Reflection

Reflection

We found that this class very challenging yet interesting and without help from Dr Fadhlina as our instructor for this course, we don't this assignment will be finished. We’ve learned a lot of new things in this course. This course also taught us that, in order to get a good outcome, we will need a loottttt of patience.

From this project, we learned how to use tools specialized for data mining tasks which are PowerBi, RapidMiner and Python using Google Colaboratory. We're quite sad because for this assignment, we didn't manage to use Python yet but we've explore that first in Google Colaboratory before we decided to do modeling using RapidMiner. Mentoring sessions with instructors, a lot of q&a sessions with classmates and groupmates is the key of this assignment. So, thanks a million for your help :)

For machine learning model, we now know that there are several steps to follow in order to ensure the effectiveness and reliability of each developed model. After we gained the dataset, we need to perform data pre-processing because of the dirty data, noises etc. Pre-processing step is very crucial in developing the models. By having a clean dataset, it can guarantee us to get a good result for modeling part. We also need to train our models to do the predictions on grades of students for this experiment so a clean dataset would be helpful to produce a good prediction.

In conclusion, the prediction models performed are able to accurately predict the grade to a certain degree. This will be useful for both students and instructors to help them to understand and see clearly how participation in class can highly influence the grade at the end of semester. Not only that, the educators and learners also will be able to improve their learning and teaching process.