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Identifying the Needs of Electric Power Industry through Online Job Ads: A Mixed-methods Approach

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Energy Conversion, Conservation and Nuclear Engineering Division (ECCNE) Technical Session 1

Tagged Divisions

Energy Conversion and Conservation and Nuclear Engineering Division (ECCNE)

Tagged Topic

Diversity

Page Count

20

DOI

10.18260/1-2--43443

Permanent URL

https://peer.asee.org/43443

Download Count

123

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Paper Authors

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Huiye Yu UNSW Sydney

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Huiye Yu received her Bachelor of Electrical Engineering from North China Electric Power University, China, in 2021. She is studying a Master of Electrical Engineering at UNSW Sydney. She is currently working as a student Electrical Engineer at Aurecon.

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Hua Chai University of New South Wales

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Hua Chai received his dual Bachelor's Degrees in both Electrical Engineering and Project Management from North China Electric Power University, China, in 2014. He received his Master's degree (Master of Philosophy) in Electrical Engineering at the University of New South Wales, Australia, in 2019. He is currently a Ph.D. student in the Energy Systems, School of Electrical Engineering and Telecommunications, UNSW. His research interests include power engineering education, curriculum design and development, and condition monitoring of power system equipment.

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Jayashri Ravishankar University of New South Wales

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A/Prof Jayashri Ravishankar is a Scientia Education Fellow and Associate Dean (Education) in the Faculty of Engineering at the University of New South Wales (UNSW), Sydney. Her teaching and research interests include power system modelling, analysis and control, renewable energy integration, smart grids and micro grids.
Jayashri has a deep interest in learning and teaching, and consistently implements strategies using technology innovations and industry partnerships to improve students’ active learning. She is institutionally and internationally recognized for the impact of her innovative, research-led and highly effective teaching and leadership. She leads best practice advanced teaching in electrical engineering through imaginative initiatives, including blended industry lectures, teamwork and flipped mode strategies. Esteem indicators include Senior Fellowship of the Higher Education Academy awarded by Advance HE (UK), UNSW Teaching Excellence Awards and the Australian Awards for University Teaching Citation.

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Abstract

With policies and projects charting the net zero future of the electric power system, new jobs are created to meet the increasing demand for electrical engineers in integrating renewable energy resources. Despite universities' efforts to prepare students for the workforce, the industry still faces a talent shortage, resulting from a gap between the fast-evolving industry expectations and the quickly outdated university curricula. The lack of systematic methods to understand authentic industry needs is one of the root causes of the gap. This paper proposes a holistic process for identifying the knowledge and skills in demand in the electric power industry by analyzing public data - job advertisements (job ads). The job ads are scraped from major online job boards and screened with a data selection framework. A mixed-method approach is applied to analyze the data, involving both quantitative and qualitative analysis. The results of this study provide a benchmark for tertiary engineering educators on what to include in their curricula to better adapt the courses and training provided and equip students with up-to-date knowledge and skills for the fast-changing industry. This approach can also be applied to other disciplines to identify the demand of the evolving job markets to produce job-ready graduates in the relevant areas.

Yu, H., & Chai, H., & Ravishankar, J. (2023, June), Identifying the Needs of Electric Power Industry through Online Job Ads: A Mixed-methods Approach Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43443

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