Research Techniques

Alan Dix

School of Computing 
Staffordshire University
http://www.soc.staffs.ac.uk/~cmtajd/

Research?

•	what is it?
•	should you be doing it?
•	how do you do it?

Definitions of research

“Systematic investigationtowards increasing the sum of knowledge”
			(Chambers 20th Century Dictionary)

“an endeavour to discover new or collate old facts etc. by the scientifi study of a subject or by a course of critical investigation.”
			(The Concise Oxford Dictionary)

Types of research

•	the scientist
•	the social scientist
•	the historian
•	the journalist

?	R & D

The project

•	integrative
•	independent
•	interesting
•	intellectually challenging
?	innovative
		not necessary but good

it is wise to learn from
			your own mistakes

it is shrewd to learn from
			other people’s mistakes

Other people’s work

•	what they write
				books, articles, manuals
•	what they say
				interviews, discussion
•	what they make
				software, organisations

Finding references

•	keyword searches
•	backward:  bibliographies
•	forward:  citation indexes
•	what’s available

Filtering references

be selective!

	•	keywords   (unreliable)
	•	abstracts
	•	skim read
	•	citation count

Recording references

what	where	
•	details (title etc.)	•	card index	
•	keywords (your own)	•	word processor file	
•	mini abstract	•	standard database	
•	key points	•	bibliographic db	

Talking to people  –  who

•	client
•	supervisor
•	other staff
•	friends and contacts

Talking to people  –  what

•	you don’t know what you’re doing

	professional	—	does it
	academic	—	knows about it

				
Artefacts 
		Embody
				Experience

•	what is good about it?
				why is it good?

•	what is bad about it?
				why is it bad?

•	why do it this way?

Artefacts
		Embody
				Theories

e.g.,  mouse  ﬁ  hand/eye control better than typing

deep understanding helps

•	combine ideas
			avoid the crocaphants
•	change context
			e.g., interfaces for the blind
•	improve and correct

				
Artefacts
		Embody
				Assumptions

	solutions depend on context
			e.g.,  speed vs. space for algorithms

Your own work

Analyse existing work

•	classify
•	taxonomise
•	multiple perspectives
•	matrices
					
Understand your context
				
matching solution?
	yes	—	then use it
	no	—	synthesise

Planning for innovation
	?	
Don’t rely on it!

Finding new ideas

	•	abstraction
	•	analogy
	•	lateral thinking
	•	challenge yourself
	•	silly ideas
				e.g., the munchman interface  

Evaluation

		•	testing
		•	simulation
		•	proof
		•	statistical
		•	anecdotal

Critique  –  the good

	good points

		•	say what they are!
		•	what is novel, interesting?
		•	how does it relate to theory?

Critique  –  the bad

	what is wrong and why

		•	resource limitations
		•	ran out of time
		•	lack of experience
		•	hindsight