GrouPer (Group-based Personalization) is an assessment and recommendation system that uses big data and machine learning to assist science teachers in providing personalized instruction. It identifies student knowledge profiles and recommends learning sequences that match their needs. GrouPer also collects teachers’ choices and improves its recommendations based on their collective wisdom. The tool was co-designed with teachers and was recently integrated into PeTeL, a free learning platform that serves teachers across Israel, developed within Weizmann’s Science Teaching Department.
Giora Alexandron
Assistant Professor in the Department of Science Teaching, Weizmann Institute of Science
Giora Alexandron is the head of the Computational Approaches to Science Education (CASEd) research group. His research combines science education and the learning sciences, AI, and human-computer interaction, in order to study and develop learning environments that are more adapted to the needs of different learners. Alexandron’s main focus is on K-12 science education and on Teacher:AI partnership – how AI can work alongside teachers in order to assist them in providing more personalized instruction.
