Teaching optimization of manufacturing problems via code components of a Jupyter Notebook

• Published in: Computer applications in engineering education Vol. 26; no. 5; pp. 1102 - 1110
• Main Authors: Suárez, Andres, Alvarez‐Feijoo, Miguel A., Fernández González, Raquel, Arce, Elena
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.09.2018
• Subjects: Engineering education; Judgments; Jupyter Notebook; learning laboratories; Mathematical analysis; Mechanical engineering; Organic chemistry; self‐directed learning; Students; teaching methods; Technical education; virtual environments; Virtual reality
• ISSN: 1061-3773; 1099-0542
• DOI: 10.1002/cae.21941

The Degree in Mechanical Engineering combines knowledge and skills of the academic STEM disciplines (Science, Technology, Engineering, and Mathematics). The teaching of the STEM subjects must give prominence to the association of the physical, chemical, and mathematical concepts with the real world. The Jupyter Notebook can be defined as a scientific interactive framework. They can contain text, mathematical equations, interactive graphs, and videos. It allows creating a workspace for watching and playing with the concepts to be learned. Because of their didactic usefulness and easy divulgation, they are highly recommended as a learning environment. In the present work, there are reflected the experiences of using interactive Jupyter Notebook in virtual laboratory sessions within a 4th year subject of Mechanical Engineering related with manufacturing processes. Students' judgments on the efficacy of this resource were evaluated. The results showed that students are in agreement on the effectiveness of using Jupyter notebooks as a teaching‐learning tool.