IS 310 Semester Project - Erol Bratt

Introduction:

When looking into culture there are many details that go into what makes up someone’s “culture” and the role and identity of certain things that happen to them in the world. For my project, I want to focus on the role of school and how it has changed over the years to display the change/ shift in culture specifically in the United States. I chose to work in schools, because almost everyone in the United States has attended School, whether it be our friends, colleagues, family members or even a random person walking down the street, which makes it a very interesting topic to work on. Because schools have been around for so long, there are bound to be shifts in our education, which could have either helped or hurt our education, but one thing remains constant that it tells us something about culture. In addition to changes over the years, there have also been many key events that have happened which have caused a change in our education, resulting in perhaps a culture change. One thing I aim to focus on is the social norms that we can learn from the curriculum changes, whether or not certain classes or courses are more valuable than others, and from this I can get an understanding of what jobs were like during this time, and whether that had a shift or change. From understanding the course and classes change, I can draw inferences to certain events that may have happened in the world, and see if that has changed the education system, to better prepare students for certain events. These are all certain analyses I would take to get a better understanding of how culture and “Non-Material” culture in specific, has changed through the education system.

Data Collection and Curation:

When looking into education, there is all sorts of data that is available for people to use and which can tell a story. One thing I chose to focus on was curriculum, and how it changed from past years to current. In order to do this I had webscarped data from a “IES NCES” National Center for Educational Statistics, which gave basic graduation requirements for each of the 50 states, however not all were included. While at first, I had webscraped the data, the webscrape did not completely work out so I instead manually added certain states to my data, where the web scraping did not work properly

To give an idea of what the data looked like in the website:

My 1993- CSV file:

61 rows, 8 columns,

Variables: State, All Courses (Credits), English/ Language Arts, Social Studies, Math, Science, PE, Electives.

The units for this data are in Carnegie credits, which is a common unit that is used in America which shows the amount of time a student has spent studying a particular subject. This dataset was not very difficult to create, aside from the difficulty in web scraping, but doing it manually was not hard at all, because of how uniform the data was, and how it was nicely labeled. Another interesting thing about this data, is that as you can see, certain states are listed multiple times, this is because for some states, there were different diplomas that a student could get for example, “College Preparatory” where the student would have to take more classes. This gives us insight into the norms that were given during this time, where some kids could be possibly viewed as “more intelligent” therefore, they will take harder classes.

2023 Graduation Requirements Dataset:

40 rows, 11 Columns.

Variables: State, English/Language, Math, Science, Social Science, Elective, Unique Categories, Language, Computer, PE/Health, Arts?

These units are also Carnegie units. This dataset was much more difficult to create, because as time has gone on there is not as much of a standard credit hour for each state, actually most individual highschools have different credit hours required. This adds to the analysis because it shows how education is very different now depending on the highschool, where some may specialize in certain things, and there are no technical “standard” credits required compared to 1993. For this data I had used the averages of the highschools in that particular state, so I could get the best idea of what the “Standard” would look like. Another important aspect of this data, is that there are more variables than the 1993, this shows how there are more courses available for the student. In addition, the variable, “Unique Categories” was necessary, because for many states, the requirements had classes like “Finance” or “Online Classes” where if I were to include all of those variables, it would have skewed some of the results. The 2023 dataset was much more dense than the 1993, and took a lot more time to create, but even though this was the case, this fact gives valuable insight.

Other Scholarly Articles Interested in my Concept:

While it was relatively difficult to find other articles that look to analyze the same data as my current project. There are some articles that discuss the standardization of Mathematics and English Language Arts instruction. For this article the author used “Teachers’ use of aligned curricula, by grade band and subject 2020-2021.” The data claims that there is a “standard” curriculum in the United States, and it is analyzing how many people actually used this curriculum.

This data collection would be much different than mine, this data is most likely collected through a survey of teachers reports, meanwhile mine uses true metrics to gain an idea of what a curriculum could look like. My project aims to focus more on analyzing the difference and change of curriculum, while this project attempts to look at how the standard curriculum in the United States works and if it is being enforced. Because our projects are different there is going to be a large difference in the data collection. I assume this project looked through the survey reports and classified the responses into different groups, and compared those responses through percentages. This is somewhat similar to my project, where we grouped certain categories and compared them. Also, there was most likely no web scraping to be done for this project, but this is to be expected since it is a surveyed response. It is difficult to compare the data collection of my project to this one because of the different research questions, however, it can give a basic idea of how I could have gone about my project, and specifically the data collection aspect.

Data Analysis:

When looking at my first Dataset, of subjects required for graduation requirements, I first created a barchart of the 1993 Graduation Requirements which included the average over the 50 or so states.

As shown in this barchart, the highest amount of credit hours required was “Electives” and the second was “English/Language Arts.” Where Elective was at around: 6.49, and English/Language Arts was at 3.91, Math at: 2.56, Social Studies at: 2.84, Science at: 2.3, PE at: 1.315.

What does this tell us?

From this data we can see that in 1993, the US had a higher focus on the Humanities rather than STEM, when educating primary educated students. This tells us about the “Non-Material” culture going on during this time, there was a higher value on humanities in the US rather than mathematics, which can also have us build inferences to the types of jobs that people would get out of highschool being primarily in the humanities, rather than STEM. The “Non-Material” culture would be the idea that the US valued the Humanities more in education, which can mean that the US valued reading, writing, history for the youth more than the other subjects.

Another interesting takeaway is the amount of electives that students got to take. This number seems fairly high which is interesting as well. We can assume that since the main focus was towards the humanities the electives were also more focused towards those as well, rather than STEM. We also have to take into consideration that since this was 1993, there were not many computers or technology for the wide access of people. Ideally I believe these electives were things like cooking, and woodworking, which could be helpful for things outside of school. This could point in the direction that students were not necessarily pressured into going to college after highschool, and they could use their elective skills to help them with other jobs, and maybe vocational jobs, which is interesting because certain states had different requirements for vocational jobs. Which also shows the “Non-Material” culture and the general belief that most people should work vocational jobs, or that they are maybe more important than STEM related fields.

From the 2023 dataset, we can see the growth in Math and Science and STEM related fields. Another interesting thing to look at is the amount of different categories that are required, showing the growth in education, and the growth in jobs throughout the US. This shows apparent cultural change, because the old ideals of Humanities being very important, and vocational jobs being a high norm, are no longer there. Instead the US has shifted into being more accepting of different and unique jobs. Because there are more unique jobs and broader subjects, it shows a cultural shift in the acceptance of our youth, it shows that students are able to have more freedom to work in the areas that they want to without being discriminated against, but instead follow their true passion. This point is also added on to by, the fact that this is a highschool graduation requirements because usually highschool is more of a broad education system where a student gets to learn all of the basic subjects in the world, but now highschools are able to narrow the focus for students where they will be able to focus on their true passions by taking more unique courses, when before in 1993, this was not so much the case. There could be many reasons for this as well, one reason could be that highschools hope to prepare the students for college, when they will have to choose a specific subject to focus on, it could be because college classes are getting harder or because highschools aim to help the student pick a correct major for themselves, and it is something that they are really interested in. All of these ideas show the shift in cultural norm where it allows for the youth of America to have more freedom in what they plan to do later on in life.

One topic to recognize in more depth is the large increase in the STEM subjects (Math and Science) From our data we can see that the average credits from 1993, math: 2.56, science: 2.3 to 2023, math: 3.4375, science: 3.125, have increased fairly drastically. It is important to consider why this may have taken place, is the job market for STEM majors getting larger? The answer to this question is most likely yes, because if highschools aim to educate students in the STEM majors more, then there must be more demand for STEM in our society, implying the shift in cultural norm. Another question we can ask is why are there more jobs in STEM? One thing to look into is key events that have happened in the United States, one major event is COVID-19, which had a large impact on practically everyone's lives. COVID-19 is a disease, which means things like medicine and the understanding of disease have grown since COVID-19, and subjects like Science are important in understanding those concepts. Science especially has most likely had a growth in the job market since COVID-19, which could be why the education system wants to focus on science. The growth in science and medicine in the education system, shows how culture has changed throughout the years, because it shows what our society values as important, and the level of that importance.

Other Scholarly Analysis:

These are the key-findings from the other article I referenced, discussing the standardization of curriculum. While this article doesn’t discuss the cultural changes there are some similarities to my analysis and this one. Both analyses look at specific subjects and how they have been changed or impacted, to get a sense of how the curriculum has changed. Also, while this article doesn’t look at cultural change, it does have analysis like “standards-aligned materials are rising” where the author looks at how the norms have changed in the United States, specifically in education. From this the author could potentially make cultural inferences as well, but this is not the main idea of their article.

Analysis Accuracy:

In this section, I am discussing the reasoning for these analyses, and why these certain analyses can be made. The main purpose of my analysis was to look at “Non-Material” Culture. Ways “Non-Material” Culture can be described from wikipedia: “Non-material culture includes ideas, beliefs, social roles, rules, ethics, and attitudes of a society. Non-material culture does not include any physical objects or artifacts.” For my project I chose to look at these ideas and see how the change in education changed these, mostly I am looking at beliefs and social roles, because as shown above these are things that education has influenced and changed.

Citation:

“Material Culture.” Wikipedia, Wikimedia Foundation, 9 Mar. 2024, en.wikipedia.org/wiki/Material_culture.

Conclusion:

This project has been extremely helpful in understanding culture, the big picture of culture and ways to collect, analyze and use data related to culture. One of the most important ideas when working with culture is making a clear and defined research question, because without one it is very difficult to create data to work with. Once the research question is created it is important to find data that can work with the question. This part of the process I find interesting because there are many things that can impact culture, and many ways to make inferences from culture, so the data available is almost limitless. However, it is still important to find data that is relevant specifically to the research question, because it will make the analysis much easier. Overall, working with culture is something that I find very interesting because of the many options available to work with, but it is also a difficult topic to understand.

From my analyses of how the change in the education system shows the “Non-Material” culture shift in the United States, we have many key take-aways. One of the most important take-aways: The shift in education towards the STEM subjects. We can make this inference because of the curriculum changes from 1993 to 2023, and the large increase in math and science related courses. This is a clear indication of a shift in norms and beliefs, from before where school was focused on the humanities, and now there is a balance between the two. Because of this we can make inferences about how jobs have changed overtime, and the demand in the job market, which can show us what our society views as valuable or important. In our analysis we found that the job market for STEM related jobs is increasing, because the amount of education is growing for those topics, this shows that STEM jobs are becoming much more important in today's society, and the idea of science and technology is growing and becoming much more valuable for the common civilian. In addition, another take-away is looking into the key-events that could have created this cultural change. One event in particular was COVID-19, where it made the world question what we know about modern medicine and science as a whole. COVID-19 most likely had an impact on the curriculum, in focusing towards the STEM majors. The final takeaway was looking at the “Variables” for the 2023 Graduation Requirements dataset, we found that there were more variables than 1993, because the curriculum in highschools has expanded, and there are more courses for students to choose from. This shows the cultural shift to where students are allowed to have more freedom in their education, and choose what subjects they would like to focus on, rather than being told what they have to learn. Overall, the education system is a great indicator in looking at how culture has changed throughout the United States over time.

Works Cited:

Kaufman, Julia H., Sy Doan, and Maria-Paz Fernandez, The Rise of Standards-Aligned Instructional Materials for U.S. K–12 Mathematics and English Language Arts Instruction: Findings from the 2021 American Instructional Resources Survey. Santa Monica, CA: RAND Corporation, 2021. https://www.rand.org/pubs/research_reports/RRA134-11.html

“Material Culture.” Wikipedia, Wikimedia Foundation, 9 Mar. 2024, en.wikipedia.org/wiki/Material_culture.

“Digest of Education Statistics, 1993.” National Center for Education Statistics (NCES) Home Page, a Part of the U.S. Department of Education, nces.ed.gov/programs/digest/d96/d96t152.asp. Accessed 13 May 2024.

IS310 Project Reflection - Erol Bratt

Initial Project Idea:

For the beginning of my reflection on my project, I wanted to start with my initial project proposal. At first, I wanted to center my idea on how covid-19 had changed technology, and cultural impacts could be seen from this. This became my first problem, because the topic itself did relate to culture, however, the idea of looking at technological impacts made it very difficult to actually judge the impacts of culture on society. Also, the scope of this research idea was quite large, and there would be many things that I would need to look at, in order to get good inferences from my data. This portion of the project made me realize the importance of looking at your research question, and making a good research question, because this will allow for the data collection and analysis portion of the project to become much easier. My biggest takeaway from the initial project proposal was creating a good research question. For my Mid-Semester project proposal, I had changed my research question, and wanted to focus directly on COVID-19 and cultural impacts. From this research question, I had chosen to look at education and religion as my main areas of focus within determining cultural change. I had generated religious datasets that showed where and what religions were being oppressed during covid, however, this dataset was not the best in applying it to the judgment of cultural change. With my Mid-Semester Project proposal, I ran into two new problems that I had needed to review and understand. The first issue was the scope of the project, looking at both Religion and Education to judge overall Culture, was a very large project that would take a lot of time, and a lot of data. Also, with having such a large scope, it could be difficult to make inferences for my analysis. The other issue I came across, was my research question was looking at overall culture, not anything in specific, which only added to my scope problems. So for my final project design, I wanted to hopefully use those mistakes and make it so my project was more achievable. I had narrowed my focus down to only Education, and I wanted to learn more about “non-material” culture in specific, so I would be able to draw purposeful and meaningful conclusions. While my final project is not very close to my initial project much, I had learned from my mistakes in previous attempts and hopefully I came up with an outcome that could have a narrower scope, but can still tell a story about culture through the education system.

Why my Topic? / What in class influenced me and helped me?

For my project, I wanted to look at education, because I figured it would be a topic that everyone could relate to, and find interest in. I am also interested in the education system a lot because I feel it dictates how the next generation will impact the world for years to come, also I think in general the education system is very important. One lesson I found useful in picking this topic was, “Critical Cultural Data Explorations” . This lesson talked about power structures and the hierarchies within datasets. I found this lesson to be extremely useful because it taught me that while all data is useful, some data is more valuable to telling a story. In my case, I found that the education system would be more valuable in telling a story about the change in “non-material” culture, in relation to beliefs and norms about our society, than something like music, however, this is just my opinion, but this lesson helped me realize this. Once I found my proper research question, and it was something that I felt passionate about, and I felt had value behind it, I needed to create datasets. One group activity I found useful was “Build your own dataset!” because this is what I had to do for the project. This lesson was very useful in helping me understand what variables to use and how I could group variables together. For example, in my 2023 dataset, this dataset was fairly difficult to create because of how unique certain states are, and how many different requirements they have. This lesson helped me realize I could create a “Unique Categories” variable in my dataset and not have to list out individual courses, and there is still value behind “Unique Categories” in indicating the way certain states want students to learn. Overall, this class was super useful in helping me understand the data collection process but also understand how to properly answer a question and tell a story through data, and specifically culture and what it means for the world.