Using TRIZ10 for enhancing creativity in engineering design education

One of the popular creativity methods to solve technical problems is the Theory of Inventive Problem Solving, (TRIZ), however, requires a considerable investment of time. A teaching methodology for a simplified version of TRIZ (TRIZ10) has been developed for reducing learning time and improving the creative process in solving technical problems. This method has been applied in a small group of engineering design students as a proof of concept. The evaluation of the results obtained shows that students achieved adequate learning of this creative technique (75% overall efficiency). This method has led to the doubling of the number ideas developed by students compared to those generated before learning TRIZ10; further, it also improves a 10% the average degree of novelty for these ideas.

Challenges and Strategies in Remote Design Collaboration During Pandemic: A Case Study in Engineering Education

The COVID-19 pandemic forced college education to shift from face-to-face to online instruction. This effort is particularly challenging for freshmen and sophomore students, in engineering design projects where collaborations are needed. The study aims to qualitatively understand challenges and possible strategies revealed by students in remote design collaboration through the lens of an undergraduate-level engineering design introduction class. The authors closely observed team members’ struggles and how they handled them through bi-weekly and final reflections in a semester-long project. The challenges and strategies from 11 teams (42 students) were analyzed and implications for future engineering design education were discussed. The findings provide insights to experimentations that aim to establish a successful remote learning environment that reaches core education objectives of engineering design while also helping students adapt to a geographically distributed engineering workforce in future. The study also illustrated the usefulness of reflections as a tool to capture students’ learning dynamics.

AN EXPERIENTIAL LEARNING APPROACH FOR DEVELOPING MENTAL MODELS IN ENGINEERING DESIGN EDUCATION

Mental simulation represents how a person interprets and understands the causal relations associated with the perceived information, and it is considered an important cognitive device to support engineering design activities. Mental models are considered information characterized in a person’s mind to understand the external world. They are important components to support effective mental simulation. This paper begins with a discussion on the experiential learning approach and how it supports learners in developing mental models for design activities. Following that, the paper looks at the four types of mental models: object, making, analysis and project, and illustrates how they capture different aspects and skills of design activities. Finally, the paper proposes an alternative framework, i.e., Spiral Learning Approach, which is an integration of Kolb’s experiential learningcycle and the Imaginative Education (IE) framework. While the Kolb’s cycle informs a pattern to leverage personal experiences to reusable knowledge, the IE’s framework suggests how prior experiences can trigger imagination and advance understandings. A hypothetical design of a snow removal device is used to illustrate the ideas of design-related mental models and the spirallearning approach.

Distinguishing Hand Drawing Style Based on Multilevel Analytics Framework

Hand drawing is an indispensable professional skill in the fields of environmental design, industrial design, architectural engineering, civil engineering, and other engineering design education. Students usually imitate masterpieces to practice basic skills, which is an important link for a beginner. A system for digital management requires a function for an automatic recommendation task of different brushwork skill expressions. Thus, the classification method for brushwork is to combine hand-crafted features generated by DCNN and then use the final features for input to a tree structure classification scheme. The method improvement of the other deep learning models has effectiveness in distinguishing art ontology attributes.

Development of an AI Userbot for Engineering Design Education Using an Intent and Flow Combined Framework

As the inclusion of users in the design process receives greater attention, designers need to not only understand users, but also further cooperate with them. Therefore, engineering design education should also follow this trend, in order to enhance students’ ability to communicate and cooperate with users in the design practice. However, it is difficult to find users on teaching sites to cooperate with students because of time and budgetary constraints. With the development of artificial intelligence (AI) technology in recent years, chatbots may be the solution to finding specific users to participate in teaching. This study used Dialogflow and Google Assistant to build a system architecture, and applied methods of persona and semi-structured interviews to develop AI virtual product users. The system has a compound dialog mode (combining intent- and flow-based dialog modes), with which multiple chatbots can cooperate with students in the form of oral dialog. After four college students interacted with AI userbots, it was proven that this system can effectively participate in student design activities in the early stage of design. In the future, more AI userbots could be developed based on this system, according to different engineering design projects for engineering design teaching.