The data landscape of a small specialist institution Stephanie Burns Royal Conservatoire of Scotland

Data landscape? Does our small specialist institution fit into the usual success metrics? Combat metrics-driven interpretation of success. Lots of data + confusion around what is valid among staff/students. - Internal/external data sources - ”Potentially misleading, we have very small cohorts” - “Not always easy to understand and put into practice” - ”I chose to come to the conservatoire based on data” Data to guide ongoing enhancement + achieve “success”. Build an evidence-informed data set - better understand learners, their expectations + aspirations. Rich source of information on the priorities for learners - guiding programme design + employability

Question - 1st year UG (Feb 2018) Where do you see yourself in 15 years? In your own words, how can the institution help you to be fully prepared for success? (Support, placements, quality and quantity of teaching, variety of choices, coursework, facilities, student welfare).

Response 67.8% response rate Survey responses-reflective of the population 95% Confidence interval 4% margin of error Methodology: Collate qualitative responses. Exploratory method, coding responses to represent their meaning. Rich data of quotes and expressions gathered to aid understanding.

Question 1 Themes Subject + pathway = Teaching Sustained employment Individual, positive, defined aspirations. E.g. Principal ballerina with Royal NZ ballet Teaching Education course + pathway of career Sustained employment Enough money to live off, consistent work Promoted roles Managerial roles - own business + Second career

Question 2 Themes Curriculum Industry connections Opportunities Tuition. Broaden knowledge and experience variety of subjects Industry connections Networking, professional advise, industry experience Opportunities Performance, large scale projects, learn from mistakes. Support Alumni, mental health, personal “Inspire me to inspire others” “Ensure quality and content of the teaching is preparing us for the future”

Enhancing the student experience -Student priorities Experiencing a variety of subjects and styles Cross-curriculum Self-development Creative exploration and independence Learn from mistakes Working with professionals + networking Industry-ready Support mechanisms

Key findings - data in a small specialist institution Do we understand our own data landscape? Is the first year view of success different from metric models? Evolution over time (3 years)? Are we prepared to fulfil the expectations? Staff a rich source of information on the priorities for their learners, and delivery to maximise engagement. Student opportunity to reflect on the breadth of responses received but also on their changing responses over time. Next steps? Do the findings support staff hypotheses? Differences? Engage students and staff with findings. Analyse over 3 years + engage Postgraduate students

Thank you Stephanie Burns s.burns@rcs.ac.uk