ISEDJ

Information Systems Education Journal

Volume 21

V21 N1 Pages 39-52

March 2023


Developing a Data-Driven Emerging Skill Network Analytics Framework for Automated Employment Advert Evaluation


Xiaoming Liu
Southeast Missouri State University
Cape Girardeau, MO USA

Dana Schwieger
Southeast Missouri State University
Cape Girardeau, MO USA

Abstract: Rapid advancements and emergent technologies add an additional layer of complexity to preparing computer science and information technology higher education students for entering the post pandemic job market. Knowing and predicting employers’ technical skill needs is essential for shaping curriculum development to address the emergent skill gap. Examining online advertisements to determine the skills sought by employers of new hires for these emerging areas and ensuring that program course content addresses these skills can be a daunting task. In this paper, the authors describe the development of a data-driven analytics framework that can be used for evaluating emerging skill clusters in online job adverts and the application of the framework to a mobile computing course at the authors’ institution.

Download this article: ISEDJ - V21 N1 Page 39.pdf


Recommended Citation: Liu, X., Schwieger, D., (2023). Developing a Data-Driven Emerging Skill Network Analytics Framework for Automated Employment Advert Evaluation. Information Systems Education Journal21(1) pp 39-52. http://ISEDJ.org/2023-1/ ISSN : ISSN: 1545-679X. A preliminary version appears in The Proceedings of CONISAR 2022