Randy Barrera

Prof. Elisabeth von Uhl

ENGL 21007

11 March 2023

Rhetorical Analysis of Sample Lab Reports Based on Technology

Good information is significantly expressed by experiments to make them reliable and easily acquired. Lab reports are the results of the in-depth described procedures, data analysis, and conclusions based on the results presented. Three lab reports will be used to demonstrate the similarities and differences between their formats. With experiments on artificial intelligence to social technology, both can fall into a similar category as authors conduct their own choice of language and represent what they found in their testing; although the report by Lauckner et al., “An Exploratory Study of the Relationship between Social Technology Use and Depression among College Students” strands away from artificial intelligence, it still has the same concept of “Evaluation Model of Music Therapy’s Auxiliary Effect on Mental Health Based on Artificial Intelligence Technology.” by Dan Lu, on mental health; the difference between “Building an Artificial Intelligence Laboratory Based on Real World Data: The Experience of Gemelli Generator” by Damiani et al. report is the vast amount of visual information and bullet points to make the research stand out, it beats Lauckner et al. and Lu’s combined on the way they display their findings.

 

 

Abstract

The ideal part of the piece is the abstract, which saves you time before you read lengthy articles if looking for something specific. Lu’s article has an influential abstract with being straight to the point and restates the title with a bit more insight on what an auxiliary effect is, along with a heads up on how the results will turn out as he mentioned the experimental group and control group. Meanwhile, Lauckner’s et al. is short and sweet with only 4 sentences as the previous abstract mentioned had 7 long sentences. They indicate how their experiments depended heavily on surveying students from two universities, the writers’ method of doing the abstract seems perfect for a simple report. Damiani at el. was the only abstract that wasn’t didn’t have a heading but it should be a minor issue. The abstract falls weak because it gives difficulty on what exactly the article is entirely about, it twists a bunch of phrases together and that makes this the weakest abstract of the 3.

Introduction

            The introductions of each integrate their purpose and the authors of “Building an artificial” made up for their not-so-best abstract with the abundant paragraphs for this section. The explanation for every aspect of the research was set forth into bullet points and expounds names such as the “Generator RWD”. The aspects consist of the procedures and databases used to perform the experiment. “Auxiliary Effect on Mental Health” already had some basis developed in the abstract but went more in-depth with the conditions, methods, reason for trials, and the perspective of the paper on artificial intelligence. It also mentions how “the social environment is complex, the pace of life is accelerating, the learning competition is fierce, and the media communication channels are increasing” (Lu, 2022, p.2) explaining the data will have a large range of statistics. The last paper by Lauckner et al. was back with the same short paragraph and they introduce statistics already as the others two articles haven’t. They use data that most people that read these papers are included in the experiment as an example. Of people “18- 29 years old, 85% owns a smartphone” (Lauckner et al, 2020, p.1), and now that the world is heavily based on technology the number seems to be correct. Each of these reports had its tactics but Damiani et al. did all the above slightly better and had more to introduce to the readers.

Research Methods

            Methods to get the authors’ objectives varied, one depended heavily on databases the other relied on surveys, and the third one did all of the above. Lab report, “Auxiliary Effect on Mental Health”, consists of all types of methods except the well-known type, trials, and recording data based on results. Lu approaches his research by interviewing teachers, students, and parents. With those people, he learns about their living conditions for more information. His second step is by investigating the information he has gathered and figure out reasons why his results were what they were. Lu’s final method is observing every single event and keeping it noted so an analysis can be provided. This format is incredibly strong because it gives key components on what’s there to be and expectations to be found during the run. On the other hand, Damiani et al. fabricated struggle to understand or take anything in, there’s a vast amount of insignificant information. Graphs and charts were presented but they were samples with no actual data filled in. The only method to get results is to look at the databases and their algorithm. It shows why the abstract wasn’t well made because there were just too much irrelevant sentences. “An Exploratory Study” has methods simplified and brief, it’s like Lu’s work as it is very effective, unlike Damiani et al. report.

 

Data and Analysis

After trials were run and data was extracted by the methods planned out by the writers. Lauckner et al. include their numbers, and their equations to make sense of what was recorded. They did it based on popular social media, things people can have a slight understanding of and go their way to investigate easily if they wanted to. What was odd was the analysis was before the results and it seems better for it to be done after. Damiani et al. format is again a mess with no analysis and results are combined with their methods which can lead to a whole section looking empty. This style may have also led to unrelated topics being brought up. Lu part of the data and analysis is supported with a table of scores. This is the best way to share results and can help separate two different sets of data. Lu’s section of the lab report is by far better than the other two papers.

Conclusion

The article “Building an Artificial Intelligence “seems to not know how to end clearly. A conclusion should have its own heading and part for a report as it is the result of everything said. It indicates where the answers have been found and what’s next from what was found. Compared to “Auxiliary Effect on Mental Health” they don’t summarize. “Auxiliary Effect on Mental Health” has its conclusion, and it seems to have all that’s necessary to gain from reading this report. It explains how the methods worked and why the results came a certain way. It has an ending paragraph for a true conclusion. Lastly, “An Exploratory Study” doesn’t say much for its conclusion but addresses what they learned from what they found. It does a better job than a report without a conclusion.

All these reports had weaknesses and strengths. Lu’s report seemed to have the most strength as their format complimented each other really well. Lauckner et al, the report was in the middle and would be a decent standard as it followed the proper way to share its information, a lack of visuals can be a takeaway. Damiani et al, their report seemed to be the brightest of them all because of the number of visuals and ideas shared. It appeared to be the opposite because most of the stuff read wasn’t strong or even related to the purpose of researching. In the end, Lu’s report outshines the other two as it was only one person doing it all.

 

 

 

 

 

 

 

 

 

 

 

 

 

References

Lauckner, C., Hill, M., & Ingram, L. A. (2020). An Exploratory Study of the Relationship between Social Technology Use and Depression among College Students. In Journal of College Student Psychotherapy (Vol. 34, Issue 1, pp. 33–39). https://doi-org.ccny-proxy1.libr.ccny.cuny.edu/10.1080/87568225.2018.1508396

 

Damiani, A., Masciocchi, C., Lenkowicz, J., Capocchiano, N. D., Boldrini, L., Tagliaferri, L., Cesario, A., Sergi, P., Marchetti, A., Luraschi, A., Patarnello, S., & Valentini, V. (2021, November 12). Building an artificial intelligence laboratory based on Real World Data: The experience of gemelli generator. Frontiers. Retrieved March 20, 2023, from https://www.frontiersin.org/articles/10.3389/fcomp.2021.768266/full

 

Lu, D. (2022). Evaluation Model of Music Therapy’s Auxiliary Effect on Mental Health Based on Artificial Intelligence Technology. Journal of Environmental and Public Health, 2022. https://link-gale-com.ccny-proxy1.libr.ccny.cuny.edu/apps/doc/A720580948/AONE?u=cuny_ccny&sid=bookmark-AONE&xid=2af29f31