Exam Flashcards
1
Q
[wyk.5] What is QUALITATIVE INQUIRY (3)
A
- For studying social and cultural phenomena of interest.
- Understand the context they are part of from the participant point of view.
- Conducted in natural settings
2
Q
[wyk.5] When is Qualitative research used? (5)
A
- New topic
- Lack (or only a few) of previous research
- Explorative
- When phenomena needs to be investigated when applied to a new type of sample participants
- When phenomena needs to be addressed with a new theory
3
Q
[wyk.5] Characteristics of Qualitative research (5)
A
- In natural settings
- Researcher is an instrument for gathering the data
- Multiple sources of data
- Uncover the participants’ meanings
- Emergent design
4
Q
[wyk.5] Qualitative strategies of inquiry (3)
A
- Etnography
- Grounded theory
- Case study
5
Q
[wyk.5] What is CASE STUDY (6)
A
- No common agreement on what it is in the literature
- The objective is to add knowledge about the individuals, groups, organizations, about social or political phenomena
- Study about complex phenomena in their (real-life) context to gain holistic understanding
- Boundaries between phenomenon and context not clearly visible
- Using multiple sources of evidence
- Researcher exercises no control
6
Q
[wyk.5] When to use Case Study? (6)
A
- Focus of the study is on How? and Why?
- Exploration of phenomena in natural setting
- Researcher does not control the study object
- No specifications of variables before
- When the context is highly related and relevant for investigated phenomena
- Boundaries between phenomenon and context are not clear
7
Q
[wyk.5] Philosophical paradigms of Case Studies (3)
A
- Positivist
- Interpretive
- Critical
8
Q
[wyk5] Case study: research design POSITIVISM
A
Design is pre-defined before the research starts
9
Q
[wyk5] Case study: research design INTERPRETIVISM
A
Design is flexible, the initial theories and assumptions can be modified
10
Q
[wyk5] Types of Case Studies (3)
A
- Intrinsic
- Instrumental
- Collective Case
11
Q
[wyk5] INTRINSIC Case Study
A
Researcher is personally interested in the case. Interest lies in the case itself, not in using it to understand something bigger
12
Q
[wyk5] INSTRUMENTAL Case Study
A
To understand the bigger research question. Understanding the case is the mean to understand something bigger.
13
Q
[wyk5] COLLECTIVE Case Study
A
Several cases and each one of them is INSTRUMENTAL to understand something bigger
14
Q
[wyk5] Multiple case study
A
Quintain - A target, phenomenon we want to study
Degree of similarity between case studies
Common characteristics
15
Q
[wyk5] Data collection -Multiple data sources for the case study (4)
A
- Interviews
- Documents
- Archival records
- Observations
16
Q
[wyk5] Qualitative validity (6)
A
RESEARCH checks for the accuracy of findings by certain procedures
- Triangulation of data sources
- Use member checking
- Rich description
- Spend prolonged time in the field
- Present negative or discrepant information
- Peer debriefing
17
Q
[wyk5] Qualitative reliability (3)
A
PROCEDURES are consistent
- check transcripts
- in teams, coordinate the communication among those involved in coding
- continuous comparison of data with codes
18
Q
[wyk5] Qualitative trustworthiness
A
How much the researcher is able to persuade the audience that the findings of the research are convincing and plausible
- Transferability - how the results can be transferred to other contexts or settings
- Credibility - findings based on real data, interpretation of data mirrors participants’ views
- Dependability - continuous assessment of findings over time in terms of consistency
- Confirmability - degree of confirmation by other researchers
19
Q
[wyk5] Advantages of case studies (2)
A
- Holistic view on the phenomenon, getting an understanding from multiple angles
- Strength lies in the depth of the research
20
Q
[wyk5] Disadvantages of case studies (3)
A
- Little generalizations whereas it is definitely not statistically accurate
- Take longer time
- The researcher’s beliefs affect the results interpretation
21
Q
[wyk6] Ethnography (7)
A
- Description and interpretation of the culture and the social structure of a social group
- Description of life in the community in detail
- Researcher has to become accepted member of the group and participate in the cultural life and practices of the group
- Study duration is long
- Studies are conducted in the natural environment of the group
- Based on social anthropology
- Based mainly on observations and interviews
22
Q
[wyk6] Traditional (social anthropological) ethnography (3)
A
- Naturalistic
- Prolonged
- Immersive
23
Q
[wyk6] Information Systems related ethnography (3)
A
- Not naturalistic, but in natural real world settings
- Does not have to be prolonged
- Immersive
24
Q
[wyk6] Principles of ethnography in IS research (4)
A
- Natural setting
- Holistic view
- Descriptive understanding
- Participants’ point of view
25
[wyk6] Common focus of ethnographical studies in IS (4)
1. Corporate cultures
2. Organizational roles
3. Work practices
4. The role of artefacts (physical or digital)
26
[wyk6] Ethnography in IS research provides
1. domain knowledge
2. overall view of complex settings (otherwise hard to obtain)
3. multiple perspectives from variety of stakeholders
etc.
27
[wyk6] Data collection in Ethnography (4)
1. Observations and notes taking
2. Interviews
3. Documents
4. Photos/video
28
[wyk6] SHORTLY - what is Ethnography?
methodology
29
[wyk7] Iterative nature of research [Action research]
-> PLAN -> ACT -> OBSERVE -> REFLECT -> <<>>
30
[wyk7] Action research principles (5)
- The company/society/organization can be studied as a whole (social settings cannot be reduced!)
- Complex social processes can be studied best by introducing changes in the processes and observing its effects
- postpositivist, interpretitive philosophy
- CYCLIC and ITERATIVE!
- practical, problem-solving approach
31
Research approaches (3)
- Qualitative
- Quantitative
- Mixed methods
32
Research designs (3)
- Qualitative (e.g. ethnographies)
- Quantitative (e.g. experiments)
- Mixed methods (e.g. explanatory sequential)
33
Research methods (5)
- Questions
- Data collection
- Data analysis
- Interpretation
- Validation
34
Philosophical worldviews (4)
- Postpositivist
- Constructivist
- Transformative
- Pragmatic
35
Postpositivism worldview (4)
- Determination
- Reductionism
- Empirical observation and measurement
- Theory verification
36
Constructivism worldview (4)
- Understanding
- Multiple participant meanings
- Social and historical construction
- Theory generation
37
Transformative worldview (4)
- Political
- Power and justice oriented
- Collaborative
- Change oriented
38
Pragmatic worldview (4)
- Consequences of actions
- Problem-centred
- Pluralistic
- Real-world practice oriented
39
[wyk7] Action research CYCLE
Plan -> colaborative analysis of social situation by the researcher and subjects
Act -> collaborative change experiments
40
[wyk7] Ideal settings for AR (3)
- The researcher is actively involved with expected benefit for both researcher and organization - active participant, not only observer
- the knowledge obtained can be immediately applied
- research is the link of theory and practice
41
[wyk7] Action research vs consulting (5)
- AR is focused on scientific gains rather than commercial
- AR commits both to the scientifical knowledge and to the client. Consulting only works for the client.
- AR collaborates more with the organization, whereas consulting prefers its own objective perspective
- AR recommends based on the theoretical framework. Consulting based on the previous experiences.
- AR improves by iterative change, consulting by thorough critical analysis
42
[wyk7] Action research shortcomings (2)
- Being confused with consulting when not stated clearly, the company might have totally different expectations and try to influence the research process
- Harder to control the outcome of the iterative process
43
[Wyk8] Positivist ontology and epistemology (7)
- Objective reality exist independent of humans
- Reality is relatively stable and orderly and it can be accurately described in models and theories
- The entities used in the theories can be identified in reality (variables)
- The variables can be measured and often also controlled separately (reduction)
- The entities can be measured objectively, independent of the observer and instruments
- Consequently, the measurements can be repeated / replicated by other researchers and the results can be generalized
- The ideal positivist inquiry is objective and value-free
44
[wyk8] Causal models
Independent variable X causes the change in the dependent variable Y.
X => Y
The experiment controls the X and the effect on Y is studied.
X => Z => Y
means the Z is intervening (mediating) variable
Real theoretical models are obviously more complex
45
[wyk8] Quantitative strategy - CAUSALITY in Experimental Studies
Research -> Explanations (THEORIES) -> Predictions (HYPOTHESES)
46
[wyk8] Experimental design (4)
- active manipulation of the independent variable (X)
- observation or measurement of dependent variable (Y)
- split in experimental and control groups
- random assignment to the equivalent groups [RANDOMIZATION]
47
[wyk8] Non-experimental design
- no active manipulation of an independent variable
- no random assignment to experimental and control groups
48
[wyk8] Quasi-experimental design
- include active manipulation of an independent variable
- no random assignment to experimental and control groups
49
[wyk8] What is population?
Number of units we plan to study (N)
50
[wyk8] What is sampling frame?
A list of all the units in the population
51
[wyk8] What is complete enumeration (total population count, census)?
A study of every unit in the population
52
[wyk8] What is a sample?
A subset of studied units from the population (n). N > n
53
[wyk8] What is an observation?
Value of the specific property/attribute (variable) that we aim to study
54
[wyk8] What is statistics?
Methodologies to collect, visualize, organize, analyze and draw conclusions from the data
55
[wyk8] What is descriptive statistics?
Description and visualisation of population's or a sample's central tendencies, variability (dispersion) and distribution shape, as well as correlation between two variables
56
[wyk8] What is statistical inference?
Draw conclusions about the population by examining a representative sample of the population; involves often hypothesis testing
57
[wyk8] Scales of measurement
Non-quantative (categorical) variables:
- Nominal scale - categorization, classification
- Ordinal scale - Classification and rank order
Quantative (numerical) variables:
- Interval scale - Classification, rank order and equal intervals
- Ratio scale - Classification, rank order, equal intervals and absolute zero point
58
[wyk8] Numerical variables can be
- Continuous
- Discrete
59
[wyk8] Frequency of an observation
How many times the observation value occurs in the data (both qualitative and quantitative data)
60
[wyk8] Frequency distribution
Can be shown in the cross tabulation / contingency table in absolute (no. of occurrences) or relative form (percentage in the sample)
61
[wyk8] Histogram
Used for continuous, numerical values. Visualizes the shape, center and variability of the distribution.
62
[wyk8] Bar chart
Used to compare frequencies of different categories
63
[wyk8] Pie chart
Used for categorical variables and discrete, numerical variables. Used to compare frequencies of different categories.
64
[wyk8] Central tendency
Shows the center point or typical value of a dataset.
65
[wyk8] Variability (dispersion, spread)
Describes how spread out the data is
66
[wyk8] Relative error
(The sample mean - population meal) / population meal
67
[wyk8] Standard deviaion
How close each of the observed value is to the mean
68
[wyk8] Positively skewed distribution
Long tail on the right
69
[wyk8] Negatively skewed distribution
Long tail on the right
70
[wyk8] Box plot
Display the median and the distribution of data with Q1 and Q3 quartiles
71
[wyk8] Correlation
To describe strength and direction of the relationship between the two variables
72
[wyk8] Pearson product-moment correlation coefficient
r = 0 indicates zero-correlation, i.e. no relationship between x and y
0 < r < +1 positive correlation, y increases when x increases
-1 < r < 0 negative correlation, y decreases when x increases
r = +1 perfect positive correlation; perfect linear relationship
r = -1 perfect negative correlation; perfect linear relationship
73
[wyk8] Outliers
The Pearson product-moment correlation coefficient, r, is
sensitive to outliers, i.e. single data points that deviate from
the overall pattern.
* Outliers may lead to misleading results, so that if we are quite
sure that they are a result of measurement errors, they can
be removed.
* On the other hand, sometimes outliers may indicate a real
discrepancy that should be investigated.
74
[wyk8] Spearman’s rank correlation coefficient, ro
Spearman’s rank correlation coefficient, r, is a non-parametric
test to measure the strength and the direction of the monotonic
relationship between two ordinal scale variables or one ordinal
and one quantitative variable.
Monotonic relationship requires that as the value of one
variable increases, the value of the other variable either
increases or decreases; however, it does not require a linear
relationship
r can have values from -1 to +1;
r = 0 indicates zero-correlation, i.e. no relationship between the variables
r = +1 perfect positive correlation
r = -1 perfect negative correlation
75
[wyk8] Sampling
Procedure of selecting a sample from population
76
[wyk8] Response rate
Fraction of the individuals in the sample that participate in a study
77
[wyk8] Sampling error
Difference between the value of the sample statistics and the true value of the population parameter
78
[wyk8] Random sampling techniques (3)
Simple random sampling
Stratified random sampling
Cluster random sampling
79
[wyk8] Simple random sampling
n units out of N are chosen randomly
80
[wyk8] Stratified sampling
Each individual comes from the one (and only one) group (stratum). The surveyed sample comes from all of the groups (strata)
81
[wyk8] Cluster sampling
Each individual comes from the one (and only one) group (stratum). Only the individuals from the selected clusters are surveyed. [lower precision]
82
[wyk8] Quantitative strategy
Ideally we should achieve objectivity and generalization, so the procedure should be repeatable by other researchers
83
[wyk8] Total error
Sum of sampling error and bias
84
[wyk8] Bias
Bias is a systematic error due to erratic way of sampling, measurements and/or reporting
85
[wyk8] Quantitative validity (3)
Validity
* The extent to which the tools/instruments are measuring
what we intend to measure
* Accuracy of the interpretations and inferences that are based
on the results (test scores)
* Do the conclusions give an (approximately) true description of
the reality?
86
[wyk8] Quantitative reliability (2)
Reliability
* Consistency or stability of the test scores
* If the measurements are repeated will the same results be
obtained?
87
[wyk9] Design science (2)
- Problem-solving paradigm
- Holistic approach - technology and behavior are considered inseparable entities
88
[wyk9] IT Artifacts (4)
IT artifacts are at the center of the process helping researchers to
understand the problem and approach the solution
Artifacts being:
– Constructs (language, symbols, vocabulary)
– Models (representations of real-world situation)
– Methods (algorithms, practices, guidelines)
– Instantiations (prototypes)
89
[wyk9] Guidelines for Design science in IS Research (7)
G1: Design as an artifact
G2: Problem relevance
G3: Design evaluation
G4: Research contributions
G5: Research rigor
G6: Design as a search process
G7: Communication of research
90
[wyk9] Guidelines for Design science in IS Research: Design as an artifact
G1
- Producing innovative and purposeful artifacts
- Artifact is used to define ideas,
practices
- Something to be evaluated, without a goal to be used in practice (the goal is solving the problem)
91
[wyk9] Guidelines for Design science in IS Research: Problem relevance
G2
- Everything starts from a problem which needs to be defined
- Develop technology-based solutions to relevant problems
92
[wyk9] Guidelines for Design science in IS Research: Design evaluation
G3
- Evaluation of the artifact provides feedback and a better understanding of the problem
- Qualitative and quantitative
- Evaluate artifacts with regards to:
–- Effectiveness
–- Efficiency
–- Usability
93
[wyk9] Guidelines for Design science in IS Research: Research contributions
G4
Must provide clear contribution on:
–- Design of the artifact itself
–- Design of evaluation methods (e.g., experimental, observational, etc.)
-Goal is to improve the quality of the product and the design process
94
[wyk9] Guidelines for Design science in IS Research: Research rigor
G5
- Application of rigorous methods in both the construction and evaluation of the designed artifact
Continuous assessment of appropriateness of artifact design and evaluation methods/metrics
95
[wyk9] Guidelines for Design science in IS Research: Design as a search process
G6
- Search process to discover an effective solution to a problem
- Sometimes it is helpful to decompose a bigger problem into
subproblems
- Design artifacts for subproblems- Design is both, a process (set of
activities) and a product (an
artifact)
96
[wyk9] Guidelines for Design science in IS Research: Communication of research
G7
Research results should be communicated to both:
– Technology-oriented audience
– Management-oriented audience
- Emphasis should be on the importance of the:
– problem being solved
– novelty and effectiveness of the
solution using the artifac
97
[wyk9] Design thinking (2)
- human-centric approach
- prototyping
98
[wyk9] Prototyping (3)
- paper prototypes
- digital (interactive) prototypes
- physical gadget
99
[wyk9] Design Thinking compared to Design Science (4)
– Provides more structure making it easier to follow phases
– Is more suitable for ill-defined problems, which are most of today’s problems
– Provides bigger emphasis on users, not artifacts
– Freedom to reiterate on each phase
100
What is ONTOLOGY
Ontology is a philosophical theory regarding the nature of reality, asserts that there is either a single reality or none at all. To be more specific, ontology answers the question, “What is reality?” - question WHAT
101
What is EPISTEMOLOGY
Epistemology is the study of knowledge, focusing on the validity, extent, and ways of gaining knowledge. Epistemology seeks to address the question, “How can we know reality?“ - question HOW
102
Methodology
Methodology refers to general concepts that underpin how one explores the social environment and proves the validity of the knowledge gained. The methodological question is “How to go about discovering the reality/answer?“
103
Positivist Paradigm
- Single reality that can be measured and understood, relatively stable
- Uses quantitative approaches to research the reality
104
Interpretivism Paradigm
- There are multiple realities
- Focuses more on qualititative research
- Human behavior is complex and cannot be properly predicted
105
Pragmatism Paradigm
- Depending on the research topic, it can incorporate both positivist and interpretivism paradigms
- Problem-solving philosophy, we take what brings the best results
106
What is research problem? (2)
- Statement that addresses a gap in knowledge
- Challenge or contradiction in the field
107
Characteristics of research problem (3)
- Reflecting on issues or required knowledge in a particular field
- Rely on evidence and data
- Practical and manageable for the researchers involved in data collection and analysis
108
Types of research problems (3)
1. Theoretical research problem
2. Applied research problem
3. Action research problem
109
How to identify an area of research problem (3)
- find contradiction between theoretical perspectives
- find the contexts not well investigated
- find the processes that can be improved
110
How to formulate research problem (6)
1. Identify an area of interest
2. Learn more about the problem
3. Review the context of the information
4. Determine relationships between variables
5. Select and include important variables
6. Receive feedback and revise
111
What is theory in research (2)
- well defined explanation of the phenomena
- might incorporate laws, hypotheses and facts
112
Quantitative Research Methodology (4)
- Quantitative data
- Closed-ended questions
- Large sample sizes
- High External Validity - highly generalizable
113
Qualitative Research Methodology (3)
- Open-ended questions
- Complex reasoning
- Important role of the researcher
114
Mixed Methods Methodology
- Flexible - we take what best suits for the research
- Combines the benefits of both Quantitative and Qualitative approaches
115
Qualitative approaches to inquiry (5)
- Narrative research - chronological study of experiences of the individuals
- Phenomenology - study of an idea or concept that has a common meaning for a small group of individuals
- Grounded theory research - seeks to generate or discover a theory (general explanation) for social process, action or interaction shaped by the view of participants, larger datasets to understand a phenomenon
- Ethnographic - interpret the shared and learned patterns of values, behaviors, beliefs or language of the group, researcher participates
- Case study - detailed study to illustrate and understand the issue on a real-life example
116
Quantitative approaches to inquiry (3)
True Experiment - controlled variable, randomized samples [hypothesis testing experiments]
Quasi Experiment - controlled variable, not randomized [correlational and single-subject studies]
Non Experimental - no treatment of subjects [surveys]
117
Methods of data collection (8)
1. Experiment
2. Survey and questionnaire
3. Observation and note-taking
4. Ethnography
5. Secondary data collection
6. Archival research
7. Interview
8. Focus group [with moderator]
118
Methods of data analysis (5)
1. Regression analysis - to estimate how the independent variables can impact the dependent variable in order to identify trends and patterns
2. Factor analysis - reducing a large number of variables to a smaller number of factors. Multiple separate variables correlate each other.
3. Cohort analysis - breaking down of the dataset into related groups for analysis (common characteristics or experiences) within a defined time span
4. Cluster analysis - sorting different data points into groups (clusters) that are internally similar within the group and different comparing to the data in other groups
5. Time series analysis - identify trends and cycles over time
119
What is reliability? (2)
- consistency of measure - can you reproduce the same results under the same conditions?
- checked across the time and across different observers
120
What is validity? (2)
- accuracy of measure - is the data representing what it is supposed to measure
- Checked how well the result correspond to the theories or other measures of the same concept
121
Ethical considerations (6)
1. Voluntary participation
2. Informed consent
3. Anonymity
4. Confidentiality
5. Potential for harm
6. Results communication (no research misconduct, plagiarism)
