Dream Dream Dream Dream Dream Dream

For my data visualization, I wanted to track my dreams over the span of a week and see how my daily life influences what my dreams are. I decided to make my visualization in the form a bar graph and for the three types of dreams: violent, inappropriate, and slice of life, I drew the bar as something that represents the type of dream. One note is the bar graph has eight dreams because certain dreams overlapped in terms of content.

One of the slice of life dreams I had was that my credit card declined when I attempted to buy some food. It was kind of funny because I was stressing over spending too much money during that week so that dream made a lot sense to me. Another dream in that category was that I was back at my high school, it was prom, and my friends were playing in the live band. The weekend before I started tracking my dreams, I went back to my high school to see their rendition of Mamma Mia, which a LOT of my friends were in. The slice of life dreams seemed to be fairly explainable.

Since this is for a school project I’m going to skip over some of the dreams and just go straight to the violent ones. One dream that I had was that me and my sister were younger, like 10 and 8, and we were being chased through our house by a man with a gun and gas mask. To gloss over some of the more graphic details we killed him and ran. This dream came right after I watched a Call of Duty stream where in one of the campaign missions, you were a little girl trying to stop a soldier from killing her brother.

Going over my dreams, it seemed that there is a correlation to what I did that day or sometime the week before. Usually I feel like this isn’t the case. From what I remember before tracking my dreams, they had little correlation to what I did during the week. In would tend to see my friends and other people who I interact with on the daily but other than that the dreams were usually pretty random.

How Satisfied Am I With Myself?

For a week, I tracked various categories that I believe ultimately play a factor in my amount of satisfaction with myself at the end of the day. These categories covered various areas throughout my day such as my work, food intake, leisure, and sleep. While there are many aspects of the day, sometimes very specific aspects, that can affect my satisfaction with myself at the end of the day, these categories were chosen to give a more general outlook at how my satisfaction is affected by my overall day. By doing so, I can analyze the data and draw out possible connections between my satisfaction and the various categories.

I decided to use a line graph to represent the categories as it’s simple way to view multiple data set and easily point out interesting patterns, similarities, or differences, between the data. According to the visualization, I feel more satisfied with myself generally when I have spent more time doing work or studying and less time on leisure, or time outside. As expected, my satisfaction levels correspond directly with the amount of work that I am able to get done and somewhat indirectly with leisurely activities. Another interesting observation is that my satisfaction levels also seemed to correspond to the amount of sleep that I got. The more time I spent sleeping, the more I feel satisfied at the end of the day.

I’m confident that if I was to continue this project as it is into the future, the results will more or less stay the same. In order to look more in depth, I would try to find a way to observe more specific aspects of my life and how they affect my satisfaction. This project is indeed a valuable tool for self analysis as it allows one to be able to draw conclusions not solely based off of one’s opinions of themselves but rather by their actual behavior and habits.

Trinity in English 2019-11-11 03:20:49

Question: Does my external self or internal self dictate my level of confidence?

To answer my question, I chose to track my level of satisfaction with both aspects of myself. I directly recorded this information in a journal, rating each category on a scale from 1-10 (10 being highest satisfaction). For quantifying satisfaction with my physical self, I considered the following: how much I liked my outfit for that day, how I felt about my skin, how much time and effort I put into caring for my physical well-being. For tracking satisfaction with my productivity I paid attention to the following: time spent doing activities I enjoy (writing, dancing), level of focus/energy put said activities, and improvement. I chose to draw bar graphs as my visualization because it was easiest for me to understand. I’m not great with graphs and I’m especially tired of excel right now (blame bio lab). Hand drawing a qualitative graph with colored pencils kept this week’s Sunday Sketch feeling more artistic than analytical.

I expected to see direct proportionality between one category and my level of confidence for the day when analyzing my data. That’s not what I found. Instead, my level of confidence regularly split the difference between appearance and performance. So, the data answered my question indirectly; I receive confidence from difference inputs – where one aspect of my life wains in satisfaction, another can support my self-esteem. Overall, the outcome of this exercise served as a testament to balance – not placing too much stock in one aspect of life. Two data points did not demonstrate a balance between external and internal satisfaction: Saturday and Sunday’s confidence levels. One aspect was especially low on each of these days. These low-rated aspects seem to weigh down my overall confidence.

Who Has My Best Interest?

Visual Representation of Data

A question that always runs through my mind is the exact question I tracked for the week for this post: Is Emory treating me well? I never thought I would end up here so when I did I was kind of surprised myself so this was just a test to see if I really do belong here. I decided to test my social life, what I thought about throughout the week, and how full I felt each day from the food Emory provides to me. Only for the first two I noted if it was connected to me wanting to go home or was it a feeling or action that the school and my surroundings genuinely brought to me.

In conclusion I could say that Emory is doing its best and I am not miserable here and don’t think about home 24/7. Socially I am thriving and there are things set up throughout the calendar that I am interested in and looking forward to. The hardest thing about this for me was tracking my thoughts for the mental aspect and seeing if I was really excited, fake excited, or not excited at all and it was just a blank thought. I enjoyed this experiment thought because it has reassured my place here at Emory.

How Great is my Life Going?

Days with Score Above 15: Very Good Day
Days with Score Between 8-15 : Average Day
Days With Score Less than 8: Bad Day

I wanted to track the amount of times that I was performing actions that gave me a sense of comfort. These actions were to be indicative of how well the course of my week was going. Every time I would have a low count day I noticed that it was correlated to events that were making me stressed out and/or anxious. I noticed right away that the more fun or less stressed out I was, the “happier” I perceived my day to be going. I also noticed that although I wasn’t having any problems on Monday I had a low score simply for the fact that the “Monday” energy was hitting me. My “weekend” days Friday- Sunday were notably higher because I knew that I wouldn’t have to be concerned with quizzes, tests, or work.

If I were to continue this project I would have looked to make sure that even if I had personal issues during the week, I would not let them impact my mood for the day. I found this tool to be valuable for me because generally I think that most of my days are pretty terrible but being able to quantify my day with numbers helped me see that my days weren’t as bleak as I had originally anticipated. Being able to see my life as a set of bars on a graph helped me to see that I am capable of controlling how to navigate my issues, and not let them have as big of an impact on my life or of those around me.

Assignment Link: https://eng181f19.davidmorgen.org/assignments/sketches/sketch-9-data-viz-from-everyday-life/

What am I busy with?

sk9

I developed this habit of listing pending matters at the beginning of this semester after a terrible week haunted by time conflicts. To avoid over-scheduling myself as well as procrastination, I write down my everyday work on a notebook for better time management. This sketch assignment makes me realize that the notebook can also be used to trace back my daily life and identify potential patterns. Although I do not put down everything in my life, items on the notebook are usually things that occupy most of my time when I am not in class. This graph represents data from Sep. 23rd to Nov. 10th.

My Sunday to Monday is mostly occupied by academics and less time is spent studying since Wednesday because I tend to finish assignments ahead of time so that I can enjoy the rest of my free time without thinking about dues. Most of my extracurricula are scheduled on Thursday night and Friday because I do not have classes on Friday. The drop between Friday and Saturday is easy to understand – Friday nights never end on Friday.

I have thought about showing the percentage of each category, but the different amounts of free time I have make it more reasonable to record the actual numbers. For instance, my Saturday always begins in the afternoon, and I have to wake up early for classes on Tuesday and Thursday. If I were to continue this record to assess my schedule, I would use total time spent in each category instead of the number of items, since time spent on each item may range from 30 minutes to 12 hours. Except for the fact that staying up late is unhealthy, I do not see the necessity to significantly change my typical weekly schedule.

 

Assignment Link: https://eng181f19.davidmorgen.org/assignments/sketches/sketch-9-data-viz-from-everyday-life/

A Week in Life of an Emory Scholar

For this Sunday Sketch, I decided to look very closely at how four different factors affected my overall study habits at Emory. I also wanted to know what type of assignments should I complete to varying points during my day to ensure my time is being used effectively. Some tasks require lots of energy and focus while others are more simple and just need some minimal motivation. Therefore, these factors were my levels of Energy, Motivation, Focus, and Productivity. I ranged each element from 1-5, one being very low and five being very high. I then looked at how these levels fluctuated throughout my day and throughout my week and came to some interesting conclusions. 

This research was vital to me because I wanted to see what days and what times during the days would be the most suitable time to work on a particular assignment. For example, based on the data, I can conclude that my peak focus time is during breakfast. Therefore, going forward, I can aim to complete all my readings during the early breakfast time because I know I’ll be able to focus on them. In contrast, it’ll probably be best to achieve my most energy-intensive assignments during dinner time because that’s when my energy levels are typically the highest. I also was able to conclude from my data that the factors that impact my study habits are directly correlated to the number of classes I have on a given day. On Thursday, I have three-morning courses back to back, and they are all very long and rigorous courses. According to my data, I experience some of my lowest energy, focus, and motivation on Thursdays.

If I were to continue this research, I’d collect more data over more days to make my data sets more accurate. On of the judgments I had to make when documenting this data was figuring out what was important enough to record. A lot of factors impact study habits and figuring out which ones to look at were difficult. It was also hard to asses sometimes how I was feeling, and sometimes I felt my level was between two numbers, so I had to pick whichever one I was leaning towards. In another study, I would make the range larger (i.e., 1-10) so that I could obtain a more accurate level.

This project was a valuable tool in allowing me to look at when are the best convenient times to complete different types of tasks. I’m currently in the process of building out my schedule for next semester, and I will be sure to return to this data when scheduling my classes and to manage my workload.

DEPRESSION, DESPONDENCY, AND DEJECTION

The past week, for me, has been pretty depressing. Unlike the other assignments, this Sunday sketch assignment took up a significant amount of time. My goal was to simplistically quantify a subjective quantity, such as depression, based on specific categories. The five categories: loneliness, study/work, talking with family, sleep, hangouts. The results were satisfying, to say the least. The categories selected had a relatively radical influence on depression. Loneliness contributes to depression, while sleep has a neutral effect (because I would usually sleep if I was depressed). Studying, talking with family, and hanging out decreased the effect of depression for me.

I decided to use time as the unit of measurement for the categories, the greater the amount of time the greater the effect that category will have on my depressive mood. After analyzing the data collected from the past week, I could conclude that I have been in a more depressive mood at the end of the week than on weekdays. I chose to visualize the five categories in the form of a timetable as it was easier for me to quantify depression on the final scale. The final scale was a simple bar graph showcasing depression in numerical form.

The project has done a surprisingly good job. If I were to continue with this project in the future, I would’ve continued with it similarly as I did the past week, though, I would add more variables to the equation to bring about more accurate results.

Link to the assignment is here.

Image credits: https://www.theodysseyonline.com/brief-visualization-depression

Data Viz

When I started this assignment a week ago I had a question: Does the amount of time between eating and engaging in academic work effect my productivity? More specifically, should I be making more of an effort to eat before my first class?

Throughout the span of a week I kept track of the time and my perceived productivity and alertness. Some days I wouldn’t eat until a few hours into my academic work. In order to show this I entered the times in negatively. At the end I found that the more time there was between my first bite and the start of my academic day the more productive and alert I felt.

Though it will be difficult to wake up in the morning earlier in order to have time for a bite, I can see that it will be beneficial. And even if I oversleep I will try to have a banana or some sort of quick snack in my room.