Do you agree or disagree with the following statement Workers are more satisfied when they have many different types of tasks to do during the workday than when they do similar tasks all day long Use specific reasons and examples to support your answer

Essay topics:

Do you agree or disagree with the following statement?
Workers are more satisfied when they have many different types of tasks to do during the workday than when they do similar tasks all day long.
Use specific reasons and examples to support your answer.

Some people argue that worker are more satisfied when they engage in multiple tasks during the workday as different tasks can provide them with an array of experiences, which will prevent them from getting bored. However, in my opinion, worker are more satisfied when they focus on one task during workday. I feel this way for 3 reasons, which I illustrate in the subsequent paragraphs.

Firstly, people prefer to work on those task in which they are specialized in, and they can continue working on them for hours. They don’t get tired when they do things they like as they find joy in them. To illustrate by an example, my father, who is a stock market broker can spend hours looking at the charts for stocks. He spend almost all day analyzing and predicting the future prices of the stocks and doesn’t get bored. When I asked him why don’t he try something new he said his work in stock market is passion driven and would like to continue the work even after his retirement. This clearly shows that it is not necessary to enjoy work doing different things rather we can focus on ony task and enjoy.

Secondly, the more tasks workers get involved in the more likely they will get confused. Different tasks have diiferent methods that has to be learned before performing those tasks. If workers indulge in variety of tasks they will have to learn vast number of methods and processes, which can easily confuse them. For example, my interest is in Machine learning . One day, I tried learning app developement and frontend development along with machine learning, however, after few days I got confused with all the concepts that I learned, and ended up having only raw knowledge of the three subjects. If I had focused only on Machine learning, I would have in dept knowledge of it.

Thirdly, It is also difficult for the organization to allocate various tasks to a single employees. When companies hires employees they check their special skills and accordingly allocate them their groups. It comes much easier for the company to assign tasks based on one’s skill. For example, Google hires an app developer based on his Android skill, and Frontend developer based on his Javascript skills. After hiring Google can’t ask the Frontend developer to build an android app as he would not be able to build the app as good as the android developer.

In conclusion, I firmly believe that workers should focus on one task and master them. This is because they will enjoy the task once they have an indept knowledge of it, and would not get confused; it is also better for the organization.

Votes
Average: 7 (1 vote)
Essay Categories

Comments

Grammar and spelling errors:
Line 3, column 328, Rule ID: HE_VERB_AGR[1]
Message: The pronoun 'He' must be used with a third-person verb: 'spends'.
Suggestion: spends
...rs looking at the charts for stocks. He spend almost all day analyzing and predicting...
^^^^^
Line 5, column 362, Rule ID: COMMA_PARENTHESIS_WHITESPACE
Message: Don't put a space before the full stop
Suggestion: .
...mple, my interest is in Machine learning . One day, I tried learning app developem...
^^
Line 7, column 90, Rule ID: A_PLURAL[2]
Message: Don't use indefinite articles with plural words. Did you mean 'employee'?
Suggestion: employee
...n to allocate various tasks to a single employees. When companies hires employees they ch...
^^^^^^^^^

Transition Words or Phrases used:
accordingly, also, first, firstly, however, if, look, second, secondly, so, third, thirdly, as to, for example, i feel, in conclusion, in my opinion

Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments

Performance on Part of Speech:
To be verbs : 12.0 15.1003584229 79% => OK
Auxiliary verbs: 15.0 9.8082437276 153% => OK
Conjunction : 12.0 13.8261648746 87% => OK
Relative clauses : 15.0 11.0286738351 136% => OK
Pronoun: 60.0 43.0788530466 139% => Less pronouns wanted
Preposition: 54.0 52.1666666667 104% => OK
Nominalization: 5.0 8.0752688172 62% => OK

Performance on vocabulary words:
No of characters: 2157.0 1977.66487455 109% => OK
No of words: 450.0 407.700716846 110% => OK
Chars per words: 4.79333333333 4.8611393121 99% => OK
Fourth root words length: 4.6057793516 4.48103885553 103% => OK
Word Length SD: 2.46130320781 2.67179642975 92% => OK
Unique words: 224.0 212.727598566 105% => OK
Unique words percentage: 0.497777777778 0.524837075471 95% => More unique words wanted or less content wanted.
syllable_count: 646.2 618.680645161 104% => OK
avg_syllables_per_word: 1.4 1.51630824373 92% => OK

A sentence (or a clause, phrase) starts by:
Pronoun: 13.0 9.59856630824 135% => OK
Article: 1.0 3.08781362007 32% => OK
Subordination: 6.0 3.51792114695 171% => OK
Conjunction: 4.0 1.86738351254 214% => Less conjunction wanted as sentence beginning.
Preposition: 5.0 4.94265232975 101% => OK

Performance on sentences:
How many sentences: 22.0 20.6003584229 107% => OK
Sentence length: 20.0 20.1344086022 99% => OK
Sentence length SD: 43.7328478774 48.9658058833 89% => OK
Chars per sentence: 98.0454545455 100.406767564 98% => OK
Words per sentence: 20.4545454545 20.6045352989 99% => OK
Discourse Markers: 6.72727272727 5.45110844103 123% => OK
Paragraphs: 5.0 4.53405017921 110% => OK
Language errors: 3.0 5.5376344086 54% => OK
Sentences with positive sentiment : 11.0 11.8709677419 93% => OK
Sentences with negative sentiment : 5.0 3.85842293907 130% => OK
Sentences with neutral sentiment: 6.0 4.88709677419 123% => OK
What are sentences with positive/Negative/neutral sentiment?

Coherence and Cohesion:
Essay topic to essay body coherence: 0.276131707189 0.236089414692 117% => OK
Sentence topic coherence: 0.0874502446346 0.076458572812 114% => OK
Sentence topic coherence SD: 0.08299394922 0.0737576698707 113% => OK
Paragraph topic coherence: 0.167682509348 0.150856017488 111% => OK
Paragraph topic coherence SD: 0.0735573402713 0.0645574589148 114% => OK

Essay readability:
automated_readability_index: 11.4 11.7677419355 97% => OK
flesch_reading_ease: 68.1 58.1214874552 117% => OK
smog_index: 3.1 6.10430107527 51% => Smog_index is low.
flesch_kincaid_grade: 8.7 10.1575268817 86% => OK
coleman_liau_index: 10.5 10.9000537634 96% => OK
dale_chall_readability_score: 7.96 8.01818996416 99% => OK
difficult_words: 95.0 86.8835125448 109% => OK
linsear_write_formula: 10.5 10.002688172 105% => OK
gunning_fog: 10.0 10.0537634409 99% => OK
text_standard: 11.0 10.247311828 107% => OK
What are above readability scores?

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Rates: 70.0 out of 100
Scores by essay e-grader: 21.0 Out of 30
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Note: the e-grader does NOT examine the meaning of words and ideas. VIP users will receive further evaluations by advanced module of e-grader and human graders.