2025 ASEE Annual Conference & Exposition

Investigating Competencies in Electrical Engineering: Alignment Between Internet Media and Job Postings

Plan of Submission: This submission is a Work-in-Progress paper that will investigate the relationship between the technical and professional competencies outlined by job postings for electrical engineers and those recommended by YouTube videos.

Assessment Methods: The proposed approach involves collecting transcript data from video sources that enumerate recommended skills for electrical engineering on YouTube. We will analyze and extract the core competencies using AI-driven techniques to ensure consistency and expedite the process. The frequency and emphasis of each competency will be analyzed.

Statement of Results: Preliminary findings may identify which competencies are overemphasized or overlooked in internet media compared to those stated as required by employers, offering insights into the accuracy and usefulness of these sources and job postings for students seeking employment in electrical engineering.

Topic Addressed: This submission addresses the topic of “Current ECE issues and integration into the curriculum” by exploring the alignment of competencies critical for job preparation.

Social media has become an important part of the everyday lives of billions of people. As social media has become more prevalent, it has become an important source of information to many. On many internet media sites, advice surrounding the best skills to acquire to ensure relevancy in certain fields is very common and serves as a useful resource for those looking to build certain competencies for employment.  Because of the importance of this source of information, analysis of the types of advice given will be helpful in understanding and improving the effectiveness of these internet media sources. The proposed study will investigate the relationship between the technical and professional competencies outlined by job postings for electrical engineers and the competencies recommended by internet media.

This study will analyze advice targeting undergraduate electrical engineering students seeking jobs post-graduation. Specifically, we collected transcript data from YouTube blogs discussing recommended skills for electrical engineering students exploring the job market. These videos were collected using a single search term that has been refined to provide the most relevant results. We excluded videos with less than 10,000 views. This resulted in 34 videos that were included in the sample. The transcripts of these videos and their associated comment section were downloaded.

We will use ChatGPT to analyze this data and extract the core competencies discussed in these videos. Specifically, we placed the transcript data into a constructed template which will be entered into ChatGPT with instructions on how to analyze the text and output the competencies that are recommended by the video. This method is used to ensure consistency in analysis and expedite the process of analysis. The data from each video will be combined to determine the frequency and emphasis of each of the competencies.

With the findings, we aim to identify which competencies are overemphasized or overlooked in internet media and which sources provide the most accurate information regarding essential skills for employment in electrical engineering. This research could increase the quality and usefulness of internet media sources across various fields and inform the development of curriculum and teaching strategies that better prepare students for the job market.

Authors

Dr. Aakash Alpesh Patel University of Georgia [biography]

Aakash Alpesh Patel is a second year undergraduate Computer Systems Engineering major at the University of Georgia. He is interested in machine learning, natural language processing, and computer architecture.
Taiwo Raphael Feyijimi http://orcid.org/0009-0009-5752-4175 University of Georgia [biography]

Taiwo is a highly skilled AI Engineer, Researcher, and Doctoral Student at the University of Georgia who completed his MS in Electrical and Computer Engineering in the College of Engineering. He is currently leveraging AI to tackle simple and longstanding problems in engineering education.

With over a decade of industry experience as a Technology Strategist and Technical Lead, he has established himself as a forward-thinking innovator in AI and EdTech.

His expertise spans Exploratory Data Analysis (EDA), Machine Learning (ML), Natural Language Processing (NLP), and Prompt Engineering Techniques (PETs) with Large Language Models (LLMs). Taiwo is known for his ability to collaborate effectively within and across organizations to meet project goals and drive transformative results. He excels in leading technical teams, offering strategic IT consultations, and implementing solutions that enhance productivity.
Dr. Sarah Jane Bork http://orcid.org/0000-0002-4344-554X University of Georgia [biography]

Dr. Sarah Jane (SJ) Bork is an Assistant Professor in Electrical and Computer Engineering with an emphasis on engineering education research. Dr. Bork’s research has focused on examining the mental health experiences of engineering graduate students. She has studied different areas (e.g., social factors, engineering culture, etc.) using a variety of research methods (e.g., regression analysis, photovoice, factor analysis, interview data, etc.). Dr. Bork earned her doctorate degree from the University of Michigan’s Engineering Education Research Program. Prior to this, she earned both a Bachelor’s and Master’s degree in Electrical Engineering from The Ohio State University.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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