System to Enhance and Monitor Group Studying

Schwarz Baruch (Education), HUJI, Faculty of Humanities, School of Education


Virtual teams, Artificial Intelligence (AI), E-learning Platforms, Machine learning, online group learning

Current development stage

TRL4 Technology validated in lab; interested in commercial partnerships     



  • Group work can lead students to develop their academic and social competencies and to create knowledge, but only if they collaborate and argue with each other on learning.
  • Collaborative learning means working on joint tasks, sharing (artefacts), coordinating actions, and creating a common meaning - this is harder to accomplish in an online group learning. The guidance given by the teachers, along with the timing and the adaptivity of teacher's interventions to the needs of the group plays a major role in online group learning.
  • Currently there is no automated or semi-automated way to support collaborative learning in online systems and face the challenges of a real classroom (such as multiple students and limited teacher support).

Our Innovation

  • A novel approach based on Artificial Intelligence (AI) techniques that enable group learning for students using on-line education systems by getting students to engage in collaborative learning
  • Supports collaborative learning of students and identify critical moments in groups that interact together using educational software (e.g., emergence of new ideas, promising patterns of interaction, impasses).
  • Provide recognition of key patterns within group in real time.
  • Provide effective visualization of patterns and interventions to teachers and others educational stakeholder
  • Support large groups while providing automatic recommendations and adaptive interventions even at the single student level



  • SAGLET will be integrated with existing e-learning platforms, analyzing student interactions in these platforms and recommending interventions for teachers through various awareness tools.
  • It includes a sophisticated monitoring and administration dashboard based on state-of-the-art artificial intelligence and machine learning algorithms that presents analytical data to the teacher, receives feedback and decisions and acts upon it.
  • The SAGLET system can be easily applied to schools using existing educational frameworks. It will augment existing technologies to be able to recognize students’ learning styles in the group and to facilitate their interaction.


  • Schools and universities - many of them are expanding their investments in inquiry-based educational tools to meet new educational standards and a growing awareness that rich exploratory environments lead to better learning outcomes.
  • Increase educational outcomes, such as learning gains, attitude and opinion change by students, and the fostering of general reasoning/argumentative capabilities.




Contact for more information:

Anna Pellivert