Postdocs, PhD, master, undergraduate, intern, exchange/visiting student
In a blended learning environment where learning activities span across physical and digital spaces, effective learning relies heavily on a students' ability to manage these activities in real time. How a teacher manages multi-layered learning activities in a multi-constraints context is known as classroom orchestration . In this project we expand the scope of classroom orchestration to cover learning activities both in and outside classroom, with the purpose of generating a full spectrum of a user's learning activity record.
This project aims to develop a mobile app—StudySpectrum—that enables the tracking and visualizing of learning activities in and outside classroom. StudySpectrum generates a digital footprint of learning orchestration that allows teachers to reflect their teaching in-and-on-action.
 P Dillenbourg (2013). Design for classroom orchestration. Computers & Education 69:485-492.
This research project may involve the following activities:
systematic literature reviews to understand the theoretical foundation of classroom orchestration
prototype development of StudySpectrum with different platforms (e.g., iOS, Android, web)
data visualization design and user experience evaluations
field study of StudySpectrum with instructors and students
quantitative and qualitative data analysis
co-author research papers and give presentations in academic conferences
Upon conclusion of this research, you will gain:
experience in app development.
knowledge in both quantitative and qualitative research methods.
domain knowledge in educational technology and learning analytics.
knowledge in human computer interaction.
skills in project management and technical communication.
Skills and experience
As the ideal candidate, you'll have a passion for improving teaching and learning and a strong background in interactive design/human-computer interaction or app development.
Dr. Mario Alberto Chapa-Martell (Silver Egg Technology, Japan)
Dr. Satoshi Nishimura (AIST, Japan)
Dr. Takuichi Nishimura (AIST, Japan)
Liang Z, Nishimura S, Nishimura T, Chapa-Martell MA. (2018). Investigating classroom activities in English conversation lessons based on activity coding and data visualization. Lecture Notes in Artificial Intelligence. Berlin: Springer.
Liang Z, Nishimura S, Nishimura T, Chapa-Martell MA. (2018). LessonSpectrum: visualizing teaching and learning activities in English conversation lessons. Orchestrating Learning Analytics (OrLA) workshop, Sydney, Australia.
Liang Z, Nishimura S, Nishimura T, Chapa-Martell MA. (2017). Understanding teachers' time management in English conversation classes using experience sampling method and data visualization. International Workshop on Knowledge Explication for Industry, Tokyo, Japan.