Information For:

Give back to HGSE and support the next generation of passionate educators and innovative leaders.

Faculty & Research

Bertrand Schneider

Assistant Professor of Education

Bertrand Schneider

Degree:  Ph.D., Stanford University, (2015)
Email:  [javascript protected email address]
Phone:  617.496.2094
Office:  Longfellow 333
Faculty Assistant:  Claire Goggin

Profile

Bertrand Schneider graduated from the Learning Sciences and Technology Design program at Stanford University and was most recently a postdoctoral researcher at the Transformative Learning Technologies Laboratory. His interests include the development of educational interfaces (e.g., tangible, multitouch, pen/paper based) for collaborative learning in formal and informal learning environments. Additionally, he researches the use of multi-modal data (e.g., gaze, body movement, speech, arousal) to visualize and assess students' learning trajectories.

Click here to see a full list of Bertrand Schneider's courses.

Sponsored Projects

EAGER: Making with Understanding (2017-2019)
National Science Foundation

Emerging technologies, such as Augmented Reality (AR), have the potential to radically transform STEM education (Science, Technology, Engineering, Mathematics) by making challenging concepts visible to students. It is now possible to design activities where learners can “see” hidden forces in the world around them (e.g., electricity, magnetic fields, light waves). This proposal focuses on maker spaces and describes how AR can promote making with understanding by augmenting traditional activities in maker spaces with digital information. For example, students could be building a speaker from scratch (in which amplified electrical signals are converted into magnetic fields) and the system would display the flow of electrons, magnetic forces or sensor values. This research includes empirical studies to compare the usefulness of AR-based learning with traditional approaches, and follow-up studies to identify their affordances for collaborative learning. Results will be analyzed using traditional quantitative and qualitative methods, along with techniques from the field of Multi-Modal Learning analytics to understand how students’ behavior varies across conditions. This work will 1) contribute to our understanding of how new technologies, such as AR, can facilitate the understanding of ideas in STEM, and 2) produce guidelines to help the design of innovative learning environments.

News Stories