Yuqi Peng

This paper explores the often-overlooked role of teaching assistants (TAs) in engineering ethics courses, and a particular challenge that TAs face in these roles. TAs not only undertake tasks like instructors, which include teaching, guiding, and evaluating courses, but they also assume the roles of “intermediaries between instructors and students” and “learners becoming teachers.” These distinct roles present TAs with unique challenges, one of which we call the neutrality problem. This problem pertains to whether TAs can and should maintain a neutral stance in the classroom, particularly when students articulate ideas that deviate from the values promoted in the course or held by the TAs. Using a real-life teaching experience as illustrative, we claim that it is challenging and, at times, undesirable for TAs to achieve pedagogical neutrality, primarily due to their pre-existing understanding of ethics and the actual situation of the students. Nevertheless, we posit that TAs should strive to foster an environment where students are encouraged to improve their ethical awareness. Through the underrepresented lens of TAs, we aim to initiate a multi-faceted dialogue on the teaching philosophy and goal of engineering ethics.

To facilitate engineering students’ understanding of engineering ethics and support instructors in developing course content, this study introduces an innovative educational tool drawing inspiration from the Rubik’s Cube metaphor. This Engineering Ethics Knowledge Rubik’s Cube (EEKRC) integrates six key aspects—ethical theories, codes of ethics, ethical issues, engineering disciplines, stakeholders, and life cycle—identified through an analysis of engineering ethics textbooks and courses across the United States, Singapore, and China. This analysis underpins the selection of the six aspects, reflecting the shared and unique elements of engineering ethics education in these regions. In an engineering ethics course, the EEKRC serves multiple functions: it provides visual support for grasping engineering ethics concepts, acts as a pedagogical guide for both experienced and inexperienced educators in course design, offers a complementary assessment method for evaluating students learning outcomes, and assists as a reference for students engaging in ethical analysis.

© 2015 Macmillan Publishers Limited All rights reserved. Genome-wide gene expression measurements have enabled comprehensive studies that integrate the changes of gene expression and phenotypic information to uncover their novel associations. Here we reported the association analysis between psychophysical phenotypes and genome-wide gene expression changes in human adaptation to one of the most extreme climates on Earth, the Antarctic Dome Argus. Dome A is the highest ice feature in Antarctica, and may be the coldest, driest and windiest location on earth. It is considered unapproachable due to its hostile environment. In 2007, a Chinese team of 17 male explorers made the expedition to Dome A for scientific investigation. Overall, 133 psychophysical phenotypes were recorded, and genome-wide gene expression profiles from the blood samples of the explorers were measured before their departure and upon their arrival at Dome A. We found that mood disturbances, including tension, depression, anger and fatigue, had a strong, positive, linear relationship with the level of a male sex hormone, testosterone, using the Pearson correlation coefficient analysis. We also demonstrated that significantly lowest-level Gene Ontology groups in changes of gene expression in blood cells with erythrocyte removal were consistent with the adaptation of the psychophysical characteristics. Interestingly, we discovered a list of genes that were strongly related to significant phenotypes using phenotype and gene expression PCC analysis. Importantly, among the 70 genes that were identified, most were significantly related to mood disturbances, where 42 genes have been reported in the literature mining, suggesting that the other 28 genes were likely novel genes involved in the mood disturbance mechanism. Taken together, our association analysis provides a reliable method to uncover novel genes and mechanisms related to phenotypes, although further studies are needed.