Active Learning Classroom @ VMS: what I have learned from this.

First, let’s start with a short description of Active Learning Classroom, or ACL. ACL is a type of student-centered and technology-rich classroom equipped with movable tables and chairs (however, in our ACL, relocating tables is restricted) aiming at promoting active learning. At Assumption University, ACL is an initiative of Vincent Mary School of Science and Technology (VMS). The President has approved the idea and granted VMS two rooms with necessary facilities (tables with whiteboard paint, chairs, whiteboards, power supply, etc.).

I personally find this an opportunity to diverge myself, as a lecturer, from a traditional teaching method and to transform classroom atmosphere, expecting AU students to engage with the supplied materials (exercises), participate in class, search the Internet (knowledge is out there) and collaborate with each other. The course that I have utilized the ACL is CS1201 Programming I. For the teaching methodology, rather than teaching the course in the computer lab as it used to be, each individual student was asked to bring his/her laptop, installed necessary software. By a lecturer, worksheets with exercises guiding students to advance their computer programming skills have been prepared and disseminated online via VMS portal.

Each week students are provided with a worksheet (with several exercises and guidance). Lecturer now acts as a facilitator coaching students to complete their tasks. Students go through given exercises one by one. If help is needed, the facilitator approaches the student. With this methodology, students are able to advance their knowledge and skills with their own pace. Unlike a traditional teaching and learning method, students have to work out very hard to catch up with lecturer’s pace. Some students may be able to catch up and some may note (as we all know most Thai students are shy and reluctant to break/stop lecturers for questioning).

What I have noticed during the semester, some students are more active, engaging the material, searching for answers/solutions on the Internet, asking more relevant questions, helping each other while others just sit quietly and do their work. To me, I am very satisfied seeing students trying to help each other to solve the problem. I have observed more interactions among students. This soft-skill is also important for their future life. However, it is very unfortunate to witness few inactive students in the class (although I have tried very hard to encourage them) and to observe that a number of students have withdrawn from this course. For academic-wise, I am satisfied with the number of students who pass the course and I have noticed that a sequence of materials provided to students should be revised regularly to suit each individual student batch.

To summarize this review, I would agree that ACL is a very interesting and promising initiative and could be a tool to change the way we want to transform AU students) providing that appropriate contents (exercises, case studies, etc.) are provided and the lecturers themselves change their attitude towards ACL. As it could become disastrous if lecturers just provide some materials and let students be on their own or search for solutions without proper advice/explanation (completely ignore the students). Both lecturers and students will eventually become inactive in the class and be on their own comfort zone until the class ends. Finally, of course, necessary technology-rich facilities should be considered and provided (sometimes the lecturer need to explain something to all students at once).

Mini project in data analytics for first-year IT students (first programming course)

A mini yet exciting project related to big data for first-year IT students (also welcome a student from Martin De Tours School of Management and Economics). After putting their effort and time in learning how to code with Python and practicing data analytics with Pandas, they got their first taste of the mystery of big data (data loading, cleansing, visualization and predictions). Let’s see how they perform……

5725210 Sunepha (Sunepha’s work)(data set)

6010163 Kan (Kan’s work)(data set)

6014085 Chawalit (Chawalit’s work)(data set)

6018302 Thinley (Thinley’s work)(data set)