Abstract:

Due to the large increase in the use of learning metric systems in the school environment, there has been significant growth in the interest for data-driven decisions to guide and enhance instruction. In order to provide timely and effective data to support teachers and administration, the use of learning analytics can be a valuable tool for instruction and students' support. Thus, this Participatory Action Research (PAR) aims at using the Canvas LMS learning analytics as a way to identify students in need of support so that teachers and student support teams can design appropriate interventions. The data collected on Canvas LMS will be tracked and interpreted with the purpose of identifying students that might be underperforming and could use additional support by the teacher or support team. Thus, the purpose of this article is to provide a thorough understanding of the assessment capabilities of the data and reports available in Canvas LMS and how these could be analyzed and interpreted to provide information for stakeholders to take action to support all students. The need to ensure that all students are included in the learning process and are given multiple opportunities to learn has been long discussed by educators around the world, however, finding ways to intervene in a timely manner can be a challenge in a typical classroom. The context of the study was an international school in São Paulo, Brazil. The period for the research will be 30 days and the performance of 85 students from 10th grade will be monitored by the learning analytics of Canvas LMS. The students identified will then be observed and interviewed to determine the need for support and level of intervention.

Keywords:

Canvas LMS, Student Support, Learning Analytics.