This is Block 15 (18 ECTS) on the 3+1 Integrated BSc/MSc Immersive Software Engineering and is the first block of the MSc track. It runs in the summer semester Weeks 7 to 15 (9 Weeks) and is classified as 1 3 in SITS. The aim of this module is to enable students to become highly effective research practitioners in the context of software engineering. Students are introduced to the philosophy of research and logic reasoning as a means of contextualising hypothesis formation. It covers the topics of literature review, critical evaluation of research material, the subsequent identification of research questions and the full specification of these questions in the form of a research proposal. Students are then introduced to research methods from both qualitative and quantitative research paradigms within the lifecycle of a research project. Qualitative research methods were originally developed in the social sciences to enable researchers to understand and explain social and cultural phenomena. Increasingly these issues become more important as software becomes more pervasive in modern life. Students will be introduced to the principles and concepts behind statistical research methods and to the appropriate statistical methods for monitoring and controlling quality, analysing designed experiments, accessing reliability, modelling relationships, and data mining tools. This module will give students an understanding of design research, empirical research methods, and the data collection strategies possible, grounding these students in both qualitative and quantitative traditions. The students will develop a critical awareness of the ethical and access issues related to empirical research collaborations, in terms of data collection, data storage and data utilisation. Finally, students will discuss the presentation and dissemination of research, research management, and the role of the supervisor. The module will prepare students to present research findings in scientific journals, critiquing research findings from scientific journals, and responding to criticisms from referees and editors.

1. An introduction to the nature of, and rationale for, research; epistemology, ontology, methodology and axiology; positivist, interpretivist and critical research paradigms; 2. Research philosophies and theories: theoretical and empirical concepts: design science and natural science models; deductive and inductive logic systems; 3. Basic phases of a research project; 4. Overview of Quantitative and Qualitative research and research methods 5. Validity and generalisability; 6. The process of defining and contextualizing a research question; 7. Qualitative research methods (e.g. action research, case studies, ethnography and grounded theory); qualitative modes of analysis e.g. hermeneutics and semiotics. 8. Critical review and evaluation of academic material; 9. Statistical analysis methods: the normal model for chance variation and monitoring quality; analysis of variance: one-way ANOVA, effect size, multiple comparison procedures; Randomised Block Design; Multifactor layouts; Split-plot - designs; Cross-over designs; 2^n factorial designs 10. Advanced statistical methods: logistic regression; cluster analysis, principal component analysis, repeated measures. 11. Principles of designed experiments: randomisation, replication and blocking; sample size. 12. Regression Methods: correlation; simple linear regression; inverse prediction (calibration curves); Multiple Linear Regression; variable selection, model search and model choice. 13. Data Quality: Reliability, inter-class correlation; Method Comparison Studies, limits of agreement. 14. Regulations and the role of the supervisor. 15. Research management including research dissemination skills (oral and written). 16. Research ethics.

On successful completion of this module, students will be able to: - Define, specify and contextualize a legitimate research question. - Review, compare and critically evaluate research material from academic literature. - Consider and select an appropriate research method within a research paradigm, for a specific research scenario. - Determine the validity issues and reliability issues that arise for a selected research method within a specific research scenario. - Mitigate against said validity issues and reliability issues. - Apply qualitative analysis to qualitative data-sets. - Select the appropriate statistical technique for quantitative data sets generated by selected types of empirical studies. - Identify and understand the most appropriate statistical tools for a given research scenario. - Analyse research data using modern statistical software. - Apply best practice with respect to research ethics in empirical design. - Manage the ethical considerations involved in empirical research. - Effectively disseminate research findings. - Reflect critically on the role of the researcher.

On successful completion of this module, students will be able to: - Embrace the attitudes and values held by the scientific community as necessary to further research and discovery. - Conform to and promote a research ethos that is based on best practice . - Critically judge other researchers' empirical research. - Communicate research findings in a technical writing style.

On successful completion of this module, students will be able to:

The block is taught using the problem-based learning, the flipped classroom concept, and blended learning in a state of the art laboratory setting with an emphasis on collaborative practice and technical excellence. Learning and teaching will be research led with a focus on translating theory into practice, innovation and knowledge creation.