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Summary - Scientific Research Methods (INFOARM)

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A complete summary of all theory for the final exam for INFOARM. Includes high quality figures, extra examples and pointers to things that are important for the exam.

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Scientific Research Methods for
MBI
Created @November 11, 2024 3:17 PM

Class INFOARM


Exam
look into learning objectives

30/30/30/10 → theory and choice of methodology, quantitative, qualitative,
research as such

Put effort into qualitative

look at abstract, guess what methods they could have used

adjust SLR part

statistical tests: man wittney, anova, wilkonson, t-test, pairing t-test (see
workshops)

what statistical tests are suitable for different contexts

action research/design sceince



Week 1
As the development of software products is a complex task, the software
process itself becomes very complex.

The complexity of the software process means that it is difficult to optimize it
or even find a good enough process




Scientific Research Methods for MBI 1

, The software process stresses the need for a systematic and disciplined
approach to working.



Empirical studies are crucial to the evaluation of processes and human-based
activities. It is also beneficial to use empirical studies when there is a need to
evaluate the use of software products or tools. Experimentation provides a
systematic, disciplined, quantifiable and controlled way of evaluating human-
based activities

Empirical studies and experiments in particular are also important for
researchers in software engineering

It is crucial to evaluate new inventions and proposals in comparison with
existing ones



In order to perform scientific research in software engineering, we have to
understand the methods that are available to us, their limitations and when they
can be applied.


Research methods for software engineering:

Scientific: The world is observed and a model is built based on the
observation, for example, a simulation model.

Engineering: The current solutions are studied and changes are proposed,
and then evaluated.

Empirical: A model is proposed and evaluated through empirical studies, for
example, case studies or experiments.

Empirical strategies in software engineering include: Setting up formal
experiments, studying real projects in industry, i.e. performing a case
study, and performing surveys through, for example, interviews.

Analytical: A formal theory is proposed and then compared with empirical
observations.




Scientific Research Methods for MBI 2

, The engineering method and the empirical method can be seen as variations of
the scientific method


The main reason to use experimentation in software engineering is to enable
understanding and identification of relationships between different factors, or
variables
Improved understanding is the basis for changing and improving the way we work,
hence empirical studies in general and experimentation in particular are important.


Wieringa Ch1

Design science is the design and investigation of artifacts in context.

Design science iterates over solving design problems and answering
knowledge questions.

The social context of a design science project consists of stakeholders who
may affect or may be affected by the project.

The knowledge context consists of knowledge from natural science, design
science, design specifications, useful facts, practical knowledge, and common
sense.

Generalizations produced by design science research are middle range. They
may abstract from some conditions of practice but do not make unrealizable
idealizations. They generalize beyond the case level but are not universal



Gregor 2006

Type of article: Meta/philosophical

Type or research: argumentative

Research contribution: showing multiple views of theory in information
systems



Research fields of IS:



Scientific Research Methods for MBI 3

, IS 1: accounting IS, based in Business schools, more international/US field →
methods from social sciences

IS 2: Database theory, knowledge based systems, software productions, more
in Europe → methods from computer science



Need for theory in IS:

Theory is essential in Information Systems (IS) to provide a framework for
understanding why phenomena occur, rather than just describing what is
happening.

Without theory, data-driven studies risk becoming purely descriptive, failing to
explain the underlying causes or mechanisms of observed patterns.

Theory enables researchers to connect findings to broader concepts,
fostering deeper insights and enabling causality analysis, which data alone
cannot achieve.

Consequently, IS research that lacks theoretical grounding may lack relevance,
timeliness, and explanatory power.



Characterizing IS: An information system (IS) can be defined technically as a set
of interrelated components that collect, process, store, and distribute information
to support decision making and control in an organization.” (Laudon and Laudon
2014)




Scientific Research Methods for MBI 4

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