Using Canvas New Analytics to Monitor Student Interaction with Online Course Content and Improve Teaching Practices and Curriculum Development
Start Date
November 2025
End Date
November 2025
Keywords
Learning Analytics, Student Success, Canvas LMS
Abstract
Student engagement with course content is essential to the educational experience (Garrison, Anderson, & Archer, 2000). According to Scheffel et al. (2014), instructors should be aware of how their students interact with course content, learning materials and resources provided in their online classes.
The New Analytics tool available in the Canvas Learning Management System provides information on student interaction with online course content. Instructors who use New Analytics have access to student interaction with course resources and participation metrics across all devices, including Canvas mobile apps (Canvas, 2022). Learner analytics not only provide the instructor an opportunity to monitor student interaction with course content, but to also identify at-risk students and enhance student engagement (Naujokaitiene’ et al., 2020).
The current literature is mixed on the impact of learner analytics on student success. Some researchers report strong correlations between learner interaction with course content and academic performance (Gomez-Aguilar et al., 2015; Ellis, Han & Pardo, 2017; Zacharis, 2015). Other researchers report a lack of empirical evidence for predicting student performance using learning analytics (Agudo-Peregrina et al., 2014; Iglesias-Pradas et al., 2015; Strang, 2015; Xing et al. , 2015). However, those who reported weak correlations admit the use of learner analytics warrant further investigation, including the need to assess student familiarity with online course technology, class size, and other “interesting patterns hidden in educational data sets” (Chatti et al. 2012, p.10).
A study was conducted in hopes to extend the current research by measuring the relationship between the student’s overall course grade and Canvas’ New Analytics data of student interaction with online course materials. Anonymized New Analytics data from Canvas courses taught by a single professor in the Department of Health Science at Nova Southeastern University from 2017 – 2022 will be collected and analyzed (n = 400). Descriptive statistics, correlation, regression techniques, ANOVA and cluster analysis techniques will be used to explore the relationship of performance and engagement within and between bachelors, masters and doctoral level courses, class size, semester and year offered (to determine any impact the pandemic years may have had on interaction with course materials).
It was hoped that the report of this study would add to online instructors’ understanding of how learning analytics may be used to a). monitor student interaction with course content and b). improve teaching practices and curriculum development.
Learning Outcomes
1. Attendees will be introduced to the concept of learner analytics and correlations to student performance.
2. Attendees will be made aware of the "Course Analytics" tool in CANVAS and the types of student data that are recorded.
3. Attendees will hear the preliminary report of a study conducted by the presenter on the possible applications of learner analytics in predicting student outcomes.
Track
Teaching & Learning Technologies
Session Type
25-Minute Session
Using Canvas New Analytics to Monitor Student Interaction with Online Course Content and Improve Teaching Practices and Curriculum Development
Student engagement with course content is essential to the educational experience (Garrison, Anderson, & Archer, 2000). According to Scheffel et al. (2014), instructors should be aware of how their students interact with course content, learning materials and resources provided in their online classes.
The New Analytics tool available in the Canvas Learning Management System provides information on student interaction with online course content. Instructors who use New Analytics have access to student interaction with course resources and participation metrics across all devices, including Canvas mobile apps (Canvas, 2022). Learner analytics not only provide the instructor an opportunity to monitor student interaction with course content, but to also identify at-risk students and enhance student engagement (Naujokaitiene’ et al., 2020).
The current literature is mixed on the impact of learner analytics on student success. Some researchers report strong correlations between learner interaction with course content and academic performance (Gomez-Aguilar et al., 2015; Ellis, Han & Pardo, 2017; Zacharis, 2015). Other researchers report a lack of empirical evidence for predicting student performance using learning analytics (Agudo-Peregrina et al., 2014; Iglesias-Pradas et al., 2015; Strang, 2015; Xing et al. , 2015). However, those who reported weak correlations admit the use of learner analytics warrant further investigation, including the need to assess student familiarity with online course technology, class size, and other “interesting patterns hidden in educational data sets” (Chatti et al. 2012, p.10).
A study was conducted in hopes to extend the current research by measuring the relationship between the student’s overall course grade and Canvas’ New Analytics data of student interaction with online course materials. Anonymized New Analytics data from Canvas courses taught by a single professor in the Department of Health Science at Nova Southeastern University from 2017 – 2022 will be collected and analyzed (n = 400). Descriptive statistics, correlation, regression techniques, ANOVA and cluster analysis techniques will be used to explore the relationship of performance and engagement within and between bachelors, masters and doctoral level courses, class size, semester and year offered (to determine any impact the pandemic years may have had on interaction with course materials).
It was hoped that the report of this study would add to online instructors’ understanding of how learning analytics may be used to a). monitor student interaction with course content and b). improve teaching practices and curriculum development.