Blog #2: Relationship Between Variables: Testing Our Hypothesis

As the purpose of our project is to understand if there is a correlation between the rise in college tuition with the amount of financial aid offered to students. If a relationship exists between these two events, we hope to understand how the level of subsidies impact tuition across the United States, as well as other countries worldwide. Developing our research and going forward with factors that we believe most greatly affect our hypothesis, our research thus far supports our initial claim.

While conducting research and strategizing the most effective ways to gather information and research, we selected conceptual variables that have the potential to influence the rise in tuition prices. The variables chosen for the full model are: Average yearly Inflation in the United States, Total Financial Aid (in millions), Gross Domestic Product- GDP- (in trillions, from CPI), Expenditure of Public and Private Colleges and Universities, Median Household Income in the United States, Human Development Index (HDI). We are using the average price of tuition as our y-variable, as it is necessary to look at averages when assessing the cost of universities over time.
The variable “Total Financial Aid in US dollars” was chosen due to our curiosity related to the possibility of colleges making the average amount paid by a student the same by increasing the tuition price correlated to the increase of Aid. This was the other factor in our model that was a nonnegotiable factor; one that our model could not properly be solved without. Average inflation in the US over one year is important to our model due to the possibility of it affecting the rise in tuition costs, justifying the increase in real dollars. The fourth factor chosen for our model was GDP in trillions of dollars. We believed that if there was a serious trend in the rise of GDP, it could be a possible explanation for the rise in college tuition.We believed that an increase of a country’s economy would generate an increase in quantity demanded to attend university, justifying the increases in price.

The next factor we selected was the average expenditures of public and private colleges and universities in the US per year. This factor was chosen for our model because we assume that the more the university spends and invests, the more they expect students to pay. As students are given an increased amount of aid and as colleges and universities are given more money to spend per year, they would only adapt their budgets to have more and more money each year. Median household income was a factor we chose to incorporate into our model because we were making an assumption that if household income increased then colleges and universities would be more likely to raise tuition. If colleges and universities are assuming that median household incomes are rising then they would rationalize a raise in tuition. HDI was a factor added into our model because it is the measure of life expectancy at birth, average years of schooling per person ages 25+ and the GNI or gross national income per capita. We believed this would be important to add into our model because it is a good measure of if the number of college age citizens are actually attending college or university.
When creating our full model, we believed these factors had a high influence due to our preliminary research within the beginning stages of our work. We added additional variables that we strongly believe may explain the amount charged by colleges. We expected for all of these factors to have a positive influence in the prices of college, and for the constant to also be a positive number.
From the research conducted thus far, Total Financial Aid (in Millions) multiplied by Expenditure of Universities, and Median Household Income in the United States are significant for our model, and have the potential to explain the rise in Tuition. For every additional $1 million given in aid in the combination of financial aid and college expenditures sees an increase of .001 cents in the average price of tuition. And for every dollar increase in the median household income, the average price of College tuition in the US increases by about 29 cents. Our constant is of -8159.35.

Blog #2: Relationship Between Variables: Testing Our Hypothesis

As the purpose of our project is to understand if there is a correlation between the rise in college tuition with the amount of financial aid offered to students. If a relationship exists between these two events, we hope to understand how the level of subsidies impact tuition across the United States, as well as other countries worldwide. Developing our research and going forward with factors that we believe most greatly affect our hypothesis, our research thus far supports our initial claim.

While conducting research and strategizing the most effective ways to gather information and research, we selected conceptual variables that have the potential to influence the rise in tuition prices. The variables chosen for the full model are: Average yearly Inflation in the United States, Total Financial Aid (in millions), Gross Domestic Product- GDP- (in trillions, from CPI), Expenditure of Public and Private Colleges and Universities, Median Household Income in the United States, Human Development Index (HDI). We are using the average price of tuition as our y-variable, as it is necessary to look at averages when assessing the cost of universities over time.

The variable “Total Financial Aid in US dollars” was chosen due to our curiosity related to the possibility of colleges making the average amount paid by a student the same by increasing the tuition price correlated to the increase of Aid. This was the other factor in our model that was a nonnegotiable factor; one that our model could not properly be solved without. Average inflation in the US over one year is important to our model due to the possibility of it affecting the rise in tuition costs, justifying the increase in real dollars. The fourth factor chosen for our model was GDP in trillions of dollars. We believed that if there was a serious trend in the rise of GDP, it could be a possible explanation for the rise in college tuition.We believed that an increase of a country’s economy would generate an increase in quantity demanded to attend university, justifying the increases in price. The next factor we selected was the average expenditures of public and private colleges and universities in the US per year. This factor was chosen for our model because we assume that the more the university spends and invests, the more they expect students to pay. As students are given an increased amount of aid and as colleges and universities are given more money to spend per year, they would only adapt their budgets to have more and more money each year. Median household income was a factor we chose to incorporate into our model because we were making an assumption that if household income increased then colleges and universities would be more likely to raise tuition. If colleges and universities are assuming that median household incomes are rising then they would rationalize a raise in tuition. HDI was a factor added into our model because it is the measure of life expectancy at birth, average years of schooling per person ages 25+ and the GNI or gross national income per capita. We believed this would be important to add into our model because it is a good measure of if the number of college age citizens are actually attending college or university.

When creating our full model, we believed these factors  had a high influence due to our preliminary research within the beginning stages of our work. We added additional variables that we strongly believe may explain the amount charged by colleges. We expected for all of these factors to have a positive influence in the prices of college, and for the constant to also be a positive number.  

From the research conducted thus far, Total Financial Aid (in Millions) multiplied by Expenditure of Universities, and Median Household Income in the United States are significant for  our model, and have the potential to explain the rise in Tuition. For every additional $1 million given in aid in the combination of financial aid and college expenditures sees an increase of .001 cents in the average price of tuition. And for every dollar increase in the median household income, the average price of College tuition in the US increases by about 29 cents. Our constant is of -8159.35.

Blog #2: Undergraduate Research

At this point in my research I have looked at the texts “Transforming Feminism: Trans Feminists Speak Out,” “Trans Bodies Trans Selves,” and “Transgender History.” These books have given me basic insight into how transgender people are discussed in both feminist discourse and transgender specific spaces. They have not yet given me clear lines between feminist perspectives I wish to analyze, but they have pointed to a lot of perspectives in the modern day around transgender issues.

“Transforming Feminism: Trans Feminists Speak Out” is a Canadian text, and my research focus is transgender identities and feminism in the United States. In order to solve this problem, my faculty advisor and I decided to focus on the sections of the text which are applicable across national boundaries. One example of transnational topics include how resources for survivors of sexual assault and rape are used in relation to transgender survivors.

“Trans Bodies Trans Selves” has given me insight on how issues of gender intersect with issues of race, immigration status, and class. This text will be helpful for analyzing how trans issues fit into the future of feminism.

“Transgender History” adresses how discussions around transgender issues have evolved in the United States. A lot of the information from this text will be used to differentiate feminist perspectives both over time and by ideology.

Throughout the research process, I have found new questions to look into more closely during winter intersession as I finalize my research. One problem I have had to grapple with is how broad my research can get, and Rachel Simmon has helped me ensure I am not just reading this for the sake of completion if they won’t be helpful to the final paper. Rachel has also helped me use on campus resources to better my research process. Pace University Librarian Sarah Burns-Feyl has guided me to a number of resources I have accessed through the library.   

 

Blog #2

During this period of time, I explored obtaining the coefficients of the group, y^2=x^3-t^n x-t^n. I specifically explored the groups when n = 3 and 1. I attempted to obtain the coefficients of the group y^2=x^3-t^3 x-t algebraically, by replacing at+b for x and ct^2+dt+e for y.

This resulted in (ct^2+dt+e)^2 = (at+b)^3-(at+b)t^3-t, obtaining a^3t^3 + 3a^2bt^2 + 3ab^2t + b^3 – at^4 – bt^3 – t

By doing this, we know that c^2 = -a, e^2 = b^3, 2cd = a^3-b, 2ce+d^2=3a^2b, de=3ab^2-1

I attempted to solve for these values in maple by using the collect(simplify(equation, variable to solve for)) function to go further, since the variables cannot be simplified any further using basic algebraic methods. Maple has many useful functions that include the simplify, collect, and solve functions that allow one variable to be isolated. Then, we can set all instances of a variable, such as “c,” into what it is equal to. We know that a = -c^2, so all instances of a can be replaced with (-c^2).

I hope to continue doing this over Winter Break and apply this methodology to more complex functions. I also hope that I will be able to develop a more efficient method, possibly not using Maple, so that I can compute the larger coefficients.

Blog #2: Continuation of The Use of Lavender Aromatherapy to Reduce Test Anxiety and Improve Sleep Quality in Nursing Students

In the continuation of my undergraduate research project, The Use of Lavender Aromatherapy to Reduce Test Anxiety and Improve Sleep Quality in Nursing Students we are in the midst of recruiting individuals for our research study. Initially we were going to focus our study on the population of freshmen nursing students, however after analyzing the freshmen and sophomore nursing curriculum we have decided to also open up the study to sophomore nursing majors. Sophomore nursing majors face a lot of stress in this year of nursing. It is their first year of real nursing classes and many of the students have a hard time managing their time in order to study and get all of their projects/ papers done in time. This raises their anxiety levels and many of the students stay up all night due to this anxiety and workload. Therefore, we have officially decided to recruit sophomores in addition to freshmen nursing students for our study.

Through the course of this semester I have also learned more about the use of lavender and its effects on anxiety and sleep quality. Lavender works as an anxiolytic and as a sedative to increase relaxation and calm and help bring about sleep. It has been shown to increase time spent in deep, slow wave sleep thus improving insomnia and sleep quality. In terms of stress, lavender has been shown to reduce the physical and emotional signs of stress. This includes: lowering blood pressure and heart rate, and increasing feelings of relaxation and calmness. In addition, Lavender can also function as a pain reliever or analgesic and as an anti inflammatory agent.

The only questions in our study that we had so far was regarding our population of students that we were focusing on. However, my mentor and I discussed which population of students to focus on and decided on sophomore and freshmen nursing students.

 

 

Blog Post #2: Progress – Food Waste Education

Since my last blog update, I have been researching educational theory and STEM educational practices. Through this research, the concept of ‘Experiential’ or “Hands-on’ education has become a central theme. The premise is that experiential education is a way to supplement formal, facts-based learning with the goal of increasing the understanding of this knowledge. In this research, I assert that experiential learning does more than just increase understanding of scientific processes, but empowers learners to own and become stewards of this knowledge.

So, what does this mean for composting and food waste? Compost is a fundamentally hands-on process, but can appear abstract on paper. It is recycling in which people can become engaged through every step of the process from food to soil, and back to food. While we struggle with participation in food waste recycling, it is experiential learning of the process which can help people understand it uses and thus empower them to participate.

This project has required a great amount of collaboration with my mentor. My biggest struggle is trying to articulate and organize my ideas and findings into a paper. In my meetings with Professor Dupuis, we do brainstorming sessions on the whiteboard where these ideas flush out and take a more clear shape. She helps me recognize the connections in my ideas and in turn empowers me to investigate further. In a sense, it is much like experiential learning where engaged problem solving prompts a greater understanding of my research, and greater motivation to continue.

 

Blog Post 2: Mycobacterium bovis BCG

Throughout the semester I have been testing the growth rate as well a viability of Mycobacterium bovis BCG in several different media. Each growth curve requires a daily optical density measurement for two weeks. For weeks I kept on making new media varying up the recipe and calculations and finally about three weeks ago we might have stumbled upon a media that is suitable for M. bovis BCG growth in the presence of glutathione. I have conducted three growth curves using this media and plan on conducting a viability test by plating the cultures onto agar plates every day for 14 days.

After the viability test, I will perform an NADH assay, which will determine the relative NADH concentrations of my cultures. Running through each failed trial was frustrating but it taught me a lot about being meticulous and patient. Reading more literature was key to modifying the media. My next step would be to use transcriptomics to figure out which genes are up-regulated when M. bovis BCG is under non-replicative persistence. For this process, I would need to extract the RNA and then create a complementary DNA. Then I input the genetic information into a machine that scans and processes the genes. This would then tell me which genes are up-regulated.

One other aspect of my research also was to teach and help my other lab-mates with their own project. This gave me a better grasp of techniques needed to perform RNA extractions, feeding assays as well as inoculations.

Blog 2: Pollution and Cultures: Data Collection (China)

Survey Design

Although designing an appropriate survey is never easy, the researcher benefits a lot from the process including mistakes. Before completing the final draft, the team sent out a pilot study among a small sample of students, both in China and US, in order to improve its design.

First, the pilot study shows that too many open-ended questions might result in the low quality of answers; participants tend to skip the questions because they might be exhausted of writing, which makes the researcher aware that the non-response bias can skew the results. Meanwhile, some of the participants regard the survey as disorganized; it jumps from one topic to another and does not have a clear structure.

Since then, the researcher focuses on quantifying most the questions to avoid non-response, while maintaining the balance of quantitative and qualitative questions as the numerical data cannot reflect all the details of what the participants believe. The researcher also learns to concentrate on the issues that she wants to press on. The latest questionnaire is divided into two section: the first one will concentrate on the participants’ environmental opinions on the city where they live, whereas the second one focuses on their opinions towards global environmental protection.

 

Sample

After the pilot study, the researcher decides to focus on collecting data mainly from local students in universities at Chongqing, China, leaving the US students sample for next semester. So far, it has collected over 130 surveys across different campuses. Among them, 129 participants are Chinese native speakers, age ranging from 18 to 30, and around 56% of the participants are female. In addition, there are 48% of 113 responses claiming that they have been living in Chongqing over 4 years, while 22% of them just stay in the city between 1 to 2 years.

Accordingly, around 40% out of the 112 responses state that they just come to study in Chongqing over 1 or 2 years, while 30% have been staying in local universities at least 5 and more years. Although the participants are across disciplines, it is noted that engineering major occupies almost 50% of the participants since they mostly come from the most famous and largest Engineering-led college in the city – Chongqing University.

 

Data Analysis

Although the data collection is still processing, there are two particular results that have captured the researcher’s attention. In one of the researchers’ hypothesis, it assumes that Chinese students might favor “economic development” over “environmental protection” because China is still considered as a developing country which has to prioritize economy as its development goal. However, the survey shows that 73 out of 102 responses value environmental protection first in terms of better development in the city. When it comes to reasons, several responses suggest that the environment is the foundation for long-term development, both economically and socially. One of the participants even goes further questioning if the environmental protection cannot be promised, there is no point in advancing economy. More importantly, even for those putting economy ahead of the environment, many participants seem to agree that sustainability is the key to the future.

At the end of the survey, when it asks which one, local environment [protection] and global environment [protection], should be prioritized, 67 out of 104 responses prioritize the local environment. However, it does not mean the participants care less about environmental issues globally. In the following question, several participants associate these two factors together. Many responses also mention the term “small”, indicating that starting from fractions can eventually lead to the global environment protection. Therefore, the participants seem to believe that protecting the local environment can benefit the world globally.

Blog #2: Investigation of Combination Treatments in Breast Cancer

The goal of the research I have been doing this year is to activate the tumor suppressor Rb, in breast cancer cells. To do that we activate an enzyme called PP1, which activates Rb, by a gene silencing technique called PNUTS knockdown. So far in this research I have learned many of the techniques necessary for setting up PNUTS Knockdown. I have learned how to efficiently count and plate MCF7 breast cancer cells, as well as learned how to trypsinize cells off of plates in order to remove the cancer cells and centrifuge them to collect them.

Throughout the semester I have also learned more about the intricacies of the PNUTS KD For example, I learned that using specific antibodies we tag the proteins that are on the nitrocellulose paper and after viewing them via specific computer software (Bio-rad image software) we determine whether or not PNUTS was knocked down by comparing a portion of cancer cells that didn’t receive any treatment (controls) that knocked down PNUTS to a portion of cancer cells that did have PNUTS knocked down and if the software shows the band where PNUTS is to be lighter or less prominent then we know the knockdown was a success. Furthermore, we also look to see if the band where Actin is, is more prominent or less prominent or the same. Ideally it is the same, meaning the same amount of protein was loaded in each cell. Therefore, expression of actin serves as our loading-control.

So far we don’t have any confirmed data because the results we do have need to be replicated several times to have confidence in the accuracy of the results. However, we do have general results. For example, so far the experiments that have shown promising results regard the phosphorylation of AKT detected by the antibody AKT-473. The way we know this antibody has shown promising results is by viewing the band on the nitrocellulose paper as mentioned before and determining whether or not the band is more prominent with the treatment or less prominent and in the experiments we have carried out so far the bands for this antibody have been less prominent after the PNUTS KD and this experiment will be carried out again a number of times to ensure the results are accurate.

 

Blog 2: Continuation of Coconut and Medium Chain Triglycerides Infused with Plant Powders to Combat Bacteria

During this research I work collaboratively with my professor Dr. Rizzo for obtaining samples of surfaces and oils from shea butter, coconut oil, MCT oils, and powders. Along with the creation of the samples testing them against UV radiation is necessary in order to determine if the samples can help in the protection against harmful radiation. The results I have obtained so far are effective in my research by telling which samples are protective against radiation and also which samples fight against the three different bacteria’s being tested. There are some specific natural oils and powders when mixed in solution with coconut oil and shea butter that have had great results. However, I just received the necessary MCT oil so the results so far are based solely around the addition of coconut oil and either a powder or an oil that had constructive results from other colleague’s samples. From this point on the MCT oil will be the focus with coconut oil, powders, and other natural oils. Since the MCT oil took some time to get in I had to think of other ways to make my research successful, which is why I tested the base of shea butter and coconut oil with the different natural oils and powders as a control group to see whether or not the MCT oil will have any effect when added in. I communicated this with Dr. Rizzo and we have come up with different solutions and ways in which the research can be helpful without the MCT oil at the moment. I try to do research one to two times a week, although due to sending samples to the laboratory for testing I do have to wait a week between sending samples sometimes. Dr. Rizzo has given me great mentorship and communication throughout the process thus far, and she continues to give me great feedback and ways to improve future results for this project.

            The results concluded so far are very insightful due to seeing which oils and powders when mixed with the coconut oil and/or shea butter will have good results with the bacteria testing or UV testing. There are some natural oils that I would think would be effective against bacteria, but the results show otherwise. It is exciting to play around and try to find the perfect sample that will have the results I am looking for. From this moment on I want to see how drastically the results will change once adding the MCT oil into the samples. Along with the effects of the turmeric and maca powders with the MCT oil. Will the testing against UV radiation improve at all? Will the testing against bacteria be beneficial or no change at all? The conclusion of this research will depend solely on the MCT oil. Also, with this project I have been accepted to present at the American Chemical Society’s national meeting this spring in Orlando, Florida alongside some of my colleagues.