Metodologi Penelitian Sistem Informasi
Summary
TLDRThis video script presents an in-depth explanation of research methodology in Information Systems, using the 'onion model' to describe the layers of research design. The discussion covers key concepts such as ontology, epistemology, and research approaches like deductive, inductive, and abductive reasoning. The script delves into the differences between quantitative and qualitative methods, as well as mixed methods. It also highlights the importance of Design Science Research (DSR) in creating practical solutions for real-world problems. With a focus on how philosophical beliefs influence research choices, this guide is valuable for anyone conducting research in Information Systems.
Takeaways
- 😀 Ontology refers to the nature of reality, focusing on whether reality is independent of human perception (realism) or shaped by it (relativism).
- 😀 Epistemology addresses how we can acquire knowledge, with different approaches including positivism (objective measurement) and interpretivism (subjective understanding).
- 😀 Realism/Objectivism suggests that truth is universal and can be measured objectively, regardless of the researcher’s involvement or context.
- 😀 Relativism/Constructivism emphasizes that truth is context-dependent and shaped by human experience, and it acknowledges multiple valid perspectives.
- 😀 Positivism asserts that knowledge can be obtained through empirical observation, maintaining a clear separation between the researcher and the subject.
- 😀 Interpretivism advocates for an immersive approach, where the researcher engages deeply with the study context to understand human behaviors and social phenomena.
- 😀 Post-positivism combines elements of positivism and relativism, acknowledging that while truth exists, human limitations mean it can never be fully known.
- 😀 Pragmatism is a practical approach to research, focusing on the outcomes and solutions, and often combining methods to address specific research questions.
- 😀 Research methods can be quantitative (numeric, empirical), qualitative (descriptive, interpretive), or a mix of both, depending on the research goals.
- 😀 The deductive approach starts with a theory and tests it, while the inductive approach builds theories from observed patterns or data.
- 😀 Design Science Research (DSR) focuses on creating and evaluating solutions (artifacts) to real-world problems, with iterative cycles of development and testing.
Q & A
What is the significance of ontology in research methodology?
-Ontology in research methodology concerns the nature of reality or truth. It addresses whether reality is objective and independent (realism) or context-dependent and subjective (relativism). The choice of ontology influences how researchers view and approach the phenomena they are studying.
How does epistemology influence research methodology?
-Epistemology pertains to how knowledge is obtained and understood. It shapes the research methodology by determining whether knowledge is objective (positivism), subjective (interpretivism), or a combination of both (post-positivism). Researchers’ epistemological stance will influence their choice of data collection methods and analysis techniques.
What is the difference between deductive, inductive, and abductive research approaches?
-The deductive approach starts with a general theory and tests it through empirical data. The inductive approach, on the other hand, begins with specific observations and builds broader theories. Abductive research combines both approaches, where theory and data are iteratively developed and refined to explain a phenomenon.
What is the main characteristic of quantitative research methods?
-Quantitative research methods focus on numerical data and statistical analysis. They are typically used to test hypotheses or theories through experiments, surveys, or other methods that produce measurable, objective results.
How does qualitative research differ from quantitative research?
-Qualitative research focuses on understanding phenomena through non-numerical data, such as interviews or ethnography. It emphasizes depth of understanding and context, rather than generalization or measurement, which is the hallmark of quantitative research.
What is the role of mixed methods research?
-Mixed methods research combines both qualitative and quantitative approaches. It is used when researchers want to validate or deepen their understanding of a phenomenon by using different types of data. For instance, qualitative data might be collected first to explore a concept, followed by quantitative data to test the findings.
What is the difference between cross-sectional and longitudinal data collection?
-Cross-sectional data collection involves gathering data at a single point in time, providing a snapshot of the situation. Longitudinal data collection, on the other hand, tracks changes over time, providing insights into trends or developments.
How does realism in ontology influence a researcher’s approach?
-Researchers who adopt realism believe that reality exists independently of human perception and can be objectively studied. This ontological stance often leads to the use of deductive reasoning and quantitative methods, where data is analyzed to identify universal truths.
What is the significance of interpretivism in epistemology for social science research?
-Interpretivism posits that knowledge is subjective and context-dependent, especially in social sciences. It emphasizes understanding human experiences and meanings through immersive methods like interviews and ethnography, where the researcher interacts directly with the subjects.
What is Design Science Research (DSR) and how is it applied in information systems?
-Design Science Research (DSR) in information systems focuses on creating and evaluating artifacts (such as models, systems, or processes) that solve real-world problems. It involves iterative cycles of designing, testing, and refining these artifacts to meet specific needs, often addressing challenges in areas like business process optimization or system design.
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