Rough Draft

Computer Efficiency at City College of New York

Justus Akalonu, Keyion Carter, Progga Chowdhury, Tiffany Finnie

ENGL 21007 Writing For Engineers

Professor: Maryam Alikhani

City College of New York

October 14, 2018

 

Abstract

The objective of this study was to determine which computer operating system – Apple’s Mac OS, or Microsoft Windows – is most efficient for students at the City College of New York. We tested multiple computers for each of the operating systems – recording the speed of each computer’s restart, log-in, and log-out operations. Results indicate that each system displayed superiority in different categories: log-out average for Windows; restart average and log-in average for Mac OS. The study’s conclusions indicate that although Windows computers were faster overall, there are many underlying factors that could have swayed the results, indicating that further studies are required to properly determine which computer operating system will increase student efficiency.  

 

Introduction

When it comes to  computers, two of the most widely known companies are Microsoft and Apple, with Microsoft computers running on Windows and Apple computers on Mac OS operating systems. The first Macintosh computer was released in 1984 by Apple Inc. (Levy, 2018), while the first personal computer operating with a Microsoft Windows system followed in 1985 (Gibbs, 2014).  Naturally, when it comes to competing companies, people want  to know which is best. However, choosing which of the two are better, is not a black and white choice. There are factors such as speed, compatibility, cost, size, and appearance to be considered when making this decision. At City College of New York, it can be extremely difficult to find an available computer in the Cohen Library. This can waste valuable study time for students waiting to use computers on campus. As a result, it is important to maximize the speed required for students to log in and out of the campus computers and restart when necessary to maximize the number of students able to use the computers. The purpose of this experiment is to see which operating system – Windows or Mac OS – would be more efficient for CCNY students to use while on campus.

 

Materials and Methods

1. 4 different Microsoft Windows computers in the Cohen Library at City College of New York
2. 4 different Apple Macintosh computers in the Cohen Library at City College of New York
3. Stopwatch

Procedure

Part 1: Testing Apple Macintosh Computer Speed

1. Using a stopwatch, the amount of time (in seconds) taken to restart a Mac computer in the Cohen Library at CCNY was recorded from the time the ‘restart’ button was pressed, until the time the log-in screen reappeared.
2. Next, the time taken to hit ‘log-in’ – after a username and password were input – until the time the desktop icons and dock appeared at the bottom of the screen was recorded.
3. Finally, the time taken from when ‘log-out’ was pressed, until the log-in screen reappeared was recorded.
4. Steps 1-3 were repeated on the same computer for a second time.
5. Steps 1-4 were repeated on three more computers in the Cohen Library for a total of four computers, and eight recordings.

Part 2: Testing Microsoft Windows Computer Speed

All steps in Part 1 were repeated using Microsoft Windows computers in the Cohen Library.

Results

Table 1: Individual Trials Based On User

	Tester 1		Tester 2		Tester 3		Tester 4
Mac Trials (time in seconds)
Restart	128	120	79	120	98	96	122	122
Log-in	86	111	128	17	93	89	61	208
Log-out	218	417	46	67	25	20	379	408
Average Time	144	216	84.3	68	72	68.3	187.3	246
Total Time	432	253	216	562	648	204	205	738
Windows Trials (time in seconds)
Restart	154	167	83	134	110	129	123	136
Log-in	333	226	7	8	159	91	292	98
Log-out	38	33	31	41	35	33	20	11
Average Time	175	142	40.3	61	101.3	84.3	145	81.7
Total Time	525	121	304	435	426	183	253	245

Four testers recorded the restart, log-in and log-out speeds of the two Mac and the two Windows computers, in seconds.

Table 2: Total Average Times For Each Operating System

Test	Time (s)
	Mac	Windows
Restart Average Time	110.6	129.5
Log-in Average Time	99.125	151.8
Log-out Average Time	197.5	30.3
Overall Average Time	135.8	103.8
Overall Total Time	407.25	311.5

Total average times of the three components were noted for the Mac and Windows computers.

 

On average, Microsoft Windows PCs in the Cohen Library were most efficient at logging out, displaying a 552% faster log-out average compared with Mac OS. Conversely, the Apple computers operating with Mac OS proved most efficient when restarting and logging on.

 

Results show a 17% faster restart speed and a 53% faster log-in speed when compared with the Microsoft Windows computers in the Cohen Library at City College of New York. Overall, Microsoft Windows PCs proved to be 31% more efficient when compared with Apple Mac OS PCs in the Cohen Library at City College of New York.

Discussion

The three factors – restart, log-in and log-out speeds – were chosen because they seemed the most unbiased, as they are largely based on the manufacturer’s design. We tried to avoid testing anything involving internet connection, as well as anything reliant on programs designed by a third party – since not all students use the same programs, and the two companies have little control over either of these types of application.

 

Our trials showed that the Mac OS had a faster restart average, as well as a much more efficient log on average than the Windows. Its log out average, however, was 552% slower, resulting in the Mac OS to be declared as the “slower” processor. There was a huge room for error in our experiment just as there is in any other cases. One reason our results could have been this way was because every group member could have taken a different approach such as a different order of trial. This could have also led to confusion amongst us, affecting when each person started and stopped the stopwatch. The time each person performed their trial tests could also vary, leading to changes in the data. For example, one person could have noted their test numbers in the morning where the computers are fresh and not as used. In the afternoon, however, they have been used more heavily and can tend to run slower. Additionally, although all the Windows and Mac OS computers in the Cohen library are the same model, some could have been newer or recently purchased than the other. Perhaps the older the computer was, the slower it ran, affecting our research. Certain computers in the front of the library can also very well be used more often than others, resulting in them to have much more content stored in them and run slower.

Conclusion

There are a number of factors that could have swayed the results of this study, which should be considered for future experiments to determine the efficiency of each operating system at CCNY.  Factors include: computer usage, age of the computers, temperature, and the number of trials performed in this study. The more a computer is used, the more likely it is for the parts to fail or take damage, slowing the computer. Some computers are more likely to be used than others due to both their location in the library, and age  – the Mac computers in the CCNY library are at least one year older than the Windows’, and thus have at least a year’s worth of extra usage. Finally, temperature variations throughout the library may affect the speed of computers, as well as the time of day, given that computers in the library have been in use all day without a break, compared to the fresh start they receive in the mornings after a reboot.

 

 

Final Draft

Computer Efficiency at City College of New York

Justus Akalonu, Keyion Carter, Progga Chowdhury, Tiffany Finnie

ENGL 21007 Writing For Engineers

Professor: Maryam Alikhani

City College of New York

October 14, 2018

 

Abstract

The objective of this study was to determine which computer operating system – Apple’s Mac OS, or Microsoft Windows – is most efficient for students at the City College of New York. We tested multiple computers for each of the operating systems – recording the speed of each computer’s restart, log-in, and log-out operations. Results indicate that each system displayed superiority in different categories: log-out average for Windows; restart average and log-in average for Mac OS. The study’s conclusions indicate that although Windows computers were faster overall, there are many underlying factors that could have swayed the results, indicating that further studies are required to properly determine which computer operating system will increase student efficiency.  

 

Introduction

When it comes to personal computers, two of the most widely known companies are Microsoft and Apple, with Microsoft computers running on Windows and Apple computers on Mac OS operating systems. The first Macintosh computer was released in 1984 by Apple Inc. (Levy, 2018), while the first personal computer operating with a Microsoft Windows system followed in 1985 (Gibbs, 2014).  Naturally, when it comes to competing companies, people would like to know which is best. However, choosing which of the two are better, is not a black and white choice. There are factors such as speed, compatibility, cost, size, and appearance to be considered when making this decision. At City College of New York, it can be extremely difficult to find an available computer in the Cohen Library. This can waste valuable study time for students waiting to use computers on campus. As a result, it is important to maximize the speed required for students to log in and out of the campus computers and restart when necessary to maximize the number of students able to use the computers. The purpose of this experiment is to investigate which operating system – Windows or Mac OS – would be more efficient for CCNY students to use while on campus.

 

Materials and Methods

1. 4 different Microsoft Windows computers in the Cohen Library at City College of New York
2. 4 different Apple Macintosh computers in the Cohen Library at City College of New York
3. Stopwatch

Procedure

Part 1: Testing Apple Macintosh Computer Speed

1. Using a stopwatch, the amount of time (in seconds) taken to restart a Mac computer in the Cohen Library at CCNY was recorded from the time the ‘restart’ button was pressed, until the time the log-in screen reappeared.
2. Next, the time taken to hit ‘log-in’ – after a username and password were input – until the time the desktop icons and dock appeared at the bottom of the screen was recorded.
3. Finally, the time taken from when ‘log-out’ was pressed, until the log-in screen reappeared was recorded.
4. Steps 1-3 were repeated on the same computer for a second time.
5. Steps 1-4 were repeated on three more computers in the Cohen Library for a total of four computers, and eight recordings.

Part 2: Testing Microsoft Windows Computer Speed

All steps in Part 1 were repeated using Microsoft Windows computers in the Cohen Library.

Results

Table 1: Individual Trials Based On User

	Tester 1		Tester 2		Tester 3		Tester 4
Mac Trials (time in seconds)
Restart	128	120	79	120	98	96	122	122
Log-in	86	111	128	17	93	89	61	208
Log-out	218	417	46	67	25	20	379	408
Average Time	144	216	84.3	68	72	68.3	187.3	246
Total Time	432	253	216	562	648	204	205	738
Windows Trials (time in seconds)
Restart	154	167	83	134	110	129	123	136
Log-in	333	226	7	8	159	91	292	98
Log-out	38	33	31	41	35	33	20	11
Average Time	175	142	40.3	61	101.3	84.3	145	81.7
Total Time	525	121	304	435	426	183	253	245

Four testers recorded the restart, log-in and log-out speeds of the two Mac and the two Windows computers, in seconds.

Table 2: Total Average Times For Each Operating System

Test	Time (s)
	Mac	Windows
Restart Average Time	110.6	129.5
Log-in Average Time	99.125	151.8
Log-out Average Time	197.5	30.3
Overall Average Time	135.8	103.8
Overall Total Time	407.25	311.5

Total average times of the three components were noted for the Mac and Windows computers.

 

On average, Microsoft Windows PCs in the Cohen Library proved to be most efficient at logging out, displaying a 552% faster log-out average compared with Mac OS. Conversely, the Apple computers operating with Mac OS proved most efficient when restarting and logging on.

 

Results indicate a 17% faster restart speed and a 53% faster log-in speed when compared with the Microsoft Windows computers in the Cohen Library at City College of New York. Overall, Microsoft Windows PCs proved to be 31% more efficient when compared with Apple Mac OS PCs in the Cohen Library at City College of New York.

Discussion

The three factors – restart, log-in and log-out speeds – were chosen because they seemed the most objective, as they are largely based on the manufacturer’s design. We tried to avoid testing anything involving internet connection, as well as anything reliant on programs designed by a third party – since not all students use the same programs, and the two companies have little control over either of these types of application.

 

Our trials confirmed that the Mac OS had a faster restart average, as well as a much more efficient log on average than the Windows. Its log out average, however, was 552% slower, resulting in the Mac OS to be declared as the “slower” processor. There was a huge room for error in our experiment just as there is in any other cases. One reason our results could have been this way was because every group member could have taken a different approach such as a different order of trial. This could have also led to confusion amongst us, affecting when each person started and stopped the stopwatch. The time each person performed their trial tests could also vary, leading to changes in the data. For example, one person could have noted their test numbers in the morning where the computers are fresh and not as used. In the afternoon, however, they have been used more heavily and can tend to run slower. Additionally, although all the Windows and Mac OS computers in the Cohen library are the same model, some could have been newer or recently purchased than the other. Perhaps the older the computer was, the slower it ran, affecting our research. Certain computers in the front of the library can also very well be used more often than others, resulting in them to have much more content stored in them and run slower.

Conclusion

There are a number of factors that could have affected the results of this study, which should be considered for future experiments to determine the efficiency of each operating system at CCNY.  Factors include: computer usage, age of the computers, temperature, and the number of trials performed in this study. The more a computer is used, the more likely it is for the parts to fail or take damage, slowing the computer. Some computers are more likely to be used than others due to both their location in the library, and age  – the Mac computers in the CCNY library are at least one year older than the Windows’, and thus have at least a year’s worth of extra usage. Finally, temperature variations throughout the library may affect the speed of computers, as well as the time of day, given that computers in the library have been in use all day without a break, compared to the fresh start they receive in the mornings after a reboot.

 

Future improvements that could be made to this study include performing more trials, or even testing every single computer in the CCNY library. Each trial should be done in an environment of similar temperature, at the same time of day, by the same user. With more comprehensive results, determined from future studies, the usefulness of this experiment can be for both students, and the competing companies in question: Microsoft and Apple. Students can get a better idea of which computer to use when they enter the library, and these two companies can see where they lack, and possibly how to improve their computers.

 

References

Gibbs, S. (2014, October 2). From Windows 1 to Windows 10: 29 years of Windows evolution. The Guardian. Retrieved from http://www.theguardian.com

Levy, S. (2018). Apple Inc. In Encyclopaedia Britannica. Retrieved from https://www.britannica.com/topic/Apple-Inc

https://docs.google.com/document/d/1FpT9fn1-c2RNjM86_ShFn79JZ4j6gfFT0z0V34lT1IQ/edit  (Google doc link)