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Miss Tiffany Young's Outputs (3)

Assessing faculty perceptions of a pass/fail grading model in CS1. (2024)
Presentation / Conference Contribution
ZARB, M., BROWN, J.N.A., MCDERMOTT, R., MCGOWAN, J. and YOUNG, T. 2024. Assessing faculty perceptions of a pass/fail grading model in CS1. In Proceedings of the 2024 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2024), 13-16 October 2024, Washington, DC, USA. Piscataway: IEEE [online], article number 10893076. Available from: https://doi.org/10.1109/fie61694.2024.10893076

This Innovative Practice Full Paper outlines the findings of a survey conducted at the Robert Gordon University (Scotland, UK), focusing on feedback from faculty members and reflections subsequent to the introduction of a Pass/Fail grading system in... Read More about Assessing faculty perceptions of a pass/fail grading model in CS1..

Ethical implications of Gen-AI and LLMs in computing education. (2024)
Presentation / Conference Contribution
ZARB, M., BROWN, J.N.A., GOODFELLOW, M., LIASKOS, K. and YOUNG, T. 2024. Ethical implications of Gen-AI and LLMs in computing education. In Proceedings of the 1st Association for Computing Machinery virtual global computing education conference (SIGCSE Virtual 2024), 5-8 December 2024, [virtual event]. New York: ACM [online], volume 2, pages 293-294. Available from: https://doi.org/10.1145/3649409.3691074

The panel convenes five educators to discuss the ethical implications of utilising Generative AI (Gen-AI) and Large Language Models (LLMs) in computing education. Their expertise spans various domains, including organising national workshops on the i... Read More about Ethical implications of Gen-AI and LLMs in computing education..

Curriculum analysis for data systems education. (2024)
Presentation / Conference Contribution
MIEDEMA, D., TAIPALUS, T., AJANOVSKI, V.V., ALAWINI, A., GOODFELLOW, M., LIUT, M., PELTSVERGER, S. and YOUNG, T. 2024. Curriculum analysis for data systems education. In Monga, M., Lonati, V. Barendsen, E. et al. (eds.) ITiCSE 2024: innovation and technology in computer science education: proceedings of the 29th Innovation and technology in computer science education 2024, 8-10 July 2024, Milan, Italy. New York: ACM [online], volume 2, pages 761-762. Available from: https://doi.org/10.1145/3649405.3659529

The field of data systems has seen quick advances due to the popularization of data science, machine learning, and real-time analytics. In industry contexts, system features such as recommendation systems, chatbots and reverse image search require ef... Read More about Curriculum analysis for data systems education..