Learning Engagement Analytics combine several streams of data generated by students throughout their learner journey - VLE activity completion, attendance records, library use and other markers - tell a story. The data requires human interpretation and informs educational interventions. At QMUL, the LEA (Learner Engagement Analytics) Statement Principles point towards a goal of surfacing the learner journey and informing a supportive dialogue with students, to help them achieve their full academic potential.
DES (Digital Education Studio) talked to colleagues from across QMUL to explore LEA from multiple perspectives: Dr Usman Naeem – Senior Lecturer (Associate Professor) within the School of Electronic Engineering; Sharon Pay – Teach, Learn & Analytics Development Manager, IT Services; and Simon Durant – Learning Technologist (Video Production), IT Services.
The article explores some challenges of using LEA, affordances, and potential uses. The focus is not on one platform, but rather on the potential of using LEA to create reflective academic practice, as well as an atmosphere of supportive interventions and feedback as dialogue with students both informed by evidence.
I am an LEA Fellow at the Queen Mary Academy and also in a variety of student-facing roles related to teaching and learning. Through both research and practical experience, I've learned that LEA empowers educators to implement data-driven interventions. These interventions not only assist students in reaching their maximum potential but also enable educators to refine their curricula and teaching strategies based on data insights.
Take, for example, my involvement in a Level 6 capstone project module, where students undertook an unstructured project following six weeks of asynchronous and synchronous learning. During this period, they engaged in guided independent study to prepare for their project. By analysing completion data from QM+, I was able to identify students who had not engaged in essential activities. My approach was to offer support rather than to penalise, leading me to reach out personally via email. The response was overwhelmingly positive, with many students expressing gratitude for the support. This experience forms the basis of my upcoming research, which demonstrates the positive impact of such dialogues on student performance.
Every course/module generates data, and within that data lies a story waiting to be told! It makes students' work, presence, and engagement explicit, and we are responsible for telling that story and acting on it. It helps us, for example, go beyond mere attendance data to define markers for deeper engagement. This, in turn, opens doors to enhanced student support and the development of more effective curricula and teaching methodologies, driven by insights gained from our educational practices.
QEngage aims to mitigate attrition risks by identifying key performance indicators early and fostering student engagement, informing human interventions at School or module level. The evolution of QEngage from an attendance monitoring system to a comprehensive platform for pastoral support exemplifies QMUL's commitment to leveraging data for student success. Initially centered on retention, the project shifted focus towards holistic student support, steering away from punitive measures like penalising attendance lapses. There are challenges stemming from a rich diversity of practices across Schools, for example assignment submissions varying from paper-based to many digital formats, posing hurdles for comprehensive reporting. Additionally, the fluid nature of teaching and learning resists rigid system mapping, so a dialogue with students, academic and support staff is needed to refine requirements, such as the ongoing efforts to refine engagement metrics and extend them beyond attendance to encompass assignment submission and interaction with course materials. Understanding the intricate link between attendance and learning remains pivotal, underscoring the project's ongoing commitment to fostering a supportive and inclusive academic environment.
Schools can also define thresholds for interventions, triggering customised messages via QEngage. Future enhancements entail intervention tracking and focus on QM+ activity completion records to streamline the key markers for monitoring engagement, tailored to each school, which are slated for deployment soon.
Continuous improvement efforts, including enhanced data integration and personalised communication strategies, show an effort to create a supportive and inclusive academic environment. By facilitating dialogues and providing insights into student activities, QEngage aims to empower educators to tailor interventions effectively and foster meaningful interactions with students.
A student who starts their degree with us has been engaging and even communicating with video for years, and we can learn from their experience.
At QMUL, platforms like QReview and Kaltura offer valuable insights into student interactions with educational video content. QReview tools like confusion flags, where students raise difficulties, heat maps, which allow you to check what parts of the video students engage with the most, Q&As, where students raise questions, and other affordances might help teaching staff understand how students engage with the video material, where they might struggle, and define teaching interventions.
We can also look at video as a potential tool for dialogue in terms of social media – the ability to comment, subscribe, a mobile-friendly format are key parts of students’ experience; videos don’t necessarily need to require substantial resources for production.
I would encourage experimentation in creating videos and using analytics to refine this creative process. From interactive lecture capture to podcasting, the possibilities are endless, and there might be ways of connecting with students that can be refined. Ask students to create their own video assignments and give them options as to the format: a presentation, a reflective face to camera, etc. Which format do they choose? Which do they prefer? Look out for social media like affordances like subscriptions to Kaltura channels (coming soon), or comments. Use analytics to gauge engagement and preference for the formats you create. This is also a dialogue that informs a reflection between the videos you create, and how students learn from them.