Vietnam Excels in Student Engagement and Smooth Organization

After my two-week whirlwind teaching-tour of Indonesia, I was looking forward to Vietnam where I would settle down in one place and spend four days at a university known for its strong students. My hopes for the visit were met, and surpassed! Things were about as smooth and successful as I could ask for at any stop: The “classic” program included a one-day Design Thinking & Collaborative Problem Solving workshop with an enthusiastic group of students, staff, faculty, and professionals, followed by a three-day Big Data course with students and lecturers who were well prepared and deeply engaged.

The Hanoi University of Science and Technology (HUST) faculty member organizing my visit did an excellent job with advanced planning, and a cheerful and competent student assistant was on hand 24-7 to make sure everything ran smoothly. Hanoi’s Old Quarter, where my comfortable hotel was located, is vibrant chaos like no other place — seemingly unchanged from when I visited as a tourist in 2008 — and the food was uniformly excellent. I was able to resume my daily morning runs, joining all manner of Vietnamese doing all manner of exercise on the perimeter of Hoan Kiem Lake at dawn. (Several urban locations in Indonesia were completely unsuitable for outdoor running, and my standards are quite low!)

Hoan Kiem Lake is a very popular spot for early morning exercise. I enjoyed it every day.

The classroom for the Big Data course was bright and comfortable with a pair of reliable projectors and a working microphone, not amenities to be taken for granted! The only glitch, and we got through it, was finicky internet connectivity. The organizers had gone round and round with the university’s network services department, in the end needing to cobble together extra wifi hotspots themselves. (Even in Vietnamese I could tell when organizers and students were making disparaging remarks about the network services folks, seemingly a worldwide phenomenon.) I’m constantly re-evaluating my decision to have the Big Data hands-on material require reliable internet, but I’m going to stick with it for the time being as the alternative would make material distribution and computing environment considerations quite a bit more complex.

The Big Data students were a pleasure to teach (as were the Design Thinking workshop participants, for that matter). When we reached the end of the third and final day, I offered to stay an extra hour and cover one more module; the students voted overwhelmingly to do so. Then they asked if I would stay yet another hour to answer free-form questions. We covered topics ranging from trending Computer Science research areas, to Big Data computing systems, to the trajectory of my own career, to whether Artificial Intelligence will ever create conscious machines, to, inevitably, the USA Presidential election.

The well-equipped classroom and enthusiastic students for the three-day Big Data course at HUST.

I’m starting to learn what ingredients make for successful visits on the programmatic side. For Design Thinking workshops, the more diverse the participants are, the better: learning to brainstorm in teams and build on other viewpoints is an important part of the Design Thinking process. I can tell that the workshops have been most eye-opening for participants when the roster includes a mix of different interests and seniorities; even better when the people don’t know each other well. In the format I use, four- and five-person teams work together much of the day, and teams are created after an hour or so based on my intuition, or simple randomness. This time the host planned team composition in advance ensuring diversity and unfamiliarity — it worked very well.

Design Thinking & Collaborative Problem Solving workshops tend to look similar on the surface, but each workshop and each team has a different character.

For Big Data, one significant challenge is trying to use the same set of materials for widely different audiences. At HUST we were able to cover a lot of ground because the students have strong skills and resonated well with the material, teaching style, and expectations. Other places haven’t always gone as smoothly. I do have some topics and assignments that I can skip when I sense the material might be too challenging, and of course I can always moderate the pace. When students seem to be comprehending quickly (or even more obviously when they’re finishing assignments quickly), I try to expound on more advanced topics, and I have a few extra-challenging problems up my sleeve.

Ideally I’d have designed all of the material to be highly customizable and flexible, but that would have been an untold amount of work! As it is, the time I’ve spent preparing and constantly revising the Big Data material and logistics has dramatically exceeded what I anticipated. For those in the know, I’ll just say that the effort involved in developing a MOIC (Massive Open In-Person Course), including the requisite internationalization and perfection, in my experience is at least on par with developing a MOOC (Massive Open Online Course) and perhaps quite a bit more. But the rewards in worldwide student appreciation are equally great, and one big advantage of a MOIC is reaping those rewards in person.

Big Data participant group photo — Hanoi University of Science and Technology.