Professor Dodgson instigated, designed, and ran the highly-regarded Research Skills course at the Cambridge Computer Laboratory for five years.

There are videos of the fourth year of the course, run in the 2012-13 academic year.

The remaining pages in this part of the website are the course notes from the fifth year of the course, run in the 2013-14 academic year.

Aims

To provide advice on and training in the practical skills required for research. To provide training in skills that will be useful in the other research-led modules, in the project or essay, and in the student's future career.

Syllabus

• The Research Process: what is research? how is it conducted?

• Reading and Reviewing: critical reading, the review process.

• Presenting: how to prepare and deliver a research presentation.

• Experimental methods: experiment design, data analysis, statistical analysis

• Writing: how to write a good research paper. The structure of a paper. Writing the first draft. Editing and polishing. English style. Choice of publication venue.

• Graphs, figures, tables, mathematics, algorithms.

Objectives

On completion of this module, students should have improved their ability in the practical aspects of research, including improvements in ability to critique the work of others, to critique their own work, to write, to present, and to conduct and analyse experiments.

Coursework and assessment

The module required students to undertake a range of exercises that gave them the opportunuity to practice the various skills. Marked exercises comprised 20% of the marks. Ticked exercises comprised a further 20% of the marks. Ticked exercises had to be completed but did not receive individual feedback. Formal assessment was through a test that covered the same material as the ticked exercises (60%).

Exercises:

1. Reviewing a paper [ticked, 4 marks]
2. Editing a piece of text [ticked, 4 marks]
3. Reducing a piece of text [ticked, 4 marks]
4. Graphing data [ticked, 4 marks]
5. Analysing experimental results [ticked, 4 marks]
6. Reviewing a number of presentations [10 marks]
7. Writing an original piece [10 marks]
8. Written test [60 marks]

Required reading

Justin Zobel (2004). Writing for computer science. Springer (2nd ed.).

Recommended reading

Presentations

Garr Reynolds (2011). Presentation Zen. New Riders (2nd ed.).
Chip & Dan Heath (2007). Made to Stick. Random House.

Experimental design

Doug Cunningham & Christian Wallraven (2012). Experimental Design. CRC Press.
Jonathan Lazar, Jinjuan Heidi Feng & Harry Hochheiser (2009). Research methods in human-computer interaction. Wiley.
Peter Dalgaard (2008). Introductory statistics with R. Springer (2nd ed.).

More detailed explanations of statistical theory and data analysis

Michael Crawley (2007). The R Book. Wiley.
Andy Field (2009). Discovering statistics using SPSS. Sage (3rd ed.). 
John Rice (2006). Mathematical Statistics and Data Analysis. Brooks/Cole (3rd ed.).