Selecting the Research Method

As a student, it is important to choose an appropriate research method that suits solving the problem at hand. Please look at the links below (most are accessible from within the university network) and discuss with your supervisor which is the best approach. Note that you do not need to write lengthy chapters about the method, it is just necessary to clearly state what the method you use is and how your approach is adjusted to the appropriate method.

Scientific Evaluation

by Roel Wieringa, Hans Heerkens and Björn Regnell.

"Scientific evaluation papers investigate existing problem situations or validate proposed solutions with scientific means, such as by experiment or case study. There is a growing amount of literature about how to report about empirical research in software engineering, but there is still some confusion about the difference between a scientific evaluation paper and other kinds of research papers. This is related to lack of clarity about the relation between empirical research, engineering, and industrial practice. In this minitutorial we give a brief rundown on how to structure a scientific evaluation papers as a special kind of research paper, using experiment reports and case study reports as examples. We give checklists of items that a reader should be able to find in these papers, and sketch the dilemmas that writers and readers of these papers face when applying these checklists"

A design science research methodology and its application to accounting information systems research

by Guido L.Geerts

"Natural science research follows a stereotypical pattern and such uniformity makes it easier to recognize and evaluate the results of such research. A similar format has been lacking for design science research. This issue was addressed by Peffers et al. (2008) who defined such a template for design science research for information systems: the design science research methodology (DSRM). In this paper, we first discuss design science research and the DSRM. Then, we illustrate the application of the DSRM to AIS research through retroactive analysis. Finally, we integrate the DSRM into the operational specification of artifact networks and use the REA literature for illustration purposes"

The above paper gives a nice overview of how design science research method is applied to concrete information systems. This may be easier to read than the classic references

Design Science Research in Information Systems by A. Hevner and S. Chatterjee, and A Design Science Research Methodology for Information Systems Research by Ken Peffers, Tuure Tuunanen, Marcus A. Rothenberger and Samir Chatterjee.

Selecting Empirical Methods for Software Engineering Research

by Steve Easterbrook, Janice Singer, Margaret-Anne Storey and Daniela Damian.

"Selecting a research method for empirical software engineering research is problematic because the benefits and challenges to using each method are not yet well catalogued. Therefore, this chapter describes a number of empirical methods available. It examines the goals of each and analyzes the types of questions each best addresses. Theoretical stances behind the methods, practical considerations in the application of the methods and data collection are also briefly reviewed. Taken together, this information provides a suitable basis for both understanding and selecting from the variety of methods applicable to empirical software engineering."

Statistical Methods

Meaningfully designed statistical analysis is at the core of many theses. Please discuss the choice of appropriate methods with your supervisor. A very nice overview of how statistical methods have evolved during the computer age is given in Computer Age Statistical Inference by Bradley Efron and Trevor Hastie.

R3: repeatability, reproducibility and rigor

by Jan Vitek and Tomas Kalibera.

"Computer systems research spans sub-disciplines that in- clude embedded systems, programming languages and com- pilers, networking, and operating systems. Our contention is that a number of structural factors inhibit quality systems research. We highlight some of the factors we have encoun- tered in our own work and observed in published papers and propose solutions that could both increase the productivity of researchers and the quality of their output."