Mosaix combines the course content and activity delivery with group discussions, multimedia sharing, and embedded assessment.

Mosaix model

Step 1: The teacher uploads lesson content and/or lesson activities.

Step 2: Students can discuss lesson content, and respond to lesson activities.

Step 3: Students give feedback to other student’s responses. Students can submit additional responses as they learn from other student’s responses and feedbacks.

Step 4: Mosaix uses its deep learning analytics engine to assess the student’s understanding. This automated assessment can either be used by the teacher as a recommendation or as a final assessment.

The Mosaix deep analytics engine is able to accurately assess responses and feedback, independent of subject (mathematics, poetry, etc.) or medium (e.g. video, text, audio, photo, etc.). It achieves this by looking at the student’s ‘tune of understanding’, not just each response in isolation. This much broader range of inputs allows the assessment engine to measure

  • the student’s accuracy of understanding,
  • the student’s effective communication of understanding,
  • the student’s speed of understanding, and
  • the teacher’s clarity in delivering the lesson content.

And this doesn’t even scratch the surface of its capabilities!

 

Evidence for Mosaix

“We’ve been looking at a number of learning management systems, and we believe that this goes above and beyond…” 
Sue Maslen, General Manager Student and Academic Services at CIT, 2017.

Mosaix partnered with one of the leading vocational educational providers in Australia, the Canberra Institute of Technology (CIT), to conduct a series of trials. Analysis of data showed (with a statistical confidence interval of 80%):

  • 7.8% increase in demonstrated understanding when compared to the conventional assessment approach of an assignment plus an exam
  • 78.9% alignment between Mosaix assessment and the rubric assessment of in-class activities
  • 14.4% average class learning improvement, when compared to CIT’s conventional approach
  • 85.0% average class rating for student’s ability to solve unknown but somewhat related problems.

In 2018, CIT have started using Mosaix for 2 subjects, with 4 more to use it before the end of this semester. Next semester, CIT are planning to add a further 20 subjects.

The Australian National University (ANU) and the University of Canberra (UC) are also considering Mosaix for courses including sociology and computer science.

How easy is Mosaix to implement for an educational institution?

Mosaix can be implemented per teacher, per subject. So it is incredibly easy to implement, and does not require a big bang approach, as some other learning management systems do.

Even if the subject still needs to be administered by an existing learning management system (LMS), Mosaix can run the subject in parallel, integrating with the existing LMS, with little or no overhead.

Teachers and institutions can use Mosaix as an alternative delivery method for subjects, and still run their current assessment systems. Running both systems together gives the teachers and institutions confidence in the way Mosaix conducts the assessments, as they can be measured against each other.

Or they can use the assessment engine built into Mosaix to conduct the assessments, leaving more time for the teachers to spend with students.