500-Word Summary of Computer Science Education

To: Prof. Ellis

From: Michael Vanunu

Date: Sept. 21, 2021

Subject: 500-Word Summary of Computer Science Education

Computer science and technology have been developing well over time, this has instantiated multiple computer science courses. These courses can lead to problems which a new student wouldn’t be able to obtain reasonably. This will lead to future problems without assistance of people with more experience and knowledge on the subject.

More systems were developed to solve the problem. People like Chanyan Nuntwawong, Karim Hadjar, Antonio Maffei, and others have tried to fix the problem by presenting their ideas throughout the years.

The paper explains how a computer course can help fresh learners explore reasonable and appropriate curriculums.

The design of OSCCA has five basic steps, “Including data collection, data preprocessing, construction Ontology, establishing reasonable rules and implementing the system” [1, Sect. II]. For the first part, knowledge and unit’s points are being collected from the data that includes courses and universities as well as the likes of those places and locations to provide the best data possible. The second step is a very crucial one. The raw data is going to be processed into NLP, which stands for, Natural language processing. This is going to be a very rough processes that uses Apriori algorithm and things alike. The third step will include the interrelationships of the data collected that will be applied to an ontology. The fourth step defines the four reasoning rules that are important to the whole thing. The fifth and final step is to build a website using java that can provide great and available services for people who are new to learning computer science.

Datasets for the course are being collected through internet information as well as college curriculums. A python spider package named scrappy is used to fetch information for the course. “The course datasets consist of courses, units and knowledge points” [2, Sect. III]. These are the points that “Scrapy” fetches to make the best possible outcome for new students trying to learn.

The analysis and the terms of relationships are analyzed by how each item will be defined. NLP is used to detect and extract the best and contributed items. The Apriori algorithm is used in here again. Apriori algorithm will be solving the frequent items as well as the set problems to assist databases.

Computer courses are increasing at a rapid pace. The courses provided by many courses are independent. Newer learners of the computer science field might be confused by a lot of unneeded and unnecessary information. The solution to the problem is the course for OSCCA (a course ontology stem for computer science education is developed).

Y. Wang, Z. Wang, X. Hu, T. Bai, S. Yang and L. Huang, “A Courses Ontology System for Computer Science Education,” 2019 IEEE International Conference on Computer Science and Educational Informatization (CSEI), 2019, pp. 251-254, doi: 10.1109/CSEI47661.2019.8938930.

Leave a Reply