Accessibility statement

Professional & Academic Development - COM00195M

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  • Department: Computer Science
  • Module co-ordinator: Dr. Carlo Ottaviani
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2024-25
    • See module specification for other years: 2023-24

Module will run

Occurrence Teaching period
A Semester 2 2024-25

Module aims

This module prepares students for careers in computing and academic research. The module involves a multi-pronged approach to personal and professional development by providing students an opportunity to self-identify learning needs and skill development with the support of a mentor. Students will develop the competencies required for practising within the complex framework of accountability, ethical and professional boundaries in the multi-disciplinary workplace. The module captures the following key activities:

  1. Planning
  2. Assessing/reflecting
  3. Professional development/self-directed training
  4. Communication

Module learning outcomes

During this module, students will produce a short project in which they will demonstrate, and reflect on, professional skills. By the end of the module, they will be able to::

  • Demonstrate and critically reflect on their own and others' written and verbal communication styles for a broad range of professional, public and academic audiences

  • Describe and justify a project proposal that is grounded in existing academic literature and professional practice

  • Identify, describe and evaluate personal development opportunities and training needs through self-reflection and self-directed learning

Assessment

Task Length % of module mark
Essay/coursework
Presentation		 N/A 40
Essay/coursework
Project Proposal		 N/A 60

Special assessment rules

None

Reassessment

Task Length % of module mark
Essay/coursework
Presentation Reassessment		 N/A 40
Essay/coursework
Project Plan Reassessment		 N/A 60

Module feedback

Feedback is provided throughout the sessions, and after the assessment as per normal University guidelines

Indicative reading

Key texts

  • J. Zobel, Writing for Computer Science. London: Springer London, 2014. doi: 10.1007/978-1-4471-6639-9
  • E. R. Tufte, The Visual Display of Quantitative Information, 2nd ed. Cheshire, Conn: Graphics Press, 2001. https://yorsearch.york.ac.uk/permalink/f/1kq3a7l/44YORK_ALMA_DS21202699750001381
  • D. Huff, How to Lie with Statistics, Repr. London: Penguin, 1991. https://yorsearch.york.ac.uk/permalink/f/1kq3a7l/44YORK_ALMA_DS21190573200001381
  • A. Watt, Project management, BCcampus Open Education Pressbooks, 2004
  • C. Ghezzi and G. Ghezzi, Being a researcher, Springer, 2020

Other relevant links:

  • The illustrated guide to a Ph.D., https://matt.might.net/articles/phd-school-in-pictures/
  • A Gentle Introduction to Statistical Power and Power Analysis in Python, https://machinelearningmastery.com/statistical-power-and-power-analysis-in-python/
  • Seeing through statistics, https://yorsearch.york.ac.uk/permalink/f/1d5jm03/44YORK_ALMA_DS21223399890001381
  • Statistics for experimenters : design, innovation, and discovery, https://yorsearch.york.ac.uk/permalink/f/1kq3a7l/44YORK_ALMA_DS21221776990001381
  • Heath, C., & Heath, D. (2008). Made to stick: Why some ideas take hold and others come unstuck. Random House


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.