TY - JOUR
T1 - A learning analytics journey
T2 - Bridging the gap between technology services and the academic need
AU - Munguia, Pablo
AU - Brennan, Amelia
AU - Taylor, Sarah
AU - Lee, David
PY - 2020/7
Y1 - 2020/7
N2 - Developing data visualisation tools to support academics in the classroom is a challenging process due to the key requirements of usefulness and scalability, and the constraints of a university ecosystem. Here we describe the evolution of an enterprise-level, teacher-facing dashboard, designed to display data about students' enrolments and use of the Learning Management System in a meaningful way, and summarise the challenges and lessons we encountered along the way. This large university has a maturing learning analytics unit, a new, data-friendly LMS system, and data-savvy and data-hungry executive leadership. Yet the experienced pathway and evolutionary steps evidence the points that need be resolved to successfully deliver and transition to learning analytics solutions that have previously been conceptually proposed or tested at small scales in other studies. The key findings through the process highlight the level of uplift (in tech, capacity and capability) that universities need to meet contemporary demands and future possibilities.
AB - Developing data visualisation tools to support academics in the classroom is a challenging process due to the key requirements of usefulness and scalability, and the constraints of a university ecosystem. Here we describe the evolution of an enterprise-level, teacher-facing dashboard, designed to display data about students' enrolments and use of the Learning Management System in a meaningful way, and summarise the challenges and lessons we encountered along the way. This large university has a maturing learning analytics unit, a new, data-friendly LMS system, and data-savvy and data-hungry executive leadership. Yet the experienced pathway and evolutionary steps evidence the points that need be resolved to successfully deliver and transition to learning analytics solutions that have previously been conceptually proposed or tested at small scales in other studies. The key findings through the process highlight the level of uplift (in tech, capacity and capability) that universities need to meet contemporary demands and future possibilities.
KW - Data pipelines
KW - Data-driven insights
KW - Educational platforms
KW - Learning analytics
KW - University strategy
UR - http://www.scopus.com/inward/record.url?scp=85084942420&partnerID=8YFLogxK
U2 - 10.1016/j.iheduc.2020.100744
DO - 10.1016/j.iheduc.2020.100744
M3 - Article
AN - SCOPUS:85084942420
VL - 46
JO - Internet and Higher Education
JF - Internet and Higher Education
SN - 1096-7516
M1 - 100744
ER -