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In god we trust Flashcards

1
Q

What is Action research (AR)

A

Action research is described as a research method suitable for studying technology in social contexts. To only study real world problems without assisting or take part in the problem solving is regarded as unhelpful. Researcher helps client to identify and solve a problem

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2
Q

What is Technical action research (TAR)

A

Technical action research refers to a systematic approach where practitioners, often in technical fields such as engineering or computer science, engage in research activities to solve practical problems or improve processes within their professional domains. The researcher wants to learn something about a technique by
using it to solve a client’s problem

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3
Q

Contrasting TAR with AR in information system

A

AR in information systems
- Identify problem in an organization
- Jointly search for a solution and implement it
- Evaluate
- Specify learning
TAR is technology-driven, not problem driven!
- The technology is motivated by a desire to solve a class of problems
- Not a singular problem in a specific situation

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4
Q

In technical action research, what are the three roles of the researcher?

A

Designer, helper, researcher

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5
Q

Design Science Research (DSR

A

Design Science Research (DSR) is a research methodology used primarily in information systems. It focuses on creating innovative artifacts to solve complex problems or improve existing systems.

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6
Q

What is an artifact in IT-research?

A

An artifact is something that is created human begins which don’t exist without human involvement as something either by design or by interpretation.

Example of artifacts are computers, software, methods, models and so on.

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7
Q

What is hermeneutics?

A

Hermeneutics mean to develop the ability to understand phenomenon’s from another person’s perspective and to be able to understand and appreciate cultural and social forces that affects their situation.

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8
Q

What are the 3 types of literature review and there purpose?

A

Simplified literature review
- Identify and summarize seminal work in your chosen topic
Systematic literature mapping
- To structure a research area
Systematic literature review
- Gathering and synthesizing evidence

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9
Q

Describe the literature review process?

A

The literature review process involves systematically searching and critically evaluating existing literature relevant to a specific research topic or question.
Some steps that make a good literature review are:
Clearly defining scope and purpose: Determine the specific research question or topic you want to explore and establish the boundaries of your review (e.g., timeframe, geographical scope, types of sources).
Search for Relevant Literature: Use academic databases, library catalogs, and search engines to identify relevant literature. Employ a combination of Search terms, keywords, and strings, Quality criteria, Assessment and ranking functions.
Organize and Synthesize Information: Organize the selected sources chronologically based on common themes, topics, or key concepts. Identify patterns, trends, and gaps in the literature, and synthesize the findings to develop a coherent narrative that addresses your research question.
Write the Literature Review: Write the literature review using a clear and structured format. The review should be well organized and replicable.

Some steps that make bad literature review are:
Lack of Focus: A bad literature review may lack a clear focus or research question, resulting in a broad and unfocused review of the literature. Without a specific focus, the review may cover irrelevant topics, leading to confusion and lack of coherence.
Poor Organization: An ineffective literature review may suffer from poor organization, with sources arranged in a careless manner. This can make it difficult for readers to follow the text or identify key themes and trends within the literature.
Lack of Depth: A shallow literature review may provide only superficial coverage of the existing literature, failing to delve deeply into key concepts, theories, or empirical findings. This lack of depth can undermine the credibility and rigor of the review.
Lack of Critical Analysis: A weak literature review may lack critical analysis or evaluation of the sources reviewed. Instead of critically assessing the strengths, weaknesses, and limitations of each source, the review may simply summarize or describe the findings without offering meaningful insights or interpretations.
Existence of Previous Reviews: If comprehensive literature reviews already exist in the field, conducting another review without adding new perspectives or insights may be redundant and unnecessary.

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10
Q

What two stages of interpretation are important to hermeneutics?

A

1.Uncovering interpretation (finding how others have categorised the world)
2.Assigning interpretation (creating new categories)

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11
Q

What is Knowledge?

A

Knowledge is a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experience and information.

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12
Q

What is explicit knowledge?

A

Formal, codified: documents, databases, books etc

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13
Q

What is informal (tacit) knowledge?

A

Informal, uncodified: values, perspectives, culture, memories

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14
Q

What is categorical/descriptive knowledge?

A

categorical knowledge is the most fundamental type of knowledge, it is conceptualizing in terms of categories, concepts and relations

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15
Q

What is explanation knowledge/declarative knowledge?

A

Explanation knowledge is explanation of why a phenomenon is in a certain way.

Cause - effect - relationships
- if cause then effect
- if condition then result

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16
Q

What is evaluation/value knowledge?

A

Knowledge about the desirable, what we want given specific circumstances. Defining what “user friendly” means for example

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17
Q

What is normative/prescriptive knowledge?

A

Guiding knowledge
Advice, instructions, models, methods, tools, checklists… regarding a phenomenon.

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18
Q

What are some paradigms of research?

A
  • Positivism – How reality is
  • Realism – Objects exist independently of our will and knowledge
  • Interpretivism – Understand humans in their role as social actors
  • Pragmatism – If success then its good
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19
Q

What is positivism?

A

Working with an observable social reality, the researcher is independent of the research, highly structured.

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20
Q

What is realism?

A

Based on a belief that reality exists independent of human thoughts and beliefs. Social objects or phenomenon’s, external to or independent of individuals affect the way people perceive their world, whether they are aware of them or no

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21
Q

What is INFORMATION SYSTEMS (IS)

A

The discipline of information systems (IS) focuses on information
(data in a specific context) together with information capturing,
storage, processing and analysis/interpretation in ways that supports
decision making. The discipline emphasizes the importance of building systems solutions, preferably so that they can be continuously improved

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22
Q

COMPUTER SCIENCE (CS)

A

Computer science is the study of computers and algorithms,
including their principles, hardware and software design, their
applications, and their impact on industry and society

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23
Q

INFORMATION TECHNOLOGY (IT)

A

Information technology (IT) is the study of systemic
approaches to select, develop, apply, integrate, and
administer secure computing technologies to enable
users to accomplish their personal, organizational, and
societal goals

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24
Q

Why do we do Litterature Review?

A
  • To examine scientific progress and know what has been done
  • To find a research gap in order to motivate new research
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25
Q

How do we do Litterature Review?

A
  • By analyzing published results
  • By identifying and summarizing existing research and results
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26
Q

What is Iterative process?

A

Returning to earlier stages as you search, read an evaluate

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27
Q

What are some steps in the Literature search process?

A
  • Formulate a research topic and useful keywords
  • Refine the search. ex: date limits
  • Review your results and revise your search
  • Evaluate your results
  • Keep up-to-date with new literature on your topic
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28
Q

What should the literature review results be summarized in?

A
  • A related work section
  • Identification of research gap/problem description
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29
Q

What three types of litterature reviews are there?

A
  • Simplified literature review
  • Systematic literature review
  • Systematic literature mapping
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30
Q

What type of literature review is used to provide a survey of the field?

A

Systematic literature mapping/scoping

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31
Q

At what stage should the simplified literature review be conducted?

A

Before planning any form of research

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32
Q

What is the aim of the simplified literature review?

A

Idetify and summarize seminal work in your chosen topic

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33
Q

Purpose of Systematic literature mapping?

A

To structure a research area

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34
Q

Purpose of systematic literature review?

A

Gathering and synthesizing evidence

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35
Q

What type of literature review creates categories?

A

Systematic literature mapping

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36
Q

What type of literature review is used for evaluation and interpretation of research relevant to a particular topic?

A

Systematic Literature Review

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37
Q

What are the three high-level phases in a Systematic Literature Review?

A
  • Planning the review
  • Conducting the review
  • Reporting the review
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38
Q

What are individual studies that contribute to a systematic review called?

A

Primary studies

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39
Q

What is a form of a secondary study?

A

Systematic Review

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40
Q

What 6 types of information should be in a Literature Review Protocol?

A
  1. Search terms, keywords and strings
  2. Databases and sources used
  3. Inclution criteria
  4. General and specific exclution criteria
  5. Quality criteria
  6. Assessment and ranking functions
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41
Q

What are some signs of a bad literature review?

A
  • Lack of focus
  • Poor organizaton
  • Poor quality of sources
  • Not enough information in the protocol
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42
Q

What types of bias can there be?

A
  • Language bias, geographical
  • Selection bias
  • Selecting only results that support your hypothesis
  • Time related bias: Outdated information
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43
Q

What is an experminet?

A

A test under controlled conditions that is made to
demonstrate a known truth, examine the validity of a
hypothesis, or determine the efficacy of something previously
untried.

44
Q

Experiments. When and why?

A

When we need to identify dependable relationships between a
cause and its effects. When we need to identify conditions under which such causal relationships hold. Experiments are important for many societal challenges across domains, like engineering (how flexible is this metal?)

45
Q

Challenges of conducting
experiments

A

Choice of experimental design
Interpretation of the results
Statistics
Identifying and tackling validity threats

46
Q

What is a cause?

A

Most causes are more accurately called inus conditions. Presence of a match → forest fire? Any given effect often requires many factors to occur, but we rarely know all of them, or how they relate to each other.

As a consequence, many causal relationships:
are probabilistic rather than deterministic in a strict sense
are not universal, but occur only under some conditions or in certain
contexts

47
Q

Causality

A

It is rare that causal relationships hold under all conditions
with all types of people and at all historical time periods. It is vital to
identify relationships that hold more consistently.

48
Q

Effect – what is an effect?

A

An effect can be understood as the difference between what actually happened (the fact) and what would have happened if a specific cause had not occurred (the counterfactual).

Effect: The effect is essentially the difference between what actually happened (fact) and what would have happened if the cause had not occurred (counterfactual).

49
Q

What is a causal relationship?

A

The cause preceded the effect
The cause was related to the effect
We can find no plausible alternative explanation for the effect,
other than the cause

In experiments we:
Manipulate the presumed cause (and observe the outcome)
Observe whether variation in the cause is related to variation
in the effect
Attempt to rule out other explanations of the effect

50
Q

Correlation does not imply causation

A

We may not know which variable came first (i.e., whether the presumed cause preceded the effect). We cannot rule out alternative
explanations. If there exists a third variable that causes the effect, this is called a confounding variable, or simply confound.

51
Q

INDEPENDENT VARIABLE

A

Cause
This is the variable that is manipulated by the experimenter
The variable that i change

We want to know is if the independent variable affects the dependent variable in some way.

52
Q

DEPENDENT VARIABLE

A

Effect (result of experiment)
This is the variable that is measured by the experiment
It depends on the independent variable

The dependent variable is the variable that is observed and measured to see if it is affected by changes in the independent variable.

53
Q

Hypotheses

A

A hypothesis is a precise problem statement that can be
directly tested through an empirical investigation.

Example: “The iOS virtual keyboard is faster and more accurate
than the Android virtual keyboard.”

54
Q

Randomization

A

A true experiment must have randomization. Random assignment is intended to create units that are probabilistically similar to each other on average

Example: Every individual has the same chance to end up in a given condition. Therefore, any observed differences in outcome are likely to be due to the treatment (= cause)

55
Q

Simulations

A

Simulation refers to the process of creating and analyzing a
model or imitation of a real-world system or process to gain
insights into its behaviour or performance.

It involves using a computer program or mathematical model
to replicate a complex system’s essential features and
dynamics, allowing researchers to observe, experiment, and
make predictions in a controlled and virtual environment.

56
Q

Key aspects of simulations

A

Modeling: Constructing a representation of the real-world system or
phenomenon using mathematical equations, algorithms, or computer programming.
Manipulation: Changing variables or parameters in the simulated
environment to observe their effects on the system’s behavior.
Analysis: Collecting and interpreting data generated by the simulation to draw conclusions about the real-world system.
Prediction: Extrapolating the simulation results to make predictions
about the future behavior or outcomes of the real-world system under different conditions.

57
Q

Confounding variable

A

A variable that is not controlled but can affect the dependent
variable.

58
Q

Control Variable

A

A control variable is a circumstance (not under investigation) that is kept constant while testing the effect of an independent variable

More control means the experiment is less generalizable (i.e., less applicable to other people and other situations)

59
Q

Within-subjects

A

Each participant is tested on each condition

Within-subjects advantages:
Fewer participants
Less “variation due to participants”
No need to balance groups (because there is only one group!)

60
Q

Between-subjects

A

Each participant is tested on one condition only

Between-subjects disadvantage
More participants (harder to recruit, schedule, etc.)
More “variation due to participants”
Need to balance groups (to ensure they are more or less the same)

61
Q

Validity threats

A

Internal validity threats
* Reasons why inferences (assumption) that the relationship between two variables is causal may be incorrect
External validity
* Reasons why inferences about how study results would hold
over variations in persons, settings, treatments, and outcomes
might be incorrect.

62
Q

What is SURVEYS

A

Any means of asking people for information

63
Q

What are some Survey characteristics

A

With a paper or web-based survey, participants answer the questions on their own
- No chance to clarify or ask follow-ups
- It is hard to know how questions are interpreted
- Once the survey is out it is out

64
Q

In what cases are Surveys used?

A

We use surveys when we need to investigate a clearly defined topic that involves measuring
- Knowledge
- Opinions
- Behaviours
- Perception

65
Q

What are some survey development

A

We need our surveys to have a few important properties
- Relevant to our research questions
- Easy to interpret
- Be interpreted in the same way by all participants

general steps to survey development
- Define variables to measures
- Develop/adapt/find appropriate questions to measure those
- Validate and pilot

66
Q

Variable definition and survey Questions

A

The first step in developing a survey is to define variables. Then, come up with questions to measure those variables. Often we use several questions for the same variable, to capture different aspects of the variable topic
These questions can be:
- Knowledge questions
- Likert scale questions

When developing questions there are some things to consider
- Clarity
- Consistency
- Question order
- Response order

67
Q

Validation and Piloting

A

Validity concerns how well the survey measures what it intends to
measure
Expert review is one typical approach
- Focus on validity
- Ask domain experts about the survey questions (supervisor, peers)
Reliability concerns how consistently it does that
Distribute the survey to a small set of respondents and test how it goes
- Typically adding a comment question
- Focus on reliability (are people answering as expected

68
Q

Survey Sampling

A

Our target group is called population - and we can typically not ask
everyone in that population. Instead, we need to draw a sample.
A sample is a subset of our population which we assume to be
representative of the population at large.

69
Q

Random Sampling

A

Random sample
- We sample at random, and give everyone an equal chance of being selected
- Practically, we could select names at random from a list of everyone in the population
- Gold standard – but expensive and often infeasible

70
Q

Stratified sampling

A

Stratified sampling (a practical approach to random sampling)
- The population is split into sub-population based on criteria such as age, gender….
- A random sample is drawn from each sub-population
- Intends to ensure a greater spread over the population

71
Q

Convenience sampling

A

Convenience sampling
- Aka accidental sampling or opportunity sampling
- Involves recruiting participants “close at hand”
- Includes asking your friends, using social media, etc
- We cannot know how representative the sample is of the target population

72
Q

Purposive sampling

A

Purposive sampling
- Selective sampling where “high-value” respondents are invited to answer
- The idea is to include participants who are likely to generate valuable data
- Useful in some cases, but hard to generalize from the results

73
Q

Bias in Surveys

A

Sampling bias is skewness in results due to improper sampling.

Confirmation bias
- Participants tend to agree rather than disagree with opinions
- Try to avoid opinionated questions
Question order bias
- Question order may impact how participants answer
- Randomize questions to avoid
Survey fatigue bias
- Participants may get fatigued and stop answering properly
- Limit the survey length

74
Q

In Data Analysis researcher may impact the results. True/False?

A

True

75
Q

Traits of Qualitative Data (3)

A
  • Non-numerical information
  • Often textual
  • Focuses on thematic analysis
76
Q

Traits of Quantative Data(3)

A
  • Numerical
  • Best described in numbers
  • Uses statistics as a method
77
Q

What is a confidence interval? (CI)

A

Measure of how confident we are in our results

78
Q

What is a good confidece level?

A

95%

79
Q

What typ of statistics are used to describe data with means, modes, standard deviation and such?

A

Descriptive Statistics

80
Q

What type of statistics asre used to draw conclutions, correlations, hypothesis testing?

A

Infernal Statistics

81
Q

What are the 4 data levels?

A
  • Nominal
  • Ordinal
  • Interval
  • Ratio
82
Q

What type of data is Nominal Data?

A

Categorical data. Ex: Which animal is your favourite?

83
Q

What descriptives does Nominal Data use?

A

Frequencies and percentages

84
Q

What type of data is Ordinal Data?

A

Ordered data with undefined or unequal lengt between steps. Ex: How tasy is vanilla ice cream? - Tasty, - Neutral, - Untasty

85
Q

What descriptives does Ordinal Data use?

A

Frequencies, percetages and median calculation

86
Q

What type of data is Interval and Ratio?

A

Ordered data with equal distance between data points

87
Q

What is the difference between Interval and Ratio data?

A

-Interval: no defined 0
-Ration: defined 0

88
Q

What is Standard Deviation?

A

A measure of how dispersed the data is

89
Q

Inferential Statistics is a good way to use a smaller group to make an assumtion for the population at large? True/False?

A

True

90
Q

What significance level(SI) should Inferential Statistics have?

A

95%

91
Q

What are the 2 main approaches to Inferential Statistics?

A
  • Hypothesis testing
  • Correlation testing
92
Q

What is a null hypotheses?

A

Opposite variable of a hypotheses.

93
Q

What would the null hypothesis be of “Everybody likes ice cream”?

A

“We cannot prove that everybody likes ice cream”

94
Q

What is a Type 1 Error in Statistical Errors?

A

Reject a true null hypothesis (false positive)

95
Q

What is a Type 2 Error in Statistical Errors?

A

Accept a false null hypothesis (false negative)

96
Q

What tests can be used to get the p-value?

A
  • T-test
  • Rank-Sum test
  • Chi2
97
Q

What is linear correlation?

A

Correlation between 2 variables where one variable increses with the other

98
Q

What is p-hacking?

A

-Shotgunning statistical results until something is positive

  • Something will be positive sooner or later
99
Q

What is Thematic Analysis

A

Systematically generating codes and themes from qualitative data

100
Q

What are the 6 steps of Thematic Analysis?

A
  1. Familiarizing with the data
  2. Generating initial codes
  3. Searching for themes
  4. Reviewing themes
  5. Defining and naming themes
  6. Producing report
101
Q

What is an example of a Thematic Analysis?

A

Ex: Inteviews with ice cream manufacurers about how their changes to recepies might change peoples opinions on favourite ice cream flavours.

102
Q

How should an academic writing should be?

A

Clear:
- Easy to understand, impossible to misunderstand
Concise:
- Anything not needed for the task at hand should be omitted
Objective:
- Reflection of the work

103
Q

Academic writing

A

Academic writing has a purpose (contribute to scientific knowledge), specific audience (scientists, academics), tone (unemotional, unbias)

104
Q

What is the structure of academic writing?

A

Introduction
- Introduce the relevant literature
- Problem description
Materials and methods
- Introduce the study system
- What research methods have been used?
- How was the study done?
Results
- Objectively state finds
- Focus on results
Discussion
- Interpret you result
- Tie result back to the literature by answering the knowledge gap
Conclusions and implications

105
Q

Bias in academic writing

A

Bias comes from you and your design, and it can affect the results based on several issues: e.g. chosen sample, investigation method and style of analysis.

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