Lecture Communication research: Asking questions, finding answers (4e) Chapter 14: Introduction to qualitative research

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Lecture Communication research: Asking questions, finding answers (4e)  Chapter 14: Introduction to qualitative research

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Lecture Communication research: Asking questions, finding answers (4e) Chapter 12: Quantitative analysis oof text. After reading this chapter, you should be able to: Differentiate between manifest and latent content in content analysis, explain the basic processes for conducting a content analysis, identify appropriate uses of interaction analysis, explain the basic processes for conducting a research study using interaction analysis,... Đề tài Hoàn thiện công tác quản trị nhân sự tại Công ty TNHH Mộc Khải Tuyên được nghiên cứu nhằm giúp công ty TNHH Mộc Khải Tuyên làm rõ được thực trạng công tác quản trị nhân sự trong công ty như thế nào từ đó đề ra các giải pháp giúp công ty hoàn thiện công tác quản trị nhân sự tốt hơn trong thời gian tới.

Chapter 14 INTRODUCTION TO QUALITATIVE RESEARCH VAR JUA h n lều hHHCF ap * Preserves the form and content of interaction * Contextually situated * Discourse Is the data * Analyzed for its qualities - empirical, inductive, and interpretive * Aims for subjectivity * Allows interactants’ voices to be heard * Intersubjectivity + The social accomplishment of how people coconstruct and co-experience their social life and rules for doing so * How people understand and interpret communication processes? * How is communication socially situated’? MUTUAL SIMULTANEOUS SHAPING * The here and now * Everything influences everything else * Emphasis on process and the holistic frame of Interaction * Plausible explanations built on what is observed ducfoñ o + cistibuli rt _ the prior written nsent of ~~ MeGr eee one atio INC ANA * From the specific to the general * Explanations and theories emerge from the data * Propositions formulated continuously throughout the data collection and data analysis process AOL - JR ⁄⁄ Purpose ¢ Phenonfenon Interdependent stages Not linear * Cannotbe plannedin — entirety ARCH ¬ QUALITA ae d \ \ f | - Ỷ * Bottom reflects activities in the field —— — / j si of Select data _ ~~collection™ “ing Ƒ ¬ ' ¬ analyse Analysis —— P| \ “S| design of the project ie uestions existing literature N * Top circle reflects ® Reorerch — J ee ee Sm-=_ —Hm=m= Kmmmm Kmm==m Jmmm cm mm 3+FDIE YIN QUA ñ * Extent to which data interpretations are true + correct + dependable * Allows for multiple interpretations by asking “What's plausible?” NAAN \ * Triangulation: use of several kinds of methods or data to enhance credibility + Data triangulation + Investigator triangulation + Interdisciplinary triangulation * Member validation + Taking research findings back to individuals who provided data CONCEPTUALIZING RESEARCH QUESTIONS FOR QUALITATIVE RESEARCH * Based on previous literature * Broadly stated * Nondirectional * Gives researcher latitude in following interesting paths * Specific to the interaction context ASSESSING QUALITATIVE RESEARCH QUESTIONS * Should ask how or what’? * Should reference the research site? | * Focus ona specific type of TR HE * Discover how meaning is developed/shared? * Reveal naturally occurring communication not suitable for Study in an experiment? * Reveal unanticipated ophenomena/influences? * Reveal process that occur over time’? * Explore the influences of the < * Anything that can be observed or captured * Interpreting meaning + Researcher construction + Subjective valuing + Contingent accuracy * Level of evidence + Microlevel, midlevel, macrolevel ADVANTAGES * Documents the unseen * Provides information about those who cannot or will not speak for themselves * Supplements information from quantitative studies LIMITATIONS * Communication environment must be accessible * Interactants may change their behavior * Observations filtered through the researcher * Time consuming THREATS TO CREDIBILITY * Inaccuracy or incompleteness of data * Problems of interpretation + Whose interpretation is being imposed’? * Theoretical validity + What about data that fail to fit the interpretation? * Selection bias * Reactivity bias

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