Trojan horse analytics - hooking educators across institutions on personalising learning support and feedback using practical LA platforms
Presented by Dr Danny T. Liu and Dr Lorenzo Vigentini
Monday, 7 May 2018 from 3pm - 5pm.
Changes in higher education, including massification and diversification of cohorts and a push toward efficiency and digitalisation of the student experience, are diminishing educators’ ability to provide meaningful feedback and personal attention to students. A recent report about the laggard adoption of Learning Analytics by both institutions and educators highlighted that educators "still have to make sure that it [communication and feedback] is personalised and meaningful for students", and that educators need LA tools with "some ability to modify it to their own requirements because each course and each cohort of students may differ".
In this session, we discuss two projects: the Student Relationship Engagement System (SRES) and the On-Task project, funded by the OLT focusing on the personalisation of feedback at scale. We will also provide an opportunity to demonstrate the tools in practice and discuss possible use scenarios.
In stark contrast to other LA approaches and tools, these projects give precedence to teacher intelligence and small, but meaningful data over predictive algorithms and big data. It enables educators to choose data that are important for their unique learning and teaching context (e.g. interim marks, attendance, tutor feedback, in-class participation grades, etc.), and helps them to collect, collate, analyse, and make direct use of these data. Critically, educators can use these systems to efficiently personalise learning support and feedback to students at scale by building simple rules to customise information that different students will receive via email, SMS, or a web page embedded into an LMS.
Dr Danny T. Liu
Danny is a molecular biologist by training, programmer by night, researcher and academic developer by day, and educator at heart. A multiple national teaching award winner, he works at the confluence of learning analytics, student engagement, educational technology, and professional development and leadership to enhance the student experience.
Check out Danny's LinkedIn profile here.
Dr Lorenzo Vigentini
Lorenzo is the Academic Lead in Educational Intelligence and Analytics in the PVCE, steering several initiatives at the intersection of educational analytics, institutional evaluation, quality enhancement, student engagement and educational technology tools development. His work provides evidence (both data and tools) to inform strategy, QA and QE at various levels, helps to empower teachers and managers to make the right choices to improve teaching practice and supporting students experience and their future success.
For more information about the UNSW Learning Analytics & Data Science in Education Research Group (LA-EDS), click here.
Red Centre Theatre (H13)