L5, L6, L9, L1 Flashcards
What is Action research (AR)
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
What is Technical action research (TAR)
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
Contrasting TAR with AR in information system
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
What is hermeneutics?
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.
What is an experminet?
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.
Experiments. When and why?
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?)
Challenges of conducting
experiments
Choice of experimental design
Interpretation of the results
Statistics
Identifying and tackling validity threats
What is a cause?
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
Causality
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.
Effect – what is an effect?
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).
What is a causal relationship?
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
Correlation does not imply causation
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.
INDEPENDENT VARIABLE
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.
DEPENDENT VARIABLE
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.
Hypotheses
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.”
Randomization
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)
Simulations
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.
Key aspects of simulations
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.
Confounding variable
A variable that is not controlled but can affect the dependent
variable.
Control Variable
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)
