AgendaFilter by Category
- Exploring the Office for Student’s (OfS) data led approach in monitoring HE providers
- Outlining the new 2018 OfS data strategy and the data requirements that will be placed on providers as the OfS performs its regulatory functions
- Understand how data and lead indicators will be used to monitor the performance of providers and deliver risk-based regulation of the sector
- Assessing the role of the OfS in analysing and developing Teaching Excellence Framework data to monitor universities in their support of student satisfaction, continuation and employment outcomes
- Evaluating the future of HE regulation and the role of data in assessing performance
- Assessing the role of HESA in supporting the HE sector to advance capabilities and data maturity to support improved planning and decision making
- Understanding the expectations on universities in collecting and reporting on key indicators and assessing how HESA is supporting a new streamlined collection process through the Data Futures programme
- Evaluating the next steps in marketing insight, bench marking and sector analysis through Heidi Plus to support enhanced data visualisation and business intelligence for universities
- Exploring the future of HE data infrastructure and assessing opportunities for improving the quality, efficiency and accessibility of data provision
- GDPR six months on – what is there still to do?
- Areas to focus on: data analytics, HE fundraising and research data governance
- Data protection impact assessments and accountability
- Data Futures – Single Source of Truth (SSOT) versus Multiple Versions of the Truth (MVOT).
- Too many Full-Time Equivalents (FTEs) spent resolving data quality
- Student and staff revenues and costs in FTE are a significant unit of measure in H.E.
- Data Futureas will stop the chase and force a data quality behaviour and mindset change
- Outlining the principles of Jisc’s new sector-wide learning analytics model designed to improve the learning experience for students
- Assessing how predictive modelling can be utilised to deliver targeted interventions for students at risk to improve student outcomes and support retention
- Sharing lessons in utilising learning analytics findings to redesign and develop teaching and assessment practices across a course
- Exploring the impact of GDPR on learning analytics and assessing when consent is required when using a predictive data model
- Exploring the latest trends and future predictions in the development of university admissions
- Assessing the data collection conducted by UCAS within the HE admissions landscape and how it can be effectively used by providers
- Using admissions data to inform long-term strategic planning and decision making in the forecasting of future student numbers and demographics
- Analysing UCAS data at a course level within an institution to inform student marketing and course development
- Durham University’s understanding of the requirements for institutional change and the associated strategic imperatives
- How data-led insight and integration underpinned the strategy formulation process
- The processes of stakeholder engagement
- Moving from strategy formulation to practical implementation supported by data integration, planning and modelling
- Reflections on benefits realisation and lessons learnt along the way
- Trialling and developing a learning analytics project using data on student’s academic performance to support effective interventions to ensure progress
- Presenting learning analytics findings through a bespoke student data dashboard for student and staff to allow users to monitor performance
- Engaging students in the development of the project with 90% of first year students opting-in and students contributing to user focus groups to assess how data insights can provide further support
- Conducting data mining research from multiple data sources in line with academic performance to assess how student engagement can be improved and how staff can deliver targeted support where required
- Evaluating the lessons learnt from the project and how the analytics projects can be replicated to improve academic interventions and student progress across HE
- Adopting a data strategy to address challenges of student withdrawal, retention and long-term course engagement
- Developing a range of datasets including quantitative surveys of first year expectations and the formation of qualitative focus groups
- Utilising data insights to develop processes to monitor and track student support and academic engagement
- Assessing how the data project led to the development of a major retention programme including the NTU Student dashboard and a reform of the delivery of education provision and student support
- Outlining the challenges and common barriers in using data to drive change on retention outcomes
Winner of the Gold Award at the University Market Insight Awards 2017
This session will explore how the rich data available in the UK HE sector can be effectively interrogated and analysed to drive course development and support an appealing and strongly performing portfolio strategy
- How can Marketing or Planning departments contribute to course development?
- What data are available and what can they tell us?
- How can data strengthen performance in terms of institutional strategy and student recruitment?
Following the implementation of GDPR, join data leaders sharing practical insights on the next steps in ensuring data management and protection in universities
- Discussing insights into how universities can demonstrate GDPR compliance and develop an effective data accountability structure
*programme subject to change