Mr Richard Paterson
With three decades of experience in higher education and English language teaching, Richard Paterson is an established educator, researcher, and academic developer. His career spans university teaching in the UK and extensive international work across Europe, Latin America, and Central Asia. He is a published academic in the areas of pedagogy for employability, professional identity, and language education, contributing to sector-wide conversations on teaching practice and the evolving academic role.
Richard holds an EdD from the Institute of Education, University College London, where he also completed a Postgraduate Diploma in Social Science Research Methods and an MA in Linguistics. His earlier professional training includes advanced teaching qualifications gained in Cairo and Buenos Aires, reflecting a longstanding commitment to global education.
Richard’s research centres on the intersections of language education, higher education pedagogy, and emerging technologies in learning. He has a longstanding interest in second language acquisition, particularly how learners develop linguistic competence through meaningful interaction, feedback, and exposure to authentic input. His work also explores language learning and teaching practices, with a focus on curriculum design, teacher development, and the role of context in shaping classroom methodologies.
In higher education, Richard’s research examines pedagogical approaches that support student engagement, academic identity formation, and employability. He is particularly interested in how educators design learning environments that balance rigour, inclusivity, and critical thinking across disciplines.
A growing strand of his work investigates the use of artificial intelligence as a learning tool, including students’ and teachers’ perceptions of AI, its impact on assessment and academic integrity, and opportunities for integrating AI to enhance reflective practice and knowledge construction. He is especially focused on developing ethical, discipline-sensitive frameworks that support effective and responsible AI use in teaching and learning
