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Technology Impact on Behavior of Different Generations


This experiment will study how technology affects younger generations compared to older generations. It will also consider negative or positive effects on people in terms of their behavioral practices such as socialization, impulsiveness, innovation, ambition. The study will show that younger generations are more impulsive, abrasive, consumed, and lack correct socialization skills. They also lack ambition in schoolwork and sometimes do not even have enough motivation for going out or being engaged in physical activity.

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Relevant theories show that technology did change the behavior of each generation in all aspects of life. Notably, older generations are less affected by modern technology since they know how to act and resolve various tasks without using advanced technology. On the contrary, younger generations are often supported by technology throughout their lives. Further, older generations, such as Generation X or baby boomers, usually admit that millennials and Gen-Zers are overusing technology (Hayes et al., 2016). For millennials, it may sometimes be complicated to study and handle specific new types of technology that help them in various fields of their jobs (Parsons et al., 2019). At the same time, baby boomers usually know how to use technologies, but may have some problems discovering their particular features. Further, Generation Z is a bit dependant on technology, which can potentially be a drawback for their focus and willpower (Pae & Lehmann, 2003). Therefore, due to such contradictory data, there is a need for further study of these issues.


The Chi-square test method was used to conduct the study. The purpose of this study is to find out why there are such vast disparities between generations and why technology influenced each one. This research is essential for each generation to discover how technology affects people of different age groups, and how it influences their everyday lives. For example, a baby-boomer may need an explanation of why his/her daughter lets her child play on a smartphone during a family dinner. It may happen because when baby boomers were young, they did not have similar technology.

Nonetheless, nowadays, younger generation mothers know that such an approach will keep their children busy while they socialize with family. The studies show certain things are lacking in younger generations. These are decreased ability for socialization and spending time outdoors, and obsessiveness with games. On the opposite, for most older generations, technology can be confusing. This experiment will investigate whether technology affects younger generations more compared to older generations. Besides, the study will discover whether there is a negative impact of technology on people’s behavior – their socialization, impulsiveness, innovation, ambition. It will also study what types of technology are usually utilized by different generations and the effects it has. The study will prove that younger generations are affected more significantly in terms of socialization than older generations. Older generations will show more socialization skills, less impulsiveness, and more ambition than younger generations using technology. Furthermore, the study will show that owning technology at different ages plays a significant role in forming personality.


The two Chi-square test variables taken were generations and behavior. Therefore, the observed and expected changes in behavior, such as concentration, socialization, and impulsiveness in millennials, Xennials, and Gen-Z generations, were analyzed. The total number of participants was 590, with 70 Xennials, 284 millennials, and 236 Gen-Zers. Thus, 445 participants showed changes in behavior under the impact of technology, and 145 participants did not indicate any differences. Among them, 55 Xennials, 239 millennials, and 151 Gen-Zers demonstrated alterations in behavior (Category 1). At the same time, 15 Xennials, 45 millennials, and 85 Gen-Zers did not reveal shifts in behavior under the influence of the technology (Category 2). The expected values of Category 1 were 52.8 for Xennials, 214.2 for millennials, and 178 for Gen-Zers. The expected values of Category 2 were 17.2 for Xennials, 69.8 for millennials, and 58 for Gen-Zers.

Further, the Chi-square alpha found was 28, 7204, which is higher than the 5, 99 standard value from the corresponding second row in the 0, 05 column of the Chi-square distribution table. Therefore, the null hypothesis was rejected, which proves the influence of technology on the behavior of all participants. Interestingly, it was found that the expected value of Category 2 was higher than the observed value for millennials.

Besides, the expected value of Category 2 was lower than the observed value for Gen-Zers. The expected value of Category 2 was also higher than the observed value for Xennials. Moreover, the expected values of Category 1 for Xennials and millennials were lower than the observed values. The expected value of Category 1 for Gen-Zers was higher than the observed. Besides, the observed numbers can be represented as a percentage. Thus, according to data collected, 78,5% of Xennials, 84,1% of millennials, and only 64% of Gen-Zers were influenced by technology.

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The results of the study proved that technology has a significant impact on all generations. Besides, the findings showed that Gen-Zers are the most stable in the face of technology, while Xennials are influenced more. At the same time, the behavior of millennials proved to be exerted by technology more than Xennials and Gen-Zers. In the initial hypothesis, it was assumed that Generation Z would be most affected by the technology, the Xennials’ demeanor was expected to be altered less, and the millennials were expected to be impacted the least.

The provided findings can be used by other scientists who do researches in this field. For example, Hayes et al. (2015), in their study, analyzed how often people in the age between 18 and 70 years and older use Facebook. Scientists have found that younger people use the platform more often than older people. Moreover, younger people spend more time on a platform and are more susceptible to its influence. Scholars also found that the younger generation was emotionally exposed to a negative attitude towards their bodies through the use of Facebook. Further, scholars investigated problems with the control of use (presumably, dependence on social networks) and with the social content of the site. The data from this study can be enriched with the evidence that, despite more frequent use, Gen-Zers’ behavior is less affected by technology than older generations.

Further, Minsu Ha and Ross H. Nehm (2016) conducted a study on the effectiveness of computer systems for correcting errors in texts. In addition to directly studying the potency of this technology, scientists wondered how much such a system can influence the occurrence of false-positive and false-negative feedback for students. In the context of this study, it is also interesting to consider how correcting technology affects different generations. In particular, it should be studied whether older generations can read and spell better than younger ones. It is also curious whether older generations spell better because they were expected to do so in their school classes.

No less unusual is the study of Jae H. Pae and Donald R. Lehmann (2003), where they examine the impact of intergeneration time on technology innovation. In particular, the scientists conclude that the time for introducing new generations of technologies “varies from 2 years for chips with dynamic random access memory (DRAM) to more than 30 years for steel production” (Pae & Lehmann, 2003, p. 1). A notice about the creation of a new generation of technology every two years suggests that representatives of all ages face scientific progress on equal terms.

In addition, the results of this study suggest that it is not necessary to draw parallels between scientific progress and the alternation of generations of people. Notably, advertisers and technology manufacturers often impose such an idea on consumers. Pae and Lehmann (2003) also note that “imitation becomes greater for subsequent technologies” (p. 1). This wording is typical for marketing campaigns that advertise, for example, the new model of the iPhone. However, similar categories cannot be applied to people, especially when the research considers how they adapt to new technologies. The discussion should focus not on being tech-savvy or not, but on the methods of interaction with technology, which will undoubtedly vary in different age groups, and each of which will have its advantages. Therefore, the issue should be studied in subsequent researches from this position since such an approach will help generations to learn from each other’s experiences.


  1. Ha, M., & Nehm, R. H. (2016). The impact of misspelled words on automated computer scoring: A case study of scientific explanations. Journal of Science Education and Technology, 25(3), 358–374.
  2. Hayes, M., Stolk-Cooke, K. V., & Muench, F. (2016). Corrigendum to “Understanding Facebook use and the psychological effects of use across generations.” Computers in Human Behavior, 56(377), 507–511.
  3. Pae, J. H., & Lehmann, D. R. (2003). Multigenerational innovation diffusion: The impact of intergeneration time. Journal of the Academy of Marketing Science, 31(1), 36–45.
  4. Parsons, Thomas D., Lin Lin, & Deborah Cockerham. (Eds.). (2019) Mind, brain, and technology: Learning in the age of emerging technologies (1st ed.). Cham: Springer International Publishing.

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