designing future technologIES @ A*STAR, Singapore
designing future technologIES @ A*STAR, Singapore
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A global leader in science, technology and open innovation
The Agency for Science, Technology and Research, Singapore (A*STAR) is a catalyst, enabler and convenor of significant research initiatives among the research community in Singapore.
As a Science and Technology Organisation, A*STAR bridges the gap between academia and industry in terms of research and development.
A*STAR drives research that advances scientific discovery and technological innovation. It plays a key role in nurturing and developing talent and leaders for Singapore, the wider research community, and industry.
MANAGING A*STAR RESEARCH — Cognitive Tracking PROJECT
MANAGING A*STAR RESEARCH — Cognitive Tracking PROJECT
DiaCog's cognitive tracking improves learning and communication.
DiaCog's cognitive tracking improves learning and communication.
I orchestrated a flagship AI project — Dialog Games for Cognitive Tracking (DiaCog) in A*STAR, Singapore (3 years).
We developed a conversational UI which facilitates social interaction in dialogs to support the improvement of critical thinking and knowledge building skills.
Our research studies show that DiaCog improves learning by encouraging students to have more scientific argumentation, topic cohesion, and understanding and better idea communications.
Design Concept and Science Behind
Design Concept and Science Behind
DiaCog's dialog tracking functions allow students and teachers to assess the degree to which common understanding, joint learning, and knowledge building occur in dialogs.DiaCog uses a unique technique of cognitive mapping functions. DiaCog dynamically creates interactive cognitive maps of the social interactions throughout the dialog and visualizes dialog interactions.
DiaCog Research
Phase 1: We compared the use of a chat app versus DiaCog and obtained feedback from students on their liking and perception of quality of the interaction in both conditions. We use the insights from the research studies for improving the interface features for optimizing students’ ease of use of the application.
Phase 2: We comprehensively tested whether DiaCogtool promotes collaborative learning and whether the degree of concept overlap in student dialogs is linked to better knowledge-building.
Results: The results showed that DiaCog improves learning, motivate students to and help them to understand topics with stronger communication of ideas.
To date, DiaCog research has been published in several journal articles and conference proceedings.
researching Social Robots' design
researching Social Robots' design
Dragon Robot is able to manage the tutoring process.
Dragon Robot is able to manage the tutoring process.
Before DiaCog, I was a research expert in “Social Tutoring Robot” project in A*STAR Singapore (3 years).
Social Tutoring Robot project was implemented to design and develop a robot tutor that is able to show social behaviors to support after class learning activities. To enable such a scenario we created the Dragon Robot that can engage social interaction with students.
The project took 3 years under Intuitive Interaction Technologies Group, which was formed by psychologists, computer science and artificial intelligence researchers, robotics, cognitive and social psychologists, computational linguists and an instructional technologist.
Design Concept and Science Behind
Design Concept and Science Behind
The main design goal for the Dragon Robot was to design a robot that can recognize students' cognitive and emotional states and calibrate his behavior and interaction channels toward the states of the students.
Another objective was to design pedagogic activities with Drago Robot that can significantly improve the learning experiences.
In this project, I created a learning interactions framework and interactive learning activities that guide the roles and behaviors of our social robot in the facilitation of learning.
Tutoring Robot Research
I also contributed to the administration of the user experiments run in Singapore schools (e.g. German European School) that investigated the impact of interactions with the social tutoring robot. We facilitated the user research studies in which students learned secondary language rules from a robot tutor.
Results: Results of these studies showed that the tutoring robot is able to lead students’ attention and manage the tutoring process. However, research results also indicated that the robot design should be improved to address the needs of a typical classroom and one on one tutoring scenarios.
To date, Tutoring Robot research has been published in several journal articles and conference proceedings.
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