Transcript Slide 1

Business School
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
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Examine aspects of the Quantitative Research: Defining,
Attributes, Features &Types
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Reflect and summarise on each approach
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How do users get what they want?
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The users dilemma
Traditional view of software development
Analysis – specification-development-implement-signoff
Happy users
So why do researchers report that 70% of system implementations fail
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
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» 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
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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
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Assumptions
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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
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Approach
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Theory generalising
Emergence and portrayal
Researcher as instrument
Naturalistic
Inductive
Pattern Seeking
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
Doing Qualitative
Research
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Many ways of collecting and analysing data
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Historical
Correlational
Developmental
Descriptive
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Qualitative Research:
Overview of Techniques
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Observation
Interviewing
Questionnaires
Group Discussion
Historical Study
Content Analysis
Ethnographical Research
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Qualitative Research
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Increased knowledge of qualitative research
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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
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Empirical “scientific” approach
– Relying on experimentation and not untested theory
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Searches for causality and effect
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Quantitative Research
:Deduction
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Top-down approach
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The inferring of particular instances from a general law
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Working something out from something else - Sherlock
Holmes style
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Attributes of Quantitative
Research 1
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Assumptions
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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
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Approach
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Hypothesis based
Manipulation and Control
Uses formal instruments
Experimentation
Deductive
Component analysis
Seeking norms and consensus
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
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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
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Relationships are measured
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Causal explanations are made
Quantitative Research :
Descriptive Statistics
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Allows summaries of large quantities of information
Should be easily comprehensible for reader
Presentation is vital
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long strings of numbers…
tables, charts, graphs
numerical techniques
concise, appropriate text
Quantitative Research :
Inferential Statistics
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Procedures for making generalisations about
characteristics of a population based on
information taken from that population
Powerful
– estimation
– hypothesis testing
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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
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Basis for managing risk
– Analysis of incidents
– Identify causal relationships
– Plan
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Quantitative Research
Summary
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Quantitative research is based on scientific inquiry
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Offers numerous techniques for data analysis
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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