Order ID:89JHGSJE83839 | Style:APA/MLA/Harvard/Chicago | Pages:5-10 |
Instructions:
Data Science and Big Data Analytics Discussion Essay
Here I have 8 Bibliography papers about 8 subjects. I need a full page for each paper so it is 8 pages in total. Here is the links for all papers. It is 8 separate papers!
bibliography 3
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 4
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 5
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 6
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 7
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 8
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 9
https://www.smithsonianmag.com/air-space-magazine/…
bibliography 10
https://www.smithsonianmag.com/air-space-magazine/…
each link will have a full-page bibliography. here I will paste the instructions for the bibliography that you have to follow and I will attach the template and the guidelines and an example too. The work should be original!
Annotated Bibliographies Guidelines
Format
Title: Include your name and the title of the article top of each paper.
Margins: 1″ top, bottom, right, and left. Only flush left margins are acceptable.
Font: Times New Roman size 12 pt.
Line Spacing: Double Spaced
Minimum Length: Five complete lines of text for both the Abstract and Comment sections
Annotated bibliographies that do not meet all of the format criteria will receive 0 points.
Sources
List the title of the article at the top of each annotated bibliography along with your name.
Topic
The annotated bibliographies must be completed and submitted to the drop box by 11:59 PM Central time on the due date.
Content
Data Science and Big Data Analytics Discussion Essay
The annotated bibliography should not be more than 1 page and must consist of three parts; the title, an abstract, and your comments. You may not directly quote any material in your analysis. Each part will begin with the appropriate heading.
An article review that does not have each of the three headings and/or does not cover all three areas will receive 0 points. You must have a minimum of five lines for the abstract section and five lines for the comment section.
Plagiarism Detection
Papers submitted to the D2L Dropbox are automatically analyzed using the Turnitin plagiarism detection software. The software generates an originality report showing the percentage of copied material in each paper submitted. Typically, the percentage of plagiarized material detected is between 0% to 5%. If it is over 20% you cannot earn credit for the assignment. Submitting a paper and receiving a more than 20% on the originality and the resubmitting the paper again with only a few words changed is still plagiarism. I suggest that you always check the report after your paper is submitted. It takes a little time for the software to analyze the paper so the report will not be available for about 15 minutes after the paper is uploaded.
Failure to follow the criteria in the Format section will receive 0 credit
Bibliographies that score 20% or higher on the Turnitin originality report will receive 0 credit. This applies to the final version submitted. However, submitting a paper and receiving a more than 20% on the originality and the resubmitting the paper again with only a few words changed is still plagiarism. These will also receive 0 credit. You are allowed unlimited submission before the deadline.
Each error (spelling or grammatical) more than 2 per bibliography will result in a 5% reduction in the score on the assignment.
If the abstract section is less than 5 full lines of text the score on the bibliography will be reduced by 10% for each line less than a full line.
If the comment section is less than 5 full lines of text the score on the bibliography will be reduced by 10% for each line less than a full line.
Directly quoting material from the article is not allowed. Any directly quoted material will not count towards the minimum text required for either the comment or abstract section.
Data Science and Big Data Analytics Discussion Essay
RUBRIC |
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Excellent Quality 95-100%
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Introduction
45-41 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Literature Support 91-84 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Methodology 58-53 points Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met. |
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Average Score 50-85% |
40-38 points More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided. |
83-76 points Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration. |
52-49 points Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met. |
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Poor Quality 0-45% |
37-1 points The background and/or significance are missing. No search history information is provided. |
75-1 points Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration. |
48-1 points There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met |
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Data Science and Big Data Analytics Discussion Essay |
Data Science and Big Data Analytics Discussion Essay