PETAL : Learning the Android Way

Taha Sabih — Sun, 10 Nov 2013 20:45:40 +0000

by Taha Sabih | Photo Credits: Taha Sabih | 11 November 2013

It has been widely accepted that technology now plays a very important role in education delivery and retention. In the Department of Electrical and Electronic Engineering (EEE), Dr. Vincent Tam and Dr. Edmund Lam have been doing extensive research on e-learning deliverables. They discussed with us their projects. A light and fun one called PETAL over the summer; and a larger-scaled research COMPAD+ which has been applied in the learning of all EEE students since last year.

PETAL

Dr. Tam has been heading the research on e-learning in the faculty, and this past summer was joined by some interns from MIT. Dr. Lam had been in contact with MISTI (MIT International Science and Technology Initiatives), and got to know that he would be receiving a few interns. He then contacted Dr. Tam to discuss what could be an interesting project for the incoming interns. Together, they came up with PETAL (Personalized Teaching And Learning), an android program to aid learning.

Dr. Lam had research interests in image processing, so the team decided to make use of the camera on a tablet for PETAL. The trick was to figure out how could the camera be used to aid with the objectives (primarily course delivery). Since the camera was the common denominator in portable PCs, it was a good idea to use that since the software developed could be scaled and/or ported to different environments as necessary.

Dr. Vincent Tam

Dr. Edmund Y. Lam

To start, they decided to implement a system which would work on lecture delivery tools. The initial idea was to use the camera to keep ‘an eye’ on the viewer non-invasively.

Dr. Lam clarifies, ‘if the camera can point to you while you are watching an online video, it can extract information about how you respond to the lecture; in more simple terms, if it can detect that you are sleeping, it knows that you got bored.’

They came up with a few scenarios which might be of use. For example, if the camera detects that you are too close to the camera, it might pop-up a warning that you are too close and may be vulnerable to short-sightedness if this behavior continues. It could also detect expressions of being confused, bored or distraction, and pause the video at that point. More importantly, it could be used to extract underlying data about the quality of the lecture.

Dr. Lam mentions one such instance, ‘if the lecture is distributed to 100 students, and 80 of them get bored or confused 10 minutes into the video, then we can send the lecture back to the instructor telling him that maybe you are getting too fast because students are losing sight of what you are trying to say. Hence all these learning analytics information can be extracted non-intrusively without asking the viewers explicit questions.

The technology behind is not new, but this implementation is a very novel idea.

PETAL uses facial recognition algorithms to detect feature changes in expressions. These algorithms were developed with help from OpenCV (Open Source Computer Vision Library), and of course borrowing from the knowledge of Dr. Lam.

PETAL Eye Tracking: Striking a pose

Dr. Tam also mentioned that the two of them have collaborated before. Dr. Tam has extensive experience in e-learning applications. He developed a gesture-recognition system two years ago, which later facilitated the development of mobile applications for the Heep Hong Society, an organization for students with learning deficiencies.

This collaboration brings out the practical aspect of the research done in the department, with many benefits becoming exceedingly clear when deliverables are used.

About the Author

Taha Sabih

Regular Contributor

Third Year, Electrical Engineering and Economics

COMPAD + : An Interactive E-Learning System

Taha Sabih — Sat, 09 Nov 2013 21:13:35 +0000

by Taha Sabih | 11 November 2013

It has been widely accepted that technology now plays a very important role in education delivery and retention. In the Department of Electrical and Electronic Engineering (EEE), Dr. Vincent Tam and Dr. Edmund Lam have been doing extensive research on e-learning deliverable. They discussed with us their projects. A light and fun one called PETAL over the summer; and a larger-scaled research COMPAD+ which has been applied in the learning of all EEE students since last year.

COMPAD+ is a computer architecture simulator developed in collaboration with colleagues from the Electrical and Electronic Engineering and the Computer Science departments, with funding from Microsoft Research Asia (MSRA).

COMPAD, short for Learning Pad for Computers, is a project that started a few years ago. It makes EEE classes more interactive by letting students doodle system architecture sketches on a windows CE tablet and generate digital diagrams with handwriting recognition. Handwritten symbols such as μP for micro-processor, I/O for input/output are readily recognized.

COMPAD+ is a continuation of the project on a new platform — the Windows Azure Cloud — to build a flexible and interactive simulator to work on any platform and operating system through your browser.

The support from MSRA is important here; the Azure platform would cost US$1500 a year if industrial pricing applies.

COMPAD+ is now being used for the Computer Architecture and Microprocessors course for engineering freshmen. Dr. Tam talked about how the simulator could be used for other courses as well, “the simulator architecture is applicable to more advanced simulations as well, such as the graduate level course, High Performance Computer Architecture. We have made a library of different architecture models, and the system can do the retrieval of these different models as required from the cloud.”

Dr. Vincent Tam

Dr. Edmund Y. Lam

The COMPAD+ cloudapp

Visit here

The prototype has already been released to freshmen last year, and has been used with very positive reviews.

Furthermore, Dr. Tam has also collaborated with the university’s Centre for the Enhancement of Teaching and Learning – CETL to conduct evaluation of the COMPAD+ platform. The team has already published two papers on the platform (Building an Interactive Simulator on A Cloud Computing Platform to Enhance Students’ Understanding of Computer Systems, 2013 IEEE 13th International Conference on Advanced Learning Technologies) and hope to go on further from this point.

Since everything is done on the cloud, it gives rise to interesting ways the software can be used. One such approach might be for high-frequency trading. The software can access and deliver information from the cloud at very high speeds, and aid in simulation for such trades on the stock market.

It is interesting to note that in the COMPAD+ simulator, one can vary the speed of the simulation, but in the case of applications in trading, the simulation speeds are much higher, in the order of hundreds of transactions per second.