inf st december Credibility: reliability and validity in qualitative research inf5220

inf st december Credibility: criteria for evaluation (page 222 of Silvermann, table 8.1) 1.Are the methods of research appropriate to the nature of the questions being asked? 2.Is the connection to an existing body of knowledge or thoery clear? 3.Are there clear accounts of the criteria used for the selection of cases for study and of the data collection and analysis? 4.Does the sensitivty of the methods match the needs of the research questions? 5.Was the data collection and record keeping systematic? 6.Is reference made to accepted procedure for analysis? 7.How systemtic is the analysis? 8.Is there adequate discussions of how themes, concepts and categories were derived from the data? 9.Is there adequae discussion of the evidence for and against the researcher’s arguments? 10.Is a clear distinction made between the data and its interpretation?

inf st december Reliability 1 Dependability and Reliability The traditional quantitative view of reliability is based on the assumption of replicability or repeatability. reliability The idea of dependability, on the other hand, emphasizes the need for the researcher to account for the ever-changing context within which research occurs. The research is responsible for describing the changes that occur in the setting and how these changes affected the way the research approached the study.

inf st december Reliability 2 Importance of making explicit aspects as:  Role of researcher  Informant selection  Description of Social Context  Data collection strategies  Data analysis strategies  Analytical premises Imp of documenting

inf st december Validity 1 Quantitative research:  internal validity refers to the extent to which the findings accurately describe reality  external validity refers to the ability to generalize findings across different settings qualitative research  Internal validity: data triangulation  External validity: generalization

inf st december Validity 2 Triangulation:  Compare different kinds of data  Compare different methods Respondent validation Silvermann:  Constant comparative method  Deviant-case analysis  Analytic induction  Comprehensive data treatment  Using appropriate tabulations

inf st december Generalizability (walsham) Walsham, G. (2002) Interpretive Case Studies in IS research: Nature and Method, in Myers and Avison Qualitative Reaserch in Information Systems. G: explanations of particular phenomena derived from empirical interpretative research in specific settings which may be vaulabe in the future in other organizations and contexts. Development of concepts Generation of theory Drawing of specific implications in particular domains Contribution of reach insight

inf st december Resources and references to Qualitative Research in Information Systems: