LETTERS: It is high time to explore the potential, opportunities and challenges of Artificial Intelligence in teaching computer-aided technology courses at universities in Malaysia.
The use of computer-aided technology allows for more efficient and precise design, simulation and production processes, resulting in higher quality products and improved productivity.
At universities, teaching courses in computer-aided technology generally comprise of courses on CAD (computer-aided design), CAE (computer-aided engineering) and CAM (computer-aided manufacturing).
In brief, CAD involves using computer software to create 2D or 3D models of physical objects, CAE involves using computer simulations to analyse the behaviour of these CAD models under different conditions and CAM involves using computer-controlled machines to manufacture physical objects based on the CAD models.
These three fields are closely related and are often taught together as part of a larger programme in applied sciences, engineering or design.
In current practice, CAD/CAE/CAM is taught through a combination of lectures, hands-on projects and computer labs sessions. Lectures provide the theoretical foundation, while projects and lab work allow students to apply their knowledge in a practical setting. However, this approach has several limitations.
Using the traditional practice, it is difficult and time consuming to provide individualised feedback to each student, and it is challenging to design projects and labs that are relevant and engaging for all students. This presents a potential for AI where it can personalise the learning experience by adapting to the needs and abilities of each student.
For example, an AI-powered system could analyse a student's CAD model and identify areas where they need improvement. It could then provide targeted feedback and resources to help the student improve his skills.
This would allow students to learn at their own pace and receive individualised support, especially for courses related to computer-aided technology where there are many different approaches and techniques.
AI could also create more engaging and relevant projects and labs as many computer-aided technology projects and labs are generic and not necessarily related to real-world problems or applications. Students would not be able to relate and apply their natural ability and creativity.
AI could design projects and labs that are tailored to the interests and goals of each student. For example, an AI-powered system could analyse a student's career goals and suggest projects that are relevant to their desired field of work.
In return, the learning experience can be more engaging and meaningful for students. Students become highly motivated and interested in the subject.
Another potential benefit of AI in teaching computer-aided technology is the ability to automate certain tasks and processes. AI could automatically grade assignments so that instructors could focus on more complex and creative tasks.
AI could also be used to analyse student data and identify patterns and trends that may be useful for improving the curriculum or teaching methods. This would allow instructors to spend more time on teaching and less time on administrative tasks that are not contributing to the teaching and learning experience.
However, there are also several challenges in incorporating AI into the teaching of computer-aided technology. One of the biggest challenges is the need for high-quality data.
AI requires large amounts of data to accurately learn and make predictions such as having access to high-quality CAD models, simulation data, and manufacturing data.
Much of this data is proprietary or difficult to obtain, which causing difficulties to train AI models effectively. Both the universities and industry partners would need to collaborate so that the necessary data is available and accessible.
Another challenge is the need for specialised expertise to ensure the success of AI implementation. AI is a complex and rapidly evolving field, and it requires specialised knowledge and skills to develop and implement AI-powered systems.
Universities would need to invest in training their faculty members and staff to acquire the necessary expertise to incorporate AI into CAD/CAE/CAM courses effectively.
The need for a comprehensive framework that outlines the ethical and legal implications of using AI in teaching CAD/CAE/CAM is crucial. There is a risk that AI-powered systems could reinforce stereotypes as well as a risk of intellectual property infringement, especially when AI is used to analyse proprietary data.
Universities and industry partners should also work together to develop policies and guidelines that would ensure that AI is used ethically and responsibly.
In conclusion, AI has the potential to transform the teaching of computer-aided technology at universities by enhancing the learning experience, streamlining tasks, and providing students with the right resources, skills and knowledge to succeed in their career.
DR JUDITH GISIP
Senior Lecturer,
Eco-Technology Programme,
Faculty of Applied Sciences,
Universiti Teknologi Mara
The views expressed in this article are the author's own and do not necessarily reflect those of the New Straits Times