MSc Sustainable Food Systems and Food Security

Year 1

(Award available for year: Master of Science)

Learning outcomes

1. Demonstrate a sophisticated understanding of concepts, information and techniques at the forefront of the different disciplines investigating food systems sustainability and food security
2. Apply systems thinking approach to critically and creatively evaluate the complexity, current and future challenges, research and advanced scholarship in the food systems
3. Apply new analytical frameworks to understand and evaluate food as a socio-technical system
4. Diagnose and solve the real-world challenges food sustainability and food security presents, incorporating diverse resources such as existing knowledge, data collection, interpersonal skills, reflection and reasoning ability
5. Demonstrate competence in crossing disciplinary boundaries in the pursuit of sustainability solutions and food security in the food system
6. Demonstrate a comprehensive understanding of techniques (e.g. stakeholder engagement, knowledge co-production) applicable to food systems sustainability and food security practice, research or advanced scholarship
7. Take a proactive and self-reflective role in working, and develop professional relationships with stakeholders across the food systems to achieve sustainability and food security outcomes
8. Proactively formulate ideas and research questions, and develop, implement and execute plans by which to evaluate these

Skills Learning Outcomes
1. Skills to determine, analyse and solve complex problems using a range of approaches, methods, and tools related to food systems and sustainability (Leeds Skills Matrix: Work ready skills- problem solving and analytical skills, critical thinking, Sustainability skills – systems thinking)
2. Self-direction and effective decision making in complex and unpredictable situations
Independent problem-based learning and the ability to work in a way which ensures continuing professional development (Leeds Skills Matrix: Enterprise skills – managing uncertainty, ambiguity and risk; Work ready skills - decision making)
3. Advanced ability to work across the different scales relevant to food systems, from the micro to the global level and engage with multiple stakeholders (Leeds Skills Matrix: Enterprise skills - working and communicating with others, self awareness, adaptability and resilience)
4. Ability to constructively challenge existing practise and institutional form, and develop interdisciplinary professional norms (Leeds Skills Matrix: Work ready skills- negotiation & influencing; Sustainability skills – strategic practice, collaboration)
5. Advanced ability in leadership and change management to become an effective change agent (Leeds Skills Matrix: Work ready skills- leadership, interpersonal skills)
6. Advanced written, oral and digital presentation skills (Leeds Skills Matrix: Enterprise skills- applying commercial, ethical, sustainable, digital and interdisciplinary literacies; Academic skills – presentation skills)
7. Skills necessary to undertake a higher research degree and for employment in a higher capacity in the food and related industries or area of relevant professional practice (Leeds Skills Matrix: Academic skills - critical thinking, academic writing, academic language, integrity, referencing, ethics, reflection)

Assessment

1. Demonstrating the ability to critically and constructively apply a breadth of knowledge in key debates on sustainability, food studies, and socio technical systems research and practice
2. Drawing on a range of interdisciplinary and transdisciplinary perspectives to evaluate how sustainability and food security solutions can be adopted into existing socio-technical food systems
3. Evidencing an ability to conduct independent in-depth interdisciplinary and transdisciplinary enquiry
4. Critically evaluating complex and conflicting data and narratives to arrive at reasoned change recommendations
5. Making reasoned and constructive judgements whilst understanding the limitations on judgements made in the absence of complete data