Complementary role of large language models in educating undergraduate design of distillation column: Methodology development
This paper explores the integration of large language models (LLMs), such as ChatGPT, in chemical engineering education, departing from conventional practices that may not be universally accepted. While there is ongoing debate surrounding the acceptance of LLMs, driven by concerns over computational...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Digital Chemical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772508123000443 |
| _version_ | 1827587829223391232 |
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| author | Zong Yang Kong Vincentius Surya Kurnia Adi Juan Gabriel Segovia-Hernández Jaka Sunarso |
| author_facet | Zong Yang Kong Vincentius Surya Kurnia Adi Juan Gabriel Segovia-Hernández Jaka Sunarso |
| author_sort | Zong Yang Kong |
| collection | DOAJ |
| description | This paper explores the integration of large language models (LLMs), such as ChatGPT, in chemical engineering education, departing from conventional practices that may not be universally accepted. While there is ongoing debate surrounding the acceptance of LLMs, driven by concerns over computational instability and potential inconsistencies, their inevitability in shaping our communication and interaction with technology cannot be ignored. As educators, we are positioned to play a vital role in guiding students toward the responsible, effective, and synergetic use of LLMs. Focusing specifically on distillation column design in undergraduate mass-transfer courses, this study demonstrates how ChatGPT can be utilized as an auxiliary tool to create interactive learning environments and simulate real-world engineering thinking processes. It emphasizes the need for students to develop critical thinking skills and a thorough understanding of LLM principles, taking responsibility for their use and creations. While ChatGPT should not be solely relied upon, its integration with fundamental principles of chemical engineering is crucial. The effectiveness and limitations of ChatGPT are exemplified through two case studies, showcasing the importance of manual calculations and established simulation software as primary tools for guiding and validating engineering results and analyses. This paper also addresses the pedagogical implications of integrating LLMs into mass transfer courses, encompassing curriculum integration, facilitation, guidance, and ethical considerations. Recommendations are provided for incorporating LLMs effectively into the curriculum. Overall, this study contributes to the advancement of chemical engineering education by examining the benefits and limitations of LLMs as educational aids in the design process. |
| first_indexed | 2024-03-09T00:24:33Z |
| format | Article |
| id | doaj.art-b3c06dc0a9bd4a8fb6d0e585d7248da1 |
| institution | Directory Open Access Journal |
| issn | 2772-5081 |
| language | English |
| last_indexed | 2024-03-09T00:24:33Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Digital Chemical Engineering |
| spelling | doaj.art-b3c06dc0a9bd4a8fb6d0e585d7248da12023-12-12T04:37:12ZengElsevierDigital Chemical Engineering2772-50812023-12-019100126Complementary role of large language models in educating undergraduate design of distillation column: Methodology developmentZong Yang Kong0Vincentius Surya Kurnia Adi1Juan Gabriel Segovia-Hernández2Jaka Sunarso3Department of Engineering, School of Engineering and Technology, Sunway University, Bandar Sunway 47500, Selangor, Malaysia; Corresponding authors.Department of Chemical Engineering, National Chung Hsing University, Taichung 40227, Taiwan; Corresponding authors.Universidad de Guanajuato, Campus Guanajuato, División de Ciencias Naturales y Exactas, Departamento de Ingeniería Química, Noria Alta s/n, 36050 Guanajuato, Gto, MexicoResearch Centre for Sustainable Technologies, Faculty of Engineering, Computing and Science, Swinburne University of Technology, Jalan Simpang Tiga, 93350 Kuching, Sarawak, MalaysiaThis paper explores the integration of large language models (LLMs), such as ChatGPT, in chemical engineering education, departing from conventional practices that may not be universally accepted. While there is ongoing debate surrounding the acceptance of LLMs, driven by concerns over computational instability and potential inconsistencies, their inevitability in shaping our communication and interaction with technology cannot be ignored. As educators, we are positioned to play a vital role in guiding students toward the responsible, effective, and synergetic use of LLMs. Focusing specifically on distillation column design in undergraduate mass-transfer courses, this study demonstrates how ChatGPT can be utilized as an auxiliary tool to create interactive learning environments and simulate real-world engineering thinking processes. It emphasizes the need for students to develop critical thinking skills and a thorough understanding of LLM principles, taking responsibility for their use and creations. While ChatGPT should not be solely relied upon, its integration with fundamental principles of chemical engineering is crucial. The effectiveness and limitations of ChatGPT are exemplified through two case studies, showcasing the importance of manual calculations and established simulation software as primary tools for guiding and validating engineering results and analyses. This paper also addresses the pedagogical implications of integrating LLMs into mass transfer courses, encompassing curriculum integration, facilitation, guidance, and ethical considerations. Recommendations are provided for incorporating LLMs effectively into the curriculum. Overall, this study contributes to the advancement of chemical engineering education by examining the benefits and limitations of LLMs as educational aids in the design process.http://www.sciencedirect.com/science/article/pii/S2772508123000443ChatGPTChemical engineering educationLarge language modelsDistillationIndustry 4.0Mass transfer |
| spellingShingle | Zong Yang Kong Vincentius Surya Kurnia Adi Juan Gabriel Segovia-Hernández Jaka Sunarso Complementary role of large language models in educating undergraduate design of distillation column: Methodology development Digital Chemical Engineering ChatGPT Chemical engineering education Large language models Distillation Industry 4.0 Mass transfer |
| title | Complementary role of large language models in educating undergraduate design of distillation column: Methodology development |
| title_full | Complementary role of large language models in educating undergraduate design of distillation column: Methodology development |
| title_fullStr | Complementary role of large language models in educating undergraduate design of distillation column: Methodology development |
| title_full_unstemmed | Complementary role of large language models in educating undergraduate design of distillation column: Methodology development |
| title_short | Complementary role of large language models in educating undergraduate design of distillation column: Methodology development |
| title_sort | complementary role of large language models in educating undergraduate design of distillation column methodology development |
| topic | ChatGPT Chemical engineering education Large language models Distillation Industry 4.0 Mass transfer |
| url | http://www.sciencedirect.com/science/article/pii/S2772508123000443 |
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