Technology Addiction

By Zoey Pomroy, Daniel Stahl, Raoda Haque, Joshua Breneiser- Researchers

October 20th, 2023

Aim/hypothesis: Zoey

The purpose of our study was to find whether the younger generation of students at School Lane Charter School are more addicted to technology than the older generation. The younger generation would be the population of high school students, grades 9-12, while the older generation is the School Lane Charter staff. We hypothesize the younger generation of students at School Lane Charter School will be more likely to have an addiction to technology than the older generation of teachers and staff at School Lane Charter School. This is because the younger generation grew up using newer technology. whereas it's newer to the older generation and they grew up with a more technology-free lifestyle.

Procedure: Raoda

The participants will consist of 10 students and 10 staff at School Lane Charter School.
The method will use volunteer sampling. That will include asking people if they would like to be part of the study. If they say yes, then they can fill out the study
The procedures consist of participants filling out a survey that has Likert-style questions. There were two different surveys based on if the participant is a student or staff.
- The surveys asked about what social media apps they used, how often they spend with their family, how frequently they check their phones in different scenarios, like how often they check it before bed, and when they get a notification.
- The staff survey asked questions specifically about spending time with kids if they had any.
- Some of the social media app options differed based on which survey, for example the teacher survey asked about Tinder, and the student survey asked if the respondent had discord.
- The questions had five different options on the Likert scale. For example, if it asked about frequency, the options would be: always, frequently, occasionally, rarely, and never.

Examples of Questions Asked

Results: Daniel

In the results of our survey, we were able to find a vast variety of age groups and individuals that actively use their phones. On both surveys, the question of “How frequently do you check your phone before bed?” had similar percentages. 30% of students and teachers answered, “always,” are they on their phones before bed. As it becomes less frequent, the percentages split slightly by the rarely option being 10% in the teacher survey while the students hadn’t gotten anything below occasionally. To mirror this question, there was “how frequently do you check your phone when you first wake up?” The teacher had 60%, while the students had 30%. “How often do you look at your phone when you are trying to work (job, homework, household chores, etc)?” The students were the only ones that had a person answer 10% as always, teachers never had always.

Conclusion/implications: Josh

After looking at the results, it can be inferred that students and teachers are both addicted to their phones, but for different reasons. Students are addicted to their phones because of entertainment, shown by 100% of these participants actively using YouTube and being more likely to use their phone while trying to work. Along with this, students actively use more social media than adults. Teachers, however, use their phones for more work-related activities, since they check their notifications more than the students and are more likely to check their phone when they first wake up. The study does have a few limitations that could have influenced or skewed the results, though.

First of all, the sample of ten students is not enough to represent the entire population of students, and the same goes with the sample of ten teachers. The survey only consisted of people from School Lane. The results may have differed for people at other schools or people that do not work in a school environment. Additionally, the small sample allows each participant to represent 10% of their population, which is a huge percentage for one participant and allows them to easily influence results. The second limitation is that participants can easily lie in a survey due to not wanting to look bad or picking what they believe is the socially acceptable answer. Many people may have said they checked their phone more often because they thought it was the norm. The last limitation is that 60% of the student participants were male while 60% of the teacher participants were female, and while that is a one person difference, there is still a chance that it might’ve impacted the results in some capacity since each person is 10%. If the teachers had any kids could have affected the way the parent interacts with their phones as well. While the limitations of the study show that the results could be inaccurate, there are still some strengths that are present.

The first strength of the study comes from the age diversity of the participants. Even though the majority of students were 17 years old, the teachers range from a variety of ages and benefited from the survey as a result. Another strength is that even though the genders are mainly 60% to 40%, there’s around as many males as females and there’s not a huge difference or a dominant gender in either study.

In order for students and teachers to be less addicted to their phones, they should consider reducing their technology use throughout the day, as well as checking their phones less. In conclusion, the study shows that students are addicted to their phones, likely to entertain themselves and social media, while teachers are addicted for more productive reasons. Technology can be good or bad, and it depends on how the user will take advantage of it.