Introductory description

The English for Academic Purposes for Maths and Computer Science module is designed to help students develop academic listening, reading, speaking and writing skills to succeed in related undergraduate courses in the United Kingdom.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

ACADEMIC WRITING

• Select, evaluate and synthesise appropriate sources for an academic assignment
• Express and justify an academic opinion by paraphrasing, quoting and/or summarising sources
• Apply citation practices and referencing styles used in mathematics, statistics and computer science
• Plan a written academic assignment, presenting and developing ideas logically
• Write for a specific (academic) audience and purpose, applying conventions of academic writing

ACADEMIC READING

• Select and apply appropriate reading strategies for different types of academic texts
• Use note-taking strategies to check comprehension and aid long-term memory
• Form an academic opinion by reading, evaluating and synthesising two or more sources
• Develop effective self-study approaches to improve academic reading skills

ACADEMIC LISTENING

• Select and apply appropriate listening strategies for lectures and seminars
• Use note-taking strategies to check comprehension and aid long-term memory
• Explain the impact of accent and other linguistic features on listening comprehension
• Develop effective self-study approaches to improve academic listening skills

ACADEMIC SPEAKING

• Plan, structure and deliver an academic presentation based on a set theme or text
• Design effective and accessible PowerPoint slides to support an academic presentation
• Articulate the purpose and importance of seminar-style teaching in UK HE
• Prepare for and participate in a seminar discussion on a topic relevant to the discipline

Learning outcomes

By the end of the module, students should be able to:

• Analyse, interpret and evaluate spoken and written discourse for the study of mathematics, statistics and computer science
• Synthesise relevant information/data to produce discipline-specific written and spoken genres, incorporating own ideas
• Communicate effectively in written and spoken genres, employing academic conventions relevant to the disciplines

Indicative reading list

Abebe, R. et al. (2021) Narratives and Counternarratives on Data Sharing in Africa | Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery. Available at:
https://dl.acm.org/doi/10.1145/3442188.3445897.

Chang, H.-C.H. and Fu, F. (2021) ‘Elitism in mathematics and inequality’, Humanities and Social Sciences Communications, 8(1). Available at: https://doi.org/10.1057/s41599-020-00680-y.

Chiodo, M. and Clifton, T. (2019) ‘The Importance of Ethics in Mathematics’, EMS Newsletter, 2019–12(114), pp. 34–37. Available at: https://doi.org/10.4171/NEWS/114/9.

Iman, M., Arabnia, H.R. and Branchinst, R.M. (2021) ‘Pathways to Artificial General Intelligence: A Brief Overview of Developments and Ethical Issues via Artificial Intelligence, Machine Learning, Deep Learning, and Data Science’, in H. Arabnia et al. (eds) Advances in artificial intelligence and applied cognitive computing: proceedings from ICAI’20 and ACC’20. Cham, Switzerland: Springer, pp. 73–87. Available at: https://doi.org/10.1007/978-3-030-70296-0_6.

Maass, K. et al. (2019) ‘Promoting active citizenship in mathematics teaching’, ZDM, 51(6), pp. 991–1003. Available at: https://doi.org/10.1007/s11858-019-01048-6.

Saltz, J.S. and Dewar, N. (2019) ‘Data science ethical considerations: a systematic literature review and proposed project framework’, Ethics and Information Technology, 21(3), pp. 197–208. Available at: https://doi.org/10.1007/s10676-019-09502-5.

Stephan, M. et al. (2021) ‘Ethical mathematics awareness in students’ big data decision making’, in Exploring new ways to connect: Proceedings of the Eleventh International Mathematics Education and Society Conference. Hamburg, Germany: Tredition, pp. 977–985. Available at: https://doi.org/10.5281/zenodo.5416678.

Stinson, C. (2022) ‘Algorithms are not neutral’, AI and Ethics, 2(4), pp. 763–770. Available at: https://doi.org/10.1007/s43681-022-00136-w.

Yan, T. (2021) ‘Consequences of Asking Sensitive Questions in Surveys’, Annual Review of Statistics and Its Application, 8(1), pp. 109–127. Available at: https://doi.org/10.1146/annurev-statistics-040720-033353.

View reading list on Talis Aspire

Interdisciplinary

Students will have opportunities to draw on knowledge and skills acquired within the different modules on their pathway.

International

The international nature of the student cohort allows for the teaching and learning to be approached from and inclusive of a range of international perspectives.

Subject specific skills

+. Strategies to read discipline specific genres effectively, appropriate to Maths and Computer Science.
+. Strategies to listen to discipline specific genres effectively, appropriate to to Maths and Computer Science.
+. Techniques to produce coherent discipline-specific written genres, appropriate to Maths and Computer Science.
+. Techniques to deliver an effective and engaging presentation, appropriate to Maths and Computer Science.
+. Strategies to participate effectively in and lead a seminar discussion, appropriate to Maths and Computer Science.

Transferable skills

+.Study skills
+.Academic integrity skills
+. Independent study skills
+.Information technology skills: library skills, research skills
+. Research methodology
+.Critical and innovative thinking
+.Report writing skills
+.Group work skills