How it begins: A Collaboration between Mailman School of Public Health and SOLER
[Video]
Student Engagement
Student engagement is key to learning, which comes in many forms such as raising a hand and asking a question in class, skimming through an assigned reading, or reviewing old lecture slides (Johar et al., 2023). By actively interacting with instructors or instructor-provided materials, students improve their intellectual skills, practical competence, moral development, self-image, and grades (Li & Xue, 2023).
As a mediator between course content and students' learning, student engagement motivates instructors to be intentional about how they design their course content, course learning management system (CourseWorks powered by Canvas, Blackboard, Google Classroom, etc.), and learning activities to monitor and maximize engagement (Reeve, 2012) (Johar et al., 2023).
But where do instructors start in increasing student engagement in their classes?
How can instructors know what is working and what is not?
How can instructors find out which students need more of a push to engage?
Dr. Garbers' Course
If you are wondering about these questions as how to help student learning, you are not alone. Dr. Samantha Garbers, aka Sam, who is an associate professor at Columbia University, Mailman School of Public Health, had been thinking about exactly the same questions over and over again.
The course Sam teaches is a qualitative methods course for Public Health, and part of the core curriculum. It is a hard course on statistics. Even though abundant supporting materials such as readings and videos had been provided to students, students didn’t much take advantage of them. Sam and colleagues had observed that there's a significant relationship between engaging with the course materials, and the grades on specific assessments that directly mapped onto these course materials. As an avid researcher and proponent of the scholarship of teaching and learning, Sam wanted to understand why students’ engagement with course material was low, and how to improve that. Specifically, being aware of reports on nudges, which seek to help people make beneficial changes in behavior without significantly changing incentives, she asked: Can incorporating nudges in courseworks site help my students to engage more? (Szaszi et al., 2018)
Learning Analytics
With that question in mind, Sam reached out to the Science of Learning Research Initiative (SOLER), who is dedicated to support teaching faculty to attach evidence of efficacy and improvement to their work, demonstrating effective and skillful teaching. SOLER introduced Sam to learning analytics -- the collection, analysis, interpretation and communication of data about learners and their learning that provides theoretically relevant and actionable insights to enhance learning and teaching (Svabensky et al., 2026). In fact, one of SOLER’s objectives is to utilize learning analytics to identify strategies to increase student engagement. For example, by processing learning analytics data from Canvas access data, Panopto view records, and even Vocareum activity, we observe patterns to test hypotheses with a controlled experiment. This was exactly what Sam wanted.
Collaboration Between Dr. Garbers and Dr. Russell
With a research grant from SOLER, Sam together with colleague Roxanne, who is assistant dean of digital learning at Mailman School of Public Health, officially embarked on the learning analytics project with continuous support from SOLER along the way. Since its inception in 2021, this project has walked through three phases of investigations. As is the case with any scientific discoveries, the road to insights is never a straight line. Despite careful analysis of learning analytics data, phase I findings suggested that canvas nudges failed to boost student engagement (Garbers et al.,2023). The results were calling to take an unexpected turn, as Sam did. Taking a step back in phase II, Sam and colleagues interviewed students on their learning motivations and realized that student engagement is affected by learning, efficiency, academic expectations, and external rewards, based on which they classified students into learners, doers, and performers (Russell et al.,2025). Thus, in phase III, tailored nudges were designed to tap into students’ learning motivations. Learning analytics revealed significantly higher engagements among those who received them (Garbers et al.,2025).
Read more about the published papers below.
Digital advances in the learning space have changed the contours of student engagement as well as how it is measured. Learning management systems and other learning technologies now provide information about student behaviors with course materials in the form of learning analytics. In the context of a large, integrated and interdisciplinary Core curriculum course in a graduate school of public health, this study undertook a pilot randomized controlled trial testing the effect of providing a “behavioral nudge” in the form of digital images containing specific information derived from learning analytics about past student behaviors and performance. Read the full paper here.
Learning analytics are often used as proxies for student engagement. More qualitative data on how post-secondary students engage with course elements are needed to guide the design, development and deployment of learning analytics information, particularly in the use of nudge techniques. In the context of a graduate-level quantitative course within a public health core curriculum, the following research questions were explored: What do students cite as their motivations when making decisions about whether, when or how to engage with course content and learning supports? and What are student reactions to visual prompts designed to activate these motivations? Read the full paper here.
Student engagement predicts favorable educational outcomes. Nudges are increasingly applied to higher education contexts to promote engagement. A randomized study in a large quantitative analysis public health course deployed nudges catered to students’ intrinsic motivations. Participants (n = 127) self-selected into motivation groups (Learners [n = 46], Doers [n = 48], or Performers [n = 33]); half were randomized to receive four nudges tailored to their motivation group. Read the full paper here.
Your Turn: Accessing Course Analytics Report and Running an Interactive Demonstration
Did you know that your students’ interactions with Canvas materials are right at your fingertips?
Follow the GIF tutorial below to learn more about this Canvas feature. You will find out which Canvas materials your students engage with and and receive a report on students’ activities, grades, etc.
All instructions are provided and no prior coding experience is required.
Instructions for Accessing Canvas (Course) Learning Analytics Report
Information on average grades and grades of specific assignments
Number of times students have viewed or interacted with Canvas materials (Figure 3)
You can scroll down on the same page to see which Canvas materials students interacted with the most or least (Figure 4)
Information and activity of individual students
Run reports (Figure 6)
View the downloaded csv (Figure 7)
If you would like to try out the demonstration without uploading your own course activity file, download this sample file and then upload it when prompted by the interface.
Visit this interactive demonstration interface, then upload your course learning analytics report [see "Instructions for Accessing Canvas (Course) Learning Analytics Report"] and run the code.
A GIF visualization of the interactive demonstration is provided above.