Student grade prediction is a way for teachers to analyze the performances of theirs students throughout the years based on several factors. The outcomes from this analysis will be used by them for further planning of teaching methods and which students need help the most. This on the other hand can also make some students to know whether if they are in need of help or not for the next semester so they can have some improvements. The main purpose of me taking this topic into consideration is to study how some attributes can be the contributing factors to the student grades and the relationship they have between each other. The secondary data is obtained from a website () by Paulo Cortez from the University of Minho, Portugal. Upon downloading the data, it was then imported into R Studio tool to be further analyzed. From the results of my case study, we can say that student previous grades can affect their final grades since they have a really strong linear positive relationship. In addition, we can also say that student attendance also plays as a minor contibutor for their grades. In some way, I think that the result I got from this data can be the perfect sample to symbolize secondary school students as a whole. This is because the variables collected from the secondary data are from the real-world where it happens all around the world.
Personally, I think that this project has taught me a lot. That includes from coming out with a big enquiry about certain things until trying my best to find solutions from problems that I faced while handling this case study. A big thank you to Dr. Chan Weng Howe for guuiding us since the beginning or our project briefing until the day of the project submission. Dr. Chan also had never stopped in suggesting the correct ways to find solutions to our problems. In addition, by using the provided syllabus videos by Dr. Chan in the elearning, I finally managed to do all the explanation for my research and results from the data. On the other hand, my family and friends also had given me a lot of supports in completing this case study. Without their support, I could never done my project as smoothly as it is. This case study also had increase my knowledge on how to use more functions provided inside of the RStudio tool as well as on how to do data analysis from the secondary data that i chose.
Attached below is the report to my case study.