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Dr Becky Allen


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Lecturer in Computer Science (Data Science)

After graduating from Teesside University with a BSc in Music Technology, I completed an MSc in Computer Science from Newcastle University. I have completed a PhD in Artificial Intelligence with a focus on pedagogical approaches to teaching this domain.

My subsequent research focuses on applications of AI within music, as well as novel approaches to data analysis through sonification.

I teach across all courses in a variety of modules including Software Engineering, Artificial Intelligence and Advanced Programming.



Teaching and supervision

Module Leader: 
  • Software Engineering 
  • Secure Database Systems

Supervision:
  • I currently supervise undergraduate and postgraduate projects
  • I am also a PhD supervisor for a number of students

Research interests for potential research students

  • Artificial Intelligence (encompassing Machine Learning and Deep Learning)
  • Data Science

Research

  • Artificial Intelligence 
  • Data Sonification 
  • Sound and Music Computing
  • Innovative Computer Science Pedagogies 

Publications

Number of items: 3.

Article

Allen, Becky, McGough, Stephen and Devlin, Marie (2021) Toward a Framework for Teaching Artificial Intelligence to a Higher Education Audience. Transactions on Computing Education, 22 (2). ISSN 1946-6226

Conference or Workshop Item

Allen, Becky (2023) A Human-Centered Artificial Intelligence Approach to Adaptable Digital Musical Instrument Development. In: CHIME Annual One-day Music and HCI Workshop, 04 Dec 2023, The Open University, Milton Keynes, UK.

Allen, Becky, Heels, Laura and Devlin, Marie (2021) Measuring the Difference Between Student and Staff Perception of Self-Efficacy and Confidence Using Online Tools. In: United Kingdom and Ireland Computing Education Research (UKICER), 2-3 September 2021, Glasgow, UK.

This list was generated on Sat Apr 20 00:43:39 2024 BST.
  • Machine Learning/Deep Learning 
  • Data Science 

Last updated 28 February 2024