Improving Student Learning of Energy Systems through Computational Tool Development Process in Engineering Courses

• Main Authors: Jian Zhang, Heejin Cho, Pedro J. Mago
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: Sustainability
• Subjects: higher education; computer-based instruction; power generation systems; computational tool; exergy analysis
• Online Access: https://www.mdpi.com/2071-1050/13/2/884

Advancements in computer and mobile technologies have driven transformations of classroom activities in engineering education. This evolution provides instructors more opportunities to introduce computational tools that can be effectively used and promoted in engineering education to advance students’ learning process when the tools are appropriately utilized in the classroom activities. This paper presents a methodology to improve student learning of energy systems through a class assignment implementing a self-developed computational tool using Microsoft Excel and utilizing the tool to enhance their learning experience. The proposed method, a student-centered learning approach, was applied in a technical elective course called “Power Generation Systems” within a mechanical engineering curriculum. In the course, students were guided to develop a computational tool by themselves based on their learning of the fundamental principles and governing equations of a thermodynamics cycle. The self-developed computational tool allows the students to focus on more design-oriented problems, instead of the calculation process. Using the self-developed tool, students can have an enhanced understanding of the energy system performance in varying design and operational conditions and can perform the parametric analysis and visualization of essential parameters. Feedback from the students and class instructors proves that the self-development and use of the tool can significantly improve the students’ learning experience in the implemented course, make the course more dynamic, and motivate the students to learn the material more iteratively. In addition, students feel confident using computational tools to perform analysis, and are willing to develop more tools for other energy-related engineering applications.