Enhancing Cognitive Skills in E-Learning: A Machine Learning Approach Using BERT, MNB, and SVM
Keywords:
E-Learning, Cognitive Skills, Bloom Taxonomy, BERT, Machine Learning, Educational Data MinningAbstract
This research is all about figuring out how to make e-learning better by boosting how students think – things like memory and problem-solving. We're checking out some cool computer programs (they're actually called machine learning algorithms!) like BERT, MNB, and SVM to see if they can help students learn better online. Basically, we're using these programs to understand how well students are grasping the material in e-learning. We got our data from a public university and a big online collection called the UCI Machine Learning Repository. To make sense of all the info, we're using a tool called Weka to create some visual charts based on Bloom's Taxonomy – it's a way of categorizing different levels of thinking skills. And yeah, we're using Python to crunch all the numbers and get the programs running. The big idea, to connect how students develop their thinking skills with the way they learn online, all using these fancy machine learning tricks!
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