@article{anwar2020data,
  title = {Data Science for Prediction of Grades in a Mathematics Course based on Performance in its Prerequisites},
  author = {Muhammad Abaidullah Anwar and Rashmi Rani},
  year = 2020,
  url = {https://ibimapublishing.com/articles/MENA/2020/467550/},
  journal = {The MENA Journal of Business Case Studies},
  volume = 2020,
  doi = 9,
  abstract = {Data mining is one of the important techniques in data science and has been effectively and efficiently used to extract useable, previously unknown, comprehensible, useful, and actionable knowledge from a large database whether structured or unstructured. Data mining is important for supporting crucial business decisions, identifying disease diagnostics, and predicting what may happen in future academics as well. This paper presents the application of Apriori algorithm of data mining to mine associate rules among the marks scored by students in prerequisite and successor mathematics courses in an engineering degree program. The analysis of rules reveals that students who scored better marks in the prerequisite courses will 100% maintain their same performance in the successor courses. The mined rules also revealed that association rule mining could be used effectively for predicting grades and also adapting the teaching methodologies to teach mathematics courses.},
  keywords = {Educаtionаl Dаtа Mining, Association Rules, Confidence, Support.},
  note = Article ID: 467550
}