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

Autor/inn/en	Liu, Xiaoming; Schwieger, Dana
Titel	Developing a Data-Driven Emerging Skill Network Analytics Framework for Automated Employment Advert Evaluation
Quelle	In: Information Systems Education Journal, 21 (2023) 1, S.39-52 (14 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
Schlagwörter	Network Analysis; Employment Opportunities; Information Technology; Computer Science Education; COVID-19; Pandemics; Course Content; Prediction; Education Work Relationship; Curriculum Development; Job Applicants; Advertising; Employer Attitudes; Data Analysis; Internet; Distance Education; Job Skills; School Business Relationship; Computer Software; Artificial Intelligence; Programming Languages; Higher Education + Suchen Sie Ihr Suchwort? Netzplantechnik; Berufschance; Beschäftigungschance; Informationstechnologie; Computer science lessons; Informatikunterricht; Kursprogramm; Vorhersage; Curriculum; Development; Curriculumentwicklung; Lehrplan; Entwicklung; Bewerber; Werbung; Arbeitgeberinteresse; Auswertung; Distance study; Distance learning; Fernunterricht; Produktive Fertigkeit; Künstliche Intelligenz; Hochschulbildung; Hochschulsystem; Hochschulwesen
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. (As Provided).
Anmerkungen	Information Systems and Computing Academic Professionals. Box 488, Wrightsville Beach, NC 28480. e-mail: publisher@isedj.org; Web site: http://isedj.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01