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Overview

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Overview


Overview 

SAILI is currently incubating and piloting a new initiative called Huddle. Huddle is designing and prototyping an end to end Blended Learning Classroom solution that leverages technology, human resources and physical spaces to deliver high quality, accessible education.

Imagine the best teachers in South Africa (whom Huddle refer to as the ‘Springbok’ teaching team) planning, designing and delivering extremely rigorous, pre-recorded curriculum (CAPS) aligned lessons (underpinned by proven pedagogy) to millions of learners via the Huddle platform. These lessons are accessed by learners through laptops in internet enabled classrooms and workbooks which are couriered onsite. A blended learning facilitator or teacher manages the class and ensures learners feel safe, seen and loved. Facilitators also focus their attention on “closing the learning gaps” which are easily identified through data dashboards available on the Huddle platform, which provide real time feedback on each learner’s mastery and progress throughout a single lesson. In classes where learners do not have access to personal devices, lessons are projected and teachers are prompted to check the understanding of learners throughout. Workbooks accompany projected lessons to increase the rigor and engagement of the lessons.

SAILI Target School Performance Posters

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Since 2018, SAILI has been working with provincial education departments. Education departments are daily recipients of vast amounts of complex data and it differs from that of schools in its volume, content and complexity.  Our aim is to coach department data users and consumers to;

  • Optimise data usage; 
  • Maximise relevance of data and reports for end-users; and
  • Facilitate getting the right data and reports to the right consumers

SAILI’s strength is its ability to remain impartial and identify anomalies and trends in data sets. Exposing trends and anomalies by applying a new, external lens allows education departments to make strategic and operational decisions in previously unidentified and/or unsupported areas.

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