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Research in the real world: the users dilemma
Dr Gill Green
RSBM

Overview of the Lecture
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 Context for the examination of research approaches
 Examine aspects of the Qualitative Research:
Defining,
Attributes, Features &Types
 Examine aspects of the Quantitative Research:
Defining,
Attributes, Features &Types
 Reflect and summarise on each approach
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The users dilemma
 How do users get what they want?
– Traditional view of software development
– Analysis – specification-development-implement-signoff
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Happy users
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So why do researchers report that 70% of system implementations fail
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How do users know what they want?
–
The Marco Polo effect
»
How do you describe something you have never seen before
–
The gambler effect
» How do you speculate how you may like to do things in the future
– The tigger effect
» How easy is it to ask for the wrong thing

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Some hard words
 Ontology – What is
 epistemology – what it means to know
 Why is this important?
 You need to know for yourself how you interpret your world?
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Theoretical perspectives and what they teach us
 Positivist
– Reality consists of what is available to the senses
– Inquiry should be based upon scientific observation and empirical action
– Principles are shared between Natural and human sciences and deal with facts not values
 Interpretivist
– Reality is a shifting state culturally derived and historically situated
–
Inquiry deals with the actions of individuals in social settings
–
Principles suggest the emergence of unique individual qualitative aspects
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What is Qualitative
Research
“Qualitative research is a process of enquiry that draws data from the context in which events occur, in an attempt to describe these occurrences, as a means of determining the process in which events are embedded and the perspectives of those participating in the events, using induction to derive possible explanations based on observed phenomena.”
(Gorman & Clayton, 1997)
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What happens in
Qualitative Research?
 Data taken from context in which events occur
 Data collection first hand
 Attempt to describe occurrences
 Focus on process not snapshot
 Immersion leading to insight
 Induction
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Qualitative Research:
Induction
 Use of “bottom-up” approach to analyse and interpret data


Research based on observed data
“Grounded” theory
– that is based on established theories
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Qualitative Research:
Attributes 1
 Assumptions
– social construction of reality
– primacy of subject matter
– complexity of variables
– difficulty in measuring variables
 Purpose
– contextualisation
– interpretation
– understanding participant perspectives
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Qualitative Research:
Attributes 2
 Approach
– Theory generalising
– Emergence and portrayal
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Researcher as instrument
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Naturalistic
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Inductive
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Pattern Seeking
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Looking for pluralism and complexity
–
Descriptive
 Researcher Role
– personal involvement and partiality
– empathetic understanding
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Key features of Qualitative
Research (Hittleman & Simon)
 Data is collected within its natural setting. Main data collection instruments are the researchers themselves
 Data are not numerical
 Focus on the process of an activity, not just its outcomes
 Data analysed in non-numerical manner. Outcomes generate debate rather than verifying a predicted outcome
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Qualitative Research: Why is it important in IT
 Many of techniques and methods can be applied to the requirements engineering process
 Helps to place user at centre of design process
 Enables triangulation with quantitative methods
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Doing Qualitative
Research
 Many ways of collecting and analysing data
– Historical
– Correlational
– Developmental
–
Descriptive
–
...
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Qualitative Research:
Overview of Techniques
 Observation
 Interviewing
 Questionnaires
 Group Discussion
 Historical Study
 Content Analysis
 Ethnographical Research
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Qualitative Research
Summary
 Increased knowledge of qualitative research
 Awareness of qualitative approaches relevance to computing
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Quantitative Research:
What is it?
 The aim of quantitative research is not simply to state that something has a relationship with something else, but to state causality
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Quantitative Research
 Focuses on numerical and statistical data


Positivist approach
– Recognising only positive/measurable facts and observable phenomena
Empirical “scientific” approach
–
Relying on experimentation and not untested theory
 Searches for causality and effect
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Quantitative Research
:Deduction
 Top-down approach
 The inferring of particular instances from a general law
 Working something out from something else - Sherlock
Holmes style
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Attributes of Quantitative
Research 1
 Assumptions
– objective reality of social facts
– primacy of method
– possible to identify variables
– possible to measure variables
 Purpose
– generalisation
– prediction
– causal explanation
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Attributes of Quantitative
Enquiry 2
 Approach
– Hypothesis based
– Manipulation and Control
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Uses formal instruments
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Experimentation
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Deductive
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Component analysis
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Seeking norms and consensus
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Reducing data to numerical indices
 Researcher Role
– detachment and impartiality
– objective portrayal
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Features of Quantitative
Research 1
 Tests for cause and effect
– X causes Z to happen
– Y does not cause Z to happen
 Not simply that something has a relationship with something else
 Involves empirical studies
 Uses numerical and statistical techniques
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Features of Quantitative
Research 2
 Assume primacy
– Researcher defines the research activity
 Relationships are measured
 Causal explanations are made
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Quantitative Research :
Descriptive Statistics
 Allows summaries of large quantities of information
 Should be easily comprehensible for reader
 Presentation is vital
– long strings of numbers…
– tables, charts, graphs
– numerical techniques
– concise, appropriate text
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Quantitative Research :
Inferential Statistics
 Procedures for making generalisations about characteristics of a population based on information taken from that population
 Powerful
– estimation
– hypothesis testing
 Methods and rules for organising and interpreting data
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Quantitative Research:
Why is it important in IT
 Establishes metrics
– Report on process and system efficiency concerns
– Predict outcomes from developments
– Improve development and operational processes
 Basis for managing risk
–
Analysis of incidents
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Identify causal relationships
–
Plan
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Quantitative Research
Summary
 Quantitative research is based on scientific inquiry
 Offers numerous techniques for data analysis
 Searching for causality and prediction
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Some questions to answer for next week
 Can you identify your epistemological stance?
 Have you identified a theoretical perspective
 Is your approach deductive or inductive
 Have you considered research methodology
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