title: “Project3” author: “490213850 date:”University of Sydney | Data1001 | October 2019" output: html_document
library(ggplot2)
p3 <- read.csv("p3.csv")
#View(p3) Executive Summary
The aim is to understand the demographics of the student of USYD from the university sample database allow universities to know where to invest their fund in, and ways to improve the life of students. The main discovery is that the more access to canvas a student makes weekly, the better UoS mark and academic results were achieved. Hence canvas overall, seems to be benefitting students and helping them with organizing their school work.
## Size of data
dim(p3)## [1] 300 21## R's classification of data
class(p3)## [1] "data.frame"## R's classification of variables
str(p3)## 'data.frame': 300 obs. of 21 variables:
## $ Fake.Student.Identifier : int 2171 2343 1385 1985 4038 3188 3888 2650 2 3454 ...
## $ Age.at.Semester.Start : Factor w/ 4 levels "18 and under",..: 2 2 2 2 2 1 2 2 4 3 ...
## $ Domestic...international.status : Factor w/ 2 levels "Domestic","International": 1 2 1 1 2 1 2 2 1 2 ...
## $ Mode.of.Study : Factor w/ 2 levels "Full Time","Part Time": 1 1 1 1 1 1 1 1 1 1 ...
## $ UoS.Mark : int 73 71 64 69 78 88 46 51 65 83 ...
## $ Canvas.access.Week.1 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.2 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.3 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.4 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.5 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.6 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.7 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.8 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.9 : int 1 0 1 1 1 0 1 1 1 1 ...
## $ Canvas.access.Week.10 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.11 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.12 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Week.13 : int 1 0 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.Mid.semester.break: int 0 1 1 1 1 1 1 1 1 1 ...
## $ Canvas.access.STUVAC : int 0 1 1 1 1 1 1 1 1 1 ...
## $ Average : int 13 13 15 15 15 14 15 15 15 15 ...``` Summary:
Full Report
Initial Data Analysis (IDA)
I collected 300 students ( a sample) from the total population to represent and approximate roughly the entire student body of university. The limitations were that to keep it ethical, fake student profiles were used to protect the privacy of students. Hence the results could vary slightly from reality but still valid enough to make grand conclusions. The selection and variability of this data set is only representative of university of Sydney. It cannot be used as a predictor for all universities and student life. The data cannot provide in depth analysis of units of study and the course details as it only provides a glimpse and generalization.
The mean average canvas access is 14 weeks for the semester. The mean average UoS mark was 67, which provides a good indication of correlation between academic achievements with canvas access.
The research question: What is the relationship between having access to canvas and UoS Marks?
ggplot(p3, aes(x=factor(p3$Average), y=p3$UoS.Mark, fill = factor(p3$Average))) + geom_boxplot()
#Discovery and Insights
The stake holders of this data could be the government, if they hope to gain a understanding of university students .Job and company employers could also be interested in this database to gain a better understanding on this particular university and how their education system affects the chances of potential employees.
The boxplot shows that overall, the more you access canvas, the higher the median UoS mark. This correlation is quite weak though because we would expect students who access canvas every week for the semester to have higher UoS marks, but there are still a lot of students who get mark of 30 .The outliers show that accessing canvas consistently does not correlate to higher grades, but it shows that generally students have better organizational and time management skills.
Another interesting aspect is that canvas allows student to access lecture recordings.In an article by “Findlaw” some states do not allow lecture recordings and secretly recording lectures could be illegal. Canvas allows USYD student to have access to lecture recordings and perhaps this could allow further research on within students who access canvas, how many students utilize the benefit of lecture recordings and whether it should done by other universities as well.
In relation to Australian Government research paper” The Demand Driven University System” emphasizes not on the importance of university, but the success of students is throughout University the importance of adapting to new technological systems are essential skills that equip students for workplace. Students who access canvas more may have a higher likelihood to attend lectures and will tend be more organized. Having time management organizational skill correlates to achieving higher grades. It is perhaps not the actual system of “Canvas” that leads to higher marks, but it reveals how organized the student and how consistent they are with keeping up with assignment etc.
Further analysis of each student and the type of courses they are doing and further exploration is needed to make accurate and valid conclusions.
#References https://blogs.findlaw.com/law_and_life/2015/09/is-it-legal-to-record-your-teachers-or-professors.html https://www.pc.gov.au/research/completed/university-report-card/university-report-card.pdf Style: APA —