Mark Grattan

Profile

I am a postgraduate researcher in the School of Education at the University of Leeds, investigating how AI is reshaping higher music education, and how universities and conservatoires can respond ethically through a social justice lens. I bring an interdisciplinary perspective through long-standing professional practice as a music educator, alongside over three decades as an internationally recognised electronic music artist.

My academic pathway has been non-traditional. After returning to higher education as a mature student, I completed a BA (Hons) in Teaching and Education (First-Class Honours) and an MA Education (Distinction). My MA dissertation examined the democratising potential of AI for music education in England, exploring social justice concerns in relation to access, participation, and decision-making.

Alongside doctoral study, I have experience designing and delivering music education in community and professional contexts. I founded Safety in Music CIC, using music-based approaches to support vulnerable groups, and I have worked on research and evaluation projects that involved stakeholder engagement and mixed-method data collection. These practitioner-researcher experiences have shaped my focus in producing an empirically grounded framework that is both theoretically rigorous and usable in real educational settings.

Research interests

My research interests are at the intersection of AI ethics, social justice, and higher music education, with a particular focus on creative and studio-based pedagogy.

Current interests include:

AI in higher music education

How AI tools are currently used and perceived by students, educators, and administrators

The implications of AI for studio practice, musicianship, professional identity, and employability

Ethical governance, policy, and institutional responsibility

What ethical risks and responsibilities arise when AI becomes normalised in teaching, learning, and assessment

How policy and guidance can be made music-sensitive rather than generic

Social justice and AI

How social justice lenses can reveal who benefits, who is disadvantaged, and why

How issues such as access, bias, recognition, voice, and participation play out in creative higher education settings

Creativity, authorship, and assessment

How AI complicates concepts of originality, authenticity, and authorship in music-making

How assessment and feedback practices can remain fair, meaningful, and supportive of learning

Framework and resource design

Developing an ethical framework that can be translated into actionable outputs (principles, criteria, guidelines, and toolkits) for higher music education stakeholders

Qualifications

• MA Education (Distinction)
• BA (Hons) Teaching and Education (First Class)

Research groups and institutes

• Postgraduate research