Category: Article Annotations

Katie Rawson and Trevor Munoz, the authors of this article, clearly made “data cleaning” the core topic. Specifically, the downsides to data cleaning. The main concerns that were brought up were the loss of validity and the reductiveness that can be caused by data cleaning. Without the complexity of data, which is lost in data cleaning, research studies become less accurate to real life, therefore less significant to the issue at hand. In the end, the authors propose a new approach to understanding complex data. This would consist of building systems that can explore the “strange” results instead of eliminating them completely. 

This seems to be a debate that is not exactly new to research fields. I know this because the author’s purpose was not to completely get rid of data cleaning, but to change how it is done. A change in the way data cleaning is conducted was first suggested whenever the authors mentioned how harmful the current practice is. The only main alteration that is brought up is the creation of a new system that values the different and unique qualities of data. This is not a new revelation, since data cleaning has been a valuable part of research for years. However, the article still holds a significant argument, proving that data cleaning is a piece of an old system that is in dire need of an update. This is all done without entirely bashing data cleaning as a practice. 

While I may not know much about data cleaning and the arguments against it, I know this is a controversial topic, since data cleaning has long been used to improve data quality after a study is conducted. Fortunately, the way this article was written gets the point across while not attempting to take data cleaning off the list of research practices. Now, new researchers who read this article can understand the downfalls of data cleaning without ignoring its full benefits. 

If you asked the average person 10 years ago what they thought about artificial intelligence, most people would either immediately think about the robots from the Terminator or not understand what artificial intelligence actually is. By definition, artificial intelligence is the capacity of a computer program to execute functions that are normally related to human intelligence. In recent years, artificial intelligence programs like ChatGPT have become very popular as programmers are racing to improve the effectiveness of AI. This has also sparked a lot of debate about when and where AI should be properly used, like in school, for example. Luckily, many researchers have began to look into issues revolving around AI. An article titled “ChatGPT Goes to College” does a great job at showing just how far along we are on the path tp full AI integration. 

This study on ChatGPT was originally conducted in order to understand students’ views on artificial intelligence and its usefulness. The team created a survey that asked various questions such as how often they use ChatGPT in a school setting. Over 700 college students were asked these questions. In the end, the results showed that the introduction of ChatGPT did not directly cause the number of “cheaters” to increase, it merely allowed students who already had no problem with cheating to get assignments done in a crunch. This clearly shows that AI is not at the point where it is a concern for all students, as 54% of the students interviewed claimed that they have not yet used ChatGPT for school assignments. 

One of my first thoughts on the article was that it did a great job at making sure the results were not up for interpretation. The questions asked made sure to include several factors for the study, such as usage, reasoning, and effectiveness of usage. While this article did not end the debate on AI usage in school, it showed that there is still time to guide students on using artificial intelligence programs such as ChatGPT. The only problem with this study is that it was not widespread enough to show how true those results are for the rest of the country. 

The end of the study did catch me off guard at first. I have not done much research in regard to artificial intelligence in school, but even back in my senior year of high school, I began hearing several of my classmates talk about using AI to complete their assignments. These were also students who would not normally cheat in class. I would have expected the number of people who are comfortable with cheating to rise after ChatGPT. Now, these results may not be totally accurate compared to the rest of America, since the study had a few limitations to it, but I believe the study’s future implications are more important. We are at a time now when AI is still new, and not all students are using it in their everyday lives. This is the perfect opportunity for teachers to educate students on proper usage of artificial intelligence before it is too late. 

Works Cited 

Cavazos, Jenel T., et al. “ChatGPT Goes to College: Exploring Student Perspectives on Artificial Intelligence in the Classroom.” Teaching of Psychology, vol. 1, 7 Aug. 2024, www.researchgate.net/publication/382936523_ChatGPT_Goes_to_College_Exploring_Student_Perspectives_on_Artificial_Intelligence_in_the_Classroom, https://doi.org/10.1177/00986283241268829.