Picture this. To catch up with their coursework, a student only selectively completes required tasks – fully participating in some, while choosing to leave others untouched. When asked about this directly, the student explains that they missed all announcements in the Learning Management System (LMS) and haven’t completed the LMS orientation module. They only engaged with the tasks when prompted by push notifications from a mobile LMS (mLMS) application on their smartphone.

This is a real-world interaction that one of us had with a student last year. What we found interesting is not the student’s use of mLMS but their heavy reliance on push notifications to know what to do and when. This anecdote showed us what limited understanding we, as educators, have about students’ mLMS use. Without this knowledge we are at risk of unknowingly handing over the design of students’ learning journeys to these technologies.

Pushing out learning

Pushed out learning: LMS mobile applications, push notifications and learning behaviours, a research project awarded a HERDSA Grant in 2025, aims to redress this by shedding the light on the mLMS use among Australian university students. A lot of what we know about these applications comes from the LMS providers themselves. Canvas, Moodle and Blackboard hype their mobile applications as offering full LMS functionality on the go, equitable access, support for asynchronous learning, personalisation and immediacy delivered via timely notifications.

Canvas even suggests that their app enhances student success.  While some research endorses this techno-solutionist promise of mLMSs by, for example, demonstrating that push notifications can significantly reduce missed assignments. The earlier anecdote shows that heavy reliance on mLMS nudges bypasses the intended learning journey and can have detrimental effects on students’ progress. To that end, our project breaks with techno-solutionism to paint a rich picture of students’ mLMS uses across four different Australian universities.

As we conclude the first phase of the project, here we share some initial reflections from the student focus groups in two of the four participating institutions. In both institutions, we have anecdotally observed a far greater use of mLMSs and other mobile learning applications among postgraduate students than undergraduate cohorts. At both sites, timely recruitment of undergraduate participants was challenging.

Otherwise, the two institutions contrast sharply in how mLMS applications are embedded in their digital infrastructures, and how students choose to use or not use these apps. The project’s initial focus was on Canvas, Blackboard and Moodle mobile apps. However, it soon became clear that while some universities encouraged and created clear pathways for students to download and use mLMS apps, other institutions precluded (perhaps unintentionally) or not actively encouraged the use of mLMSs.

For example, at one university, students are directed to a university-branded mobile application, which is simply a shell for different URLs, including the Learning Management System. However, clicking on the link opens the LMS in a mobile browser. Therefore, most students chose to use LMS exclusively on their laptops, as they simply lacked awareness of the mLMS option.

The only two students who downloaded the mLMS app on their phones did so because it was part of their assessment task required specifically by their lecturer. This example demonstrates the power that we as educators have in shaping students’ use of learning technology. The institutional setup, in this case, meant that the university-branded app misdirected students from the use of the mLMS. This is an interesting observation coming from a regional university where a significant proportion of student population study off campus. In this context, mLMS could potentially have an important role in supporting online delivery and connecting students to the institution.  

Staying in the loop with notifications

The other participating institution, we reflect on in this blog, is a research-intensive, metropolitan university with a predominantly campus-based mode of learning. Here, the focus groups suggested a wide use of mLMS as a way for students to ‘stay in the loop’ with their studies at all times.

Students shared how receiving notifications about the release of results, or new posts in the assessment discussion forum would prompt them to stop whatever they were doing and check the app. At times, these notifications would interrupt social activities, such as hanging out with friends, and be a source of anxiety or guilt for not studying while others in their cohort are, as evidenced by them posting on the assessment discussion forum. Most students had complex, individual ways of navigating the university’s digital infrastructure. The mLMSs app were a way of catching up with some information on-the-go or at times engaging with some learning activities, like watching lectures. Like their counterparts at the regional university, most students, by their own admission, did little learning on the mLMS. Instances of perusing study materials on the mobile app were surface only and often an opportunity to check something quickly or get a broad overview of the material.

The comparison of focus group insights from these two institutions illustrates one of the key challenges we have encountered so far. The institutional approaches to mLMSs differ significantly. These differences required us to adapt to the digital infrastructure of each participating university and ask students about mobile learning applications other than Canvas, Moodle and Blackboard. The focus group data show that these institutional differences also shape the diverse ways students organise their learning and navigate the university’s digital ecosystem. As we analyse the data from the other two participating institutions, we are prepared to be surprised by further contrasts in the digital infrastructures. We are looking forward to examining how these institutionally mediated interactions with mobile learning technologies may affect learning outcomes and students’ socio-emotional experiences.

Watch this space – we will report back in six months with the final findings from this project, including survey data which will capture the prevalence of specific interactions and learning behaviours in and around mobile learning technologies.  

References for blog post

Banner image: Generated by Chat GPT