Edward Carl Greco
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Professor
Also affiliated: Lockheed Martin (United States) (1977); University of Miami (1984); Southern Arkansas University Tech (2024–2025); Johnson Space Center (2007–2008); Rice University (1975–1977)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Edward Carl Greco's research focuses on engineering education, particularly the development and assessment of laboratory systems for introductory electrical circuits courses. He has investigated the efficacy of various pedagogical approaches, including the use of individual student lab participation, self-contained instrumentation systems, and final practicums with lab reports for assessing student learning and skills. His work also explores the predictive power of student participation in EE lab teams and utilizes regression analysis to forecast student performance in electric circuits. Greco has published extensively on these topics, with a recent focus on creating accessible and effective training systems for DC electrical circuits. His scholarly output is reflected in an h-index of 8 and over 230 citations. He has collaborated with several colleagues at Arkansas Tech University, including Jim D. Reasoner, Daniel Bullock, and Zahra Zamanipour.
Metrics
- h-index: 8
- Publications: 33
- Citations: 238
Selected Publications
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"Development of a Small, Robust, and Portable Circuits Training System for an Introductory Course in DC Electrical Circuits" (2025)
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"Assessment of an Individualized, Self-Contained System in Electrical Circuits Laboratory" (2025)
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Student Participation in EE Lab Teams as a Predictor of Acquired Skills and Knowledge (2025)
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Efficacy of a Final Lab Practicum and Lab Reports for Assessment in a Fundamentals Electric Circuits Laboratory (2025)
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Improvement in Laboratory Skills and Knowledge Achieved Through Individual Student Lab Participation (2025)
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Discrete Convolution Visualization Utilizing a Jupyter Notebook (2024)
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Predicting Student Success in an Electrical Engineering Program (2021)
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Regression Analysis to Predict Student Electric Circuits Performance (2020)
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Board 81 : Work in Progress: Implementation of Electrostatics Tutorials Utilizing an Electronic Response System in Upper Level Electromagnetics (2020)
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Student Laboratory Skills And Knowledge Improved Through Individual Lab Participation (2020)
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Accuracy of advanced versus strictly conventional 12-lead ECG for detection and screening of coronary artery disease, left ventricular hypertrophy and left ventricular systolic dysfunction (2010)
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Construction and Use of Resting 12-Lead High Fidelity ECG "SuperScores" in Screening for Heart Disease (2007)
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Usefulness of Derived Frank Lead Parameters in Screening for Coronary Artery Disease and Cardiomyopathy (2007)
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New and Improved T-wave Morphology Parameters to Differentiate Healthy Individuals from those with Cardiomyopathy and Coronary Artery Disease (2007)1 citation OpenAlex
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Effect of direct current offset on the T-wave residuum parameter (2006)
Collaboration Network
Top Collaborators
- Improvement in Laboratory Skills and Knowledge Achieved Through Individual Student Lab Participation
- Efficacy of a Final Lab Practicum and Lab Reports for Assessment in a Fundamentals Electric Circuits Laboratory
- Student Participation in EE Lab Teams as a Predictor of Acquired Skills and Knowledge
- "Assessment of an Individualized, Self-Contained System in Electrical Circuits Laboratory"
- "Development of a Small, Robust, and Portable Circuits Training System for an Introductory Course in DC Electrical Circuits"
- Efficacy of a Final Lab Practicum and Lab Reports for Assessment in a Fundamentals Electric Circuits Laboratory
- Efficacy of a Final Lab Practicum and Lab Reports for Assessment in a Fundamentals Electric Circuits Laboratory
- Efficacy of a Final Lab Practicum and Lab Reports for Assessment in a Fundamentals Electric Circuits Laboratory
- Efficacy of a Final Lab Practicum and Lab Reports for Assessment in a Fundamentals Electric Circuits Laboratory
- Predicting Student Success in an Electrical Engineering Program
- Discrete Convolution Visualization Utilizing a Jupyter Notebook
- Student Participation in EE Lab Teams as a Predictor of Acquired Skills and Knowledge
- "Development of a Small, Robust, and Portable Circuits Training System for an Introductory Course in DC Electrical Circuits"
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