Work

CARIA

Year: 2024

Type: article

Abstract: The purpose of this research is to create a personalized system called CARIA that suggests career recommendations based on students' competencies and the required skills in each career. The focus of this study is on digital technology and digital media careers. The personalized career recommender system uses a novel similarity measure called modified Euclidean similarity to evaluate its performance and compare it with other similarity measures, machine learning, and GPT-4 techniques. The experimental results showed that modified Euclidean similarity achieved a precision@10 score of 0.83, which outperformed other techniques. The main objective of CARIA is to provide students with suitable career paths and conduct a competency gap analysis. This helps students choose a career path that fits their abilities. This research contributes to education in digital technology, digital media, and the workforce by providing employees with competencies that align with their needs.

Source: International Journal of Information and Communication Technology Education

DOI: 10.4018/ijicte.356499

Authors: Supaluck Seesukong, Thara Angskun, Nantapong Keandoungchun, Atitthan Thippongtorn, Jitimon Angskun

Institutions: Suranaree University of Technology, King Mongkut's University of Technology Thonburi, Suranaree University of Technology Hospital

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDGs: Quality education, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4403383286

FWCI:

Cites: 24

Cited by:

Related to: 10