Staff profile

After studying maths and then Computer Science, Steven joined Durham University in 1997 as a lecturer in Computer Science. From 2004-2013 he was a part-time teaching fellow, spending the rest of his time on web consultancy, mainly on research projects across the university. From 2013 he was a full-time teaching fellow in the department of Computer Science and has been an Professor (teaching) since 2020.

Other skills and qualifications

Steven likes playing musical instruments and singing, and holds many music qualifications including Grade 1 Violin (with merit).  He is qualified in Chainsaw Maintenance and Cross-cutting as well as Felling and Processing Trees up to 380mm. In sailing he holds the RYA Day Skipper Practical qualification and acts as personal sailing advisor to Guy Gordon, the Highland Vet, having previously held the rank of patrol leader of the Penguins in the 19th Tynemouth 9th Tyne Sea Scouts.

• Computer Science education
• Citizen science
• Knowledge representation and student learning
• Natural Language Processing
• Real-time systems

• 2024: PFHEA: Principal Fellow of the HEA
• 2019: Best Paper Award Koli Calling 2019: For "Addressing Bias to Improve Reliability in Peer Review of Programming Coursework"
• 2019: QAA Institutional Reviewer: Steven was an institutional reviewer for the Quality Assurance Agency for Higher Education (QAA) from 2019 to 2022.
• 2018: Chair, UK ACM Special Interest Group in Computer Science Education (SIGCSE): The UK and ACM SIGCSE aims to provide a national forum for the examination and exchange of research and practice related to the learning and teaching of computing. 
• 2018: External Examining: Prof Bradley was external examiner at Oxford Brookes from 2018 to 2022, and external examiner at the university of Kent from 2022. He has also acted as external for several PhD examinations.
• 2017: Excellence in Learning & Teaching Award: Awarded by Durham University in June 2017

Chapter in book

• Becker, B. A., Bradley, S., Maguire, J., Black, M., Crick, T., Saqr, M., Sentance, S., & Quille, K. (2023). Computing Education Research in the UK & Ireland. In M. Apiola, S. López-Pernas, & M. Saqr (Eds.), Past, Present and Future of Computing Education Research (421-479). Springer Verlag. https://doi.org/10.1007/978-3-031-25336-2_19
• Gajbhiye, A., Al Moubayed, N., & Bradley, S. (2021). ExBERT: An External Knowledge Enhanced BERT for Natural Language Inference. In I. Farkaš, P. Masulli, S. Otte, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2021 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14–17, 2021, Proceedings, Part V (460-472). Springer Verlag. https://doi.org/10.1007/978-3-030-86383-8_37
• Gajbhiye, A., Winterbottom, T., Al Moubayed, N., & Bradley, S. (2020). Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models. In I. Farkaš, P. Masulli, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2020 (633-646). Springer Verlag. https://doi.org/10.1007/978-3-030-61609-0_50

Conference Paper

• Bradley, S., & Ramezani, A. (2024, January). PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub. Presented at CEP '24: Computing Education Practice, Durham, United Kingdom
• Bradley, S., Parker, M. C., Altin, R., Barker, L., Hooshangi, S., Kunkeler, T., Lennon, R. G., McNeill, F., Minguillón, J., Parkinson, J., Peltsverger, S., & Sibia, N. (2023, July). Modeling Women's Elective Choices in Computing. Presented at ITiCSE 2023: Innovation and Technology in Computer Science Education, Turku Finland
• Bradley, S., & Akrida, E. (2022, December). Narrowing and Stretching: Addressing the Challenge of Multi-track Programming. Presented at Computing Education Practice 2022, Durham, England
• Morrison, B. B., Quinn, B. A., Bradley, S., Buffardi, K., Harrington, B., Hu, H. H., Kallia, M., McNeill, F., Ola, O., Parker, M., Rosato, J., & Waite, J. (2021, December). Evidence for Teaching Practices that Broaden Participation for Women in Computing. Presented at Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education
• Bradley, S. (2020, January). Creative Assessment in Programming: Diversity and Divergence. Presented at Proceedings of the 4th Conference on Computing Education Practice 2020, Durham, England
• Bradley, S. (2019, November). Addressing Bias to Improve Reliability in Peer Review of Programming Coursework. Presented at Koli Calling 2019, Finland
• (2019, December). Proceedings of the 3rd Conference on Computing Education Practice. Presented at Computing Education Practice, Durham, UK
• Gajbhiye, A., Jaf, S., Al-Moubayed, N., Bradley, S., & McGough, A. S. (2018, December). CAM: A Combined Attention Model for Natural Language Inference. Presented at IEEE International Conference on Big Data., Seattle, WA, USA
• Gajbhiye, A., Jaf, S., Al-Moubayed, N., McGough, A. S., & Bradley, S. (2018, December). An Exploration of Dropout with RNNs for Natural Language Inference. Presented at ICANN 2018: 27th International Conference on Artificial Neural Networks, Rhodes
• Bradley, S., & Church, S. (2018, June). Collaborative Creative Computing. Presented at London Computing Education Research Symposium (2018 LCERS)., London, England
• Bradley, S. (2016, November). Managing Plagiarism in Programming Assignments with Blended Assessment and Randomisation. Presented at 16th Koli Calling Conference on Computing Education Research, Koli, Finland
• Hsing, P.-Y., Bradley, S., Kent, V., Hill, R., Whittingham, M., & Stephens, P. (2015, December). Monitoring Wild Mammals in County Durham with a Citizen Science Web Platform. Presented at ICCB : 27th International Congress for Conservation Biology, Montpellier, France
• Bennett, K., Bradley, S., Glover, G., & Barnes, D. (2003, September). Software evolution in an interdisciplinary environment. Presented at Software Technology and Engineering Practice, 11th. International Conference., Amsterdam
• Fox, M., Long, D., Bradley, S., & McKinna, J. (2001, December). Using Model Checking for Pre-Planning Analysis. Presented at AAAI Symposium on Model-based Validation of Intelligence

Journal Article

• Hsing, P.-Y., Hill, R., Smith, G., Bradley, S., Green, S., Kent, V., Mason, S., Rees, J., Whittingham, M., Cokill, J., scientists, M. C., & Stephens, P. (2022). Large-scale mammal monitoring: the potential of a citizen science camera-trapping project in the United Kingdom. Ecological Solutions and Evidence, 3(4), Article e12180. https://doi.org/10.1002/2688-8319.12180
• Hsing, P.-Y., Coghill, L., Ryder, J., Austin, M., Dooley, S., Ellison, A., Fenwick, C., Garland, M., Humphrey, P., Proudlock, H., Robson, A., Steer, C., Turnbull, L., Kent, V., Bradley, S., Hill, R., Ascroft, R., & Stephens, P. (2020). Citizen scientists: school students conducting, contributing to and communicating ecological research – experiences of a school–university partnership. School science review, 101(376), 67-74
• Hsing, P.-Y., Bradley, S., Kent, V., Hill, R., Smith, G., Whittingham, M., Cokill, J., Crawley, D., Volunteers, M., & Stephens, P. (2018). Economical crowdsourcing for camera trap image classification. Remote Sensing in Ecology and Conservation, 4(4), 361-374. https://doi.org/10.1002/rse2.84
• Rees, S., Bruce, M., & Bradley, S. (2014). Utilising Data-driven Learning in Chemistry Teaching: a Shortcut to Improving Chemical Language Comprehension. New Directions in the Teaching of Physical Sciences, 10(1), 12-19. https://doi.org/10.11120/ndir.2014.00028
• Onyett, S., Linde, K., Glover, G., Floyd, S., Bradley, S., & Middleton, H. (2008). Implementation of crisis resolution/home treatment teams in England: national survey 2005–2006. Psychiatric bulletin of the Royal College of Psychiatrists, 32(10), https://doi.org/10.1192/pb.bp.107.018366
• Johnstone, D., & Bradley, S. (2005). Opportunistic scheduling in a constraint-rich world. SIGBED review, 2(2), https://doi.org/10.1145/1121788.1121795