 10.1016/j.promfg.2017.09.032
  75. Perlis, R. H. (2013). A clinical risk stratification tool for predicting treatment resistance in major depressive disorder. Biological psychiatry, 74(1), 7-14. https://doi.org/10.1016/j.biopsych.2012.12.007.
  76. Peters, M. A. (2016). Technological unemployment: Educating for the fourth industrial revolution. Educational Philosophy and Theory, 49(1), 1–6. https://doi.org/10.1080/00131857.2016.1177412
  77. Philbeck, T., & Davis, N. (2018). The fourth industrial revolution. Journal of International Affairs, 72(1), 17-22. https://www.jstor.org/stable/10.2307/26588339
  78. Pedro, F., Subosa, M., Rivas, A.& Valverde, P. (2019). Artificial intelligence in education: challenges and opportunities for sustainable development. https://unesdoc.unesco.org/ark:/48223/pf0000366994
  79. Rahim, F. R., Widodo, A., Suhandi, A., & Ha, M. (2024). Systematic review of educational level and evaluation tools for computational thinking skill. Jurnal Penelitian Pendidikan IPA, 10(2), 54-61.
  80. Rainie, L. (2018). How Americans feel about social media and privacy. Pew Research Center. https://www.pewresearch.org/short-reads/
  81. Rasmussen, T. H., Ulrich, M., & Ulrich, D. (2024). Moving people analytics from insight to impact. Human Resource Development Review, 23(1), 11-29. https://doi.org/10.1177/15344843231207220
  82. Reed, R. (2021). AI in religion, AI for religion, AI and religion: Towards a theory of religious studies and artificial intelligence. Religions, 12(6), 401. https://doi.org/10.3390/rel12060401
  83. Reyes, M. E. S., Aquino, K. F. B. T., De Leon, C. J. O., Muñoz, A. P. P., & Davis, R. D. (2021). Me, myself, & I: Narcissistic personality traits and selfie behavior among selected Filipinos. North American Journal of Psychology, 23(2), 255–272.
  84. Rompies, M., & Hakh, I. (2023). A review of artificial intelligence technology through contemporary Christian educational philosophy. Multidisciplinary Perspectives in Educational and Social Sciences VI. https://iksadyayinevi.com/wp-content/uploads/2I.pdf
  85. Rotman, D. (2023). ChatGPT is about to revolutionize the economy. We need to decide what
  86. that looks like. MIT Technology. https://www.technologyreview.com/
  87. Russo-Spena, T., Mele, C., & Marzullo, M. (2019). Practising value innovation through artificial intelligence: The IBM Watson case. Journal of creating value, 5(1), 11-24. https://doi.org/10.1177/2394964318805839
  88. Schimschal, S. E., Visentin, D., Kornhaber, R., & Cleary, M. (2020). Grit: A concept analysis. Issues in Mental Health Nursing, 1-11. https://doi.org/10.1080/01612840.2020.1814913
  89. Schwesig, R., Brich, I., Buder, J., Huff, M., & Said, N. (2023). Using artificial intelligence (AI)? Risk and opportunity perception of AI predict people’s willingness to use AI. Journal of Risk Research, 26(10), 1053-1084. https://doi.org/10.1080/13669877.2023.2249927
  90. Seventh-day Adventist Office of Archives, Statistics, and Research (ASTR) (2024), the General Conference of Seventh-day Adventists. https://www.adventiststatistics.org/
  91. Sigmundsson, H., Clemente, F. M., & Loftesnes, J. M. (2020). Passion, grit, and mindset in football players. New Ideas in Psychology, 59, 100797. https://doi.org/10.1016/j.newideapsych.2020.100797
  92. Southgate, E. (2021). Artificial intelligence and machine learning: A practical and ethical guide for teachers. In Digital Disruption in Teaching and Testing (pp. 60-74). Routledge.
  93. Sudina, E., Vernon, T., Foster, H., Del Villano, H., Hernandez, S., Beck, D., & Plonsky, L. (2021). Development and Initial Validation of the L2‐Teacher Grit Scale. TESOL Quarterly, 55(1), 156-184.
  94. Takeuchi, H., Taki, Y., Hashizume, H., Asano, K., Asano, M., Sassa, Y., ... & Kawashima, R. (2016). Impact of videogame play on the brain’s microstructural properties: cross-sectional and longitudinal analyses. Molecular psychiatry, 21(12), 1781-1789. https://doi.org/10.1038/mp.2015.193
  95. Tewell, E. (2020). The Problem with Grit: Dismantling Deficit Thinking in Library Instruction. portal: Libraries and the Academy 20(1), 137-159. https://doi:10.1353/pla.2020.0007.
  96. Tran, K., & Nguyen, T. (2021). Preliminary research on the social attitudes toward AI’s involvement in Christian education in Vietnam: Promoting AI technology for religious education. Religions, 12(3), 208. https://doi.org/10.3390/ rel12030208
  97. Tripathy, S., & Devarapalli, S. (2021). Emerging trend set by a start‐ups on Indian online education system: A case of Byju's. Journal of Public Affairs, 21(1), e2128. https://doi.org/10.1002/pa.2128
  98. Tseng, H., Yi, X., & Yeh, H. T. (2019). Learning-related soft skills among online business students in higher education: Grade level and managerial role differences in self-regulation, motivation, and social skill. Computers in Human Behavior, 95, 179-186. https://doi.org/10.1016/j.chb.2018.11.035
  99. Upala, M., & Wong, W. K. (2019, April). IoT solution for smart library using facial recognition. In IOP Conference Series: Materials Science and Engineering (Vol. 495, No. 1, p. 012030). IOP Publishing. https://doi:10.1088/1757-899X/495/1/012030
  100. Van der Vorst, T., & Jelicic, N. (2019). Artificial Intelligence in Education: Can AI bring the full potential of personalized learning to education? https://hdl.handle.net/10419/205222
  101. Walkington, C., & Bernacki, M. L. (2020). Appraising research on personalized learning: Definitions, theoretical alignment, advancements, and future directions. Journal of Research on Technology in Education,52(3), 235-252. https://doi.org/10.1080/15391523.2020.1747757
  102. World Economic Forum Boston Consulting Group (BCG). (2018). Towards a reskilling revolution: A future of jobs for all. In World Economic Forum.
  103. Yu, P. K. (2020). The algorithmic divide and equality in the age of artificial intelligence. Fla. L. Rev., 72, 331. https://scholarship.law.ufl.edu/flr/vol72/iss2/4
  104. Zainab, B., Zainab, B., Zakai, S., & Malik, S. (2019). Perceptions of international student mobility: A qualitative case study of Pakistan. Journal of Education and Educational Development, 6(2), 269-287. https://doi.org/10.22555/joeed.v6i2.2340
  105. Zhou, X. (2020). Application research of face recognition technology in Smart campus. In Journal of Physics: Conference Series (Vol. 1437, No. 1, p. 012130). IOP Publishing.
  106. Zolli, A., & Healy, A. M. (2012). Resilience: Why things bounce back. Free Press.