Michael Quinn Patton

Bio: Michael Quinn Patton is an academic researcher. The author has contributed to research in topic(s): Qualitative research & Constructionism. The author has an hindex of 1, co-authored 1 publication(s) receiving 13418 citation(s).

Qualitative research & evaluation methods

Abstract: This book explains clearly conceptual issues and themes on qualitative research and evaluaton methods including: qualitative data, triangulated inquiry, qualitative inquiry, constructivism, constructionism, Complexity (chaos) theory, qualitative designs and data collection, fieldwork strategies, interviewing, tape-recording, ethical issues, analysis, interpretation and reporting, observations vs. perceived impacts and utilisation-focused evaluation reporting.

Demonstrating Rigor Using Thematic Analysis: A Hybrid Approach of Inductive and Deductive Coding and Theme Development

Abstract: In this article, the authors describe how they used a hybrid process of inductive and deductive thematic analysis to interpret raw data in a doctoral study on the role of performance feedback in the self-assessment of nursing practice. The methodological approach integrated data-driven codes with theory-driven ones based on the tenets of social phenomenology. The authors present a detailed exemplar of the staged process of data coding and identification of themes. This process demonstrates how analysis of the raw data from interview transcripts and organizational documents progressed toward the identification of overarching themes that captured the phenomenon of performance feedback as described by participants in the study.

How to plan and perform a qualitative study using content analysis

Abstract: This paper describes the research process – from planning to presentation, with the emphasis on credibility throughout the whole process – when the methodology of qualitative content analysis is chosen in a qualitative study. The groundwork for the credibility initiates when the planning of the study begins. External and internal resources have to be identified, and the researcher must consider his or her experience of the phenomenon to be studied in order to minimize any bias of his/her own influence. The purpose of content analysis is to organize and elicit meaning from the data collected and to draw realistic conclusions from it. The researcher must choose whether the analysis should be of a broad surface structure ( a manifest analysis ) or of a deep structure ( a latent analysis). Four distinct main stages are described in this paper: the decontextualisation, the recontextualisation, the categorization, and the compilation. This description of qualitative content analysis offers one approach that shows how the general principles of the method can be used.

Designed-Based Research and Technology Enhanced Learning Environments

Abstract: During the past decade, design-based research has demonstrated its potential as a methodology suitable to both research and design of technology-enhanced learning environments (TELEs). In this paper, we define and identify characteristics of design-based research, describe the importance of design-based research for the development of TELEs, propose principles for implementing design-based research with TELEs, and discuss future challenges of using this methodology. (http://www.springerlink.com/content/a582109091287128/)

Design-Based Research and Technology-Enhanced Learning Environments.

Abstract: During the past decade, design-based research has demonstrated its potential as a methodology suitable to both research and design of technology-enhanced learning environments (TELEs). In this paper, we define and identify characteristics of design-based research, describe the importance of design-based research for the development of TELEs, propose principles for implementing design-based research with TELEs, and discuss future challenges of using this methodology.

Does sample size matter in qualitative research?: A review of qualitative interviews in IS research

Abstract: This study examines 83 IS qualitative studies in leading IS journals for the following purposes: (a) identifying the extent to which IS qualitative studies employ best practices of justifying sample size; (b) identifying optimal ranges of interviews for various types of qualitative research; and (c) identifying the extent to which cultural factors (such as journal of publication, number of authors, world region) impact sample size of interviews. Little or no rigor for justifying sample size was shown for virtually all of the IS studies in this dataset. Furthermore, the number of interviews conducted for qualitative studies is correlated with cultural factors, implying the subjective nature of sample size in qualitative IS studies. Recommendations are provided for minimally acceptable practices of justifying sample size of interviews in qualitative IS studies.