| Course code | AIST2601 |
| Course title | Technology, Society and Engineering Practice 科技、社會及工程實務 |
| Course description | This course teaches the following topics: the impact of technology on society; introduction to engineering as a profession (different engineering fields, professional societies and registration, soft skills for working in a team); engineering design and innovation; introduction to intellectual property (copyright, trademarks, registered design and patents); engineering project management; product safety; professional ethics; liability and responsibility; workplace safety; environmental impact and market requirements; case studies and experience sharing from industry; global energy policies and standards. 本科講授以下的題目：科技對社會的影響；專業工程的介紹（不同工程領域的簡介， 專業工程師學會及註冊， 團隊成員的溝通技巧）；工程設計及創新；知識產權的介紹（版權，商標權，註冊設計權及專利權）；工程項目的管理；產品安全；專業道德；責任及義務；工作場所的安全守則；對環境影響及市場的要求；個案研討；工程師實務經驗的分享；全球性的能源政策和標準。 |
| Unit(s) | 2 |
| Course level | Undergraduate |
| Semester | 2 |
| Exclusion | CSCI3250 or CSCI3251 or ENGG2601 or ENGG2602 |
| Grading basis | Graded |
| Grade Descriptors | A/A-: EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions. B+/B/B-: GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered. C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems. D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems. F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course. |
| Learning outcomes | At the end of the course of studies, students will have acquired the ability to 1. examine the impact of technology on the society and the environment; 2. recognize the contributions of engineers to the society; 3. appreciate the design and innovation aspects of engineering profession; 4. acquire the skills and tools to manage engineering projects; 5. learn the skills for working in a team; 6. understand the value of being an ethical engineer and a responsible citizen. |
| Assessment (for reference only) |
Short answer test or exam: 50% Essays: 25% Presentation: 25% |
| Recommended Reading List | 1. E.A. Stephan et al., Thinking like an engineer: an active learning approach, Pearson Prentice Hall, 3rd ed, 2015. 2. The Hong Kong Institution of Engineers web site (https://www.hkie.org.hk). 3. Intellectual Property Department web site (https://www.ipd.gov.hk). 4. The Office of the Government Chief Information Officer (OGCIO) web site (https://www.ogcio.gov.hk). |
| AISTN programme learning outcomes | Course mapping |
| Upon completion of their studies, students will be able to: | |
| 1. identify, formulate and solve AI-related engineering problems (K/S); | Y |
| 2. design a system, component, or process to meet desired needs within realistic constraints, such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability (K/S/V); |
Y |
| 3. understand the impact of AI solutions in a global and societal context, especially the importance of health, safety and environmental considerations to both workers and the general public (K/V); | Y |
| 4. communicate and work effectively in multi-disciplinary teams (S/V); |
Y |
| 5. apply knowledge of mathematics, science, and engineering appropriate to the AI degree discipline (K/S); |
|
| 6. design and conduct experiments, as well as to analyze and interpret massive data (K/S); | |
| 7. use the techniques, skills, and modern computing tools necessary for engineering practice appropriate to the AI and computing discipline (K/S); | Y |
| 8. understand professional and ethical responsibility (K/V); and | Y |
| 9. recognize the need for and the importance of life-long learning (V). |
Y |
| Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes | |