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In this paper, the authors review extant natural language processing models in the context of undergraduate mechanical engineering education. These models have advanced to a stage where it has become increasingly more difficult to discern computer vs. human-produced material, and as a result, have understandably raised questions about their impact on academic integrity. As part of our review, we perform two sets of tests with OpenAI's natural language processing model (1) using GPT-3 to generate text for a mechanical engineering laboratory report and (2) using Codex to generate code for an automation and control systems laboratory. Our results show that natural language processing is a potentially powerful assistive technology for engineering students. However, it is a technology that must be used with care, given its potential to enable cheating and plagiarism behaviours given how the technology challenges traditional assessment practices and traditional notions of authorship. [ABSTRACT FROM AUTHOR]

Undergraduate research has a significant positive impact on the students’ educational experience but has many implementation challenges in curricular or co-curricular activities. This paper presents an approach for introducing undergraduate research to engineering students in a Numerical Analysis of Engineering Systems course, which is typically a junior-level undergraduate course in most engineering departments. A course project was designed to allow the participating students to work in teams, read an assigned research paper that presents an exact solution of a problem related to smart materials and structures, locate the main equations, and write a computer code that uses these equations to regenerate the published results. Each team of students gave a presentation on the assigned paper, the main equations, the code developed to regenerate the results and graphs, with interpretations and conclusions. The project is contributing to the course outcomes and learning objectives as well as multiple ABET student outcomes. Final survey showed the effectiveness of the proposed project in introducing students to undergraduate research, and giving them the chance to understand the technical and mathematical language used in research papers, and experience working on new challenging problems. The approach does not need involvement of multiple faculty members, or large funds and resources. The theme of the assigned research papers is dependent on the instructor’s field of research. The approach can be easily extended to other courses that teach computational methods and tools. The paper presents sample student projects and lessons learned in implementing the proposed approach. [ABSTRACT FROM AUTHOR]

Delivery of manufacturing technology and practical workshop-based work, on undergraduate engineering courses that engage the learners, is challenging. The paper presents an experimental method of workshop delivery using the flipped learning approach, a pedagogical model in which the typical lecture and homework elements of a course are reversed. Video lectures are viewed by students prior to class. In-class time can be devoted to exercises, projects, or discussions as in this case. Learners were asked to observe three audiovisual clips in preparation for class. The objective was to determine whether the flipped classroom approach can enhance the learning experience, through better engagement with the students, compared to conventional classroom-based learning. The level of student participation and level of success have been established by means of feedback questionnaires from more than 100 participants and peer observation. The results are encouraging and demonstrate that this approach is favoured by the students. [ABSTRACT FROM AUTHOR]