2026-06-27T23:36:01Zhttps://docta.ucm.es/rest/oai/request
oai:docta.ucm.es:20.500.14352/1377492026-06-26T00:07:44Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense author Domínguez Toribio, Juan Carlos author Alonso Rubio, María Virginia author González Gómez, Emilio José author Guijarro Gil, María Isabel author Miranda Carreño, Rubén author Oliet Pala, María Mercedes author Rigual Hernández, Victoria de los Ángeles author Toledo Gabriel, José Manuel author Yustos Cuesta, Pedro author Villar Chavero, María del Mar 2026-06-25T08:18:10Z 2026-06-25T08:18:10Z 2021 J.C. Domínguez, M.V. Alonso, E.J. González, M.I. Guijarro, R. Miranda, M. Oliet, V. Rigual, J.M. Toledo, M.M. Villar-Chavero, P. Yustos, Teaching chemical engineering using Jupyter notebook: Problem generators and lecturing tools, Education for Chemical Engineers, Volume 37, 2021, Pages 1-10, ISSN 1749-7728, https://doi.org/10.1016/j.ece.2021.06.004. (https://www.sciencedirect.com/science/article/pii/S1749772821000397) 10.1016/j.ece.2021.06.004 https://hdl.handle.net/20.500.14352/137749 The primary objective of this study is to develop teaching materials for chemical engineering students (or students pursuing other related B.Sc./M.Sc. degrees) that encourage self-learning to facilitate understanding and the development of problem-solving skills. Tools are oriented to support the teaching of “Introduction to Chemical Engineering” courses to 1st year B.Sc. students in Chemical Engineering, 2nd year B.Sc. students in Chemistry, and 3rd year B.Sc. students in Biochemistry at the Universidad Complutense de Madrid (UCM). Problem generators of standard exercises, as an additional complement to the exercises that are used in the lectures, seminars, and assignments to facilitate the learning of the students, have been developed. These generators provide exercises to students with “unlimited” initial values (with certain restrictions). The software that was used to develop these materials was Jupyter Notebook, which runs under the Python 3.6 language. The problem generators can be classified into fixed problem generators, case-based generators, and random problem generators. Additionally, lecturing tools have been developed to support teaching using live/interactive examples. These examples can learning understanding of various topics of the courses. eng Teaching chemical engineering using Jupyter notebook: Problem generators and lecturing tools journal article 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URL https://docta.ucm.es/bitstreams/708efc27-8a34-449b-b436-2525a3fcc816/download File MD5 7a3f3d38a059dcb427b1bc21a2522e0c 3270729 application/pdf 1-s2.0-S1749772821000397-main.pdf