Extracting a Body of Knowledge as a First Step Towards Defining a United Software Engineering Curriculum Guideline

<p>In general, the computing field is a rapidly changing environment, and as such, software engineering education must be able to adjust quickly to new needs. Industry adapts to technologies as fast as it can, but the critical issue is a need for recent graduates with the necessary expertise and knowledge of new trends, technologies, and practical experience. The industries that employ graduates of computing degree programs aim to hire those who are familiar with the latest technical traits, tools, and methodologies to meet these needs, and the software engineering curriculum needs to respond quickly to these needs. Still, unfortunately, software engineering curriculums cannot change and adopt new technologies fast. Modifying the curriculum to serve industry needs better is a long and tedious process in an academic setting. It is essential to give software engineers top-notch education and training to make sure they have the information and abilities needed to succeed in their careers. In addition, there are multiple computing curriculum recommendations endorsed by computing professional organizations that provide guidelines for curriculum design. The work proposed for this research plans to develop a method of extracting a body of knowledge and generating an ontology using Natural Language Processing algorithms. This will automate the process of extracting information from curriculum guidelines and models and storing that information in one unified ontology. It is then envisioned that the resulting ontology will be used in future research to assist in creating or validating a Software Engineering curriculum to ensure that all knowledge areas are covered and that the outcomes match the established guidelines and models. This automated extracting a body of knowledge process is the first and fundamental step in defining the United Software engineering Curriculum Guideline.</p>

Name thesis:degree_name

Master of Software Engineering

Level thesis:degree_level

Thesis - Open Access

Discipline thesis:degree_discipline

Electrical, Computer, Software, and Systems Engineering

Year

2023

Author dc:creator

• Kiselev, Anton

• Software Engineering
• Natural Language Processing
• Ontology
• Education
• Computational Engineering
• Educational Assessment, Evaluation, and Research
• Educational Technology
• Engineering Education

Repository record dc:identifier

https://commons.erau.edu/edt/743

OAI identifier oai:identifier

oai:commons.erau.edu:edt-1764