Data Analysis The main goal of this step is to identify significant attributes of positive deviants The data analysis techniques you use will depend on your study design and whether you have used a qualitative approach a quantitative approach or a mixed methods approach Specific analytical techniques for each approach are outlined below This type of analysis starts with a verbatim transcription of all recorded interviews and focus group materials The transcriptions are then analyzed to identify themes that capture recurring patterns in attributes attitudes practices and strategies of positive deviants You can also bring a quantitative lens to this kind of qualitative data through open and closed coding processes Through these you either use an existing codification of topics and themes or create your own before coding your transcriptions and counting the number of times different themes appear across the two groups of positive deviants and non positive deviants In a mixed methods approach the themes identified are used to develop a survey instrument that is grounded in the views of the participants Its main objective is to validate the qualitative findings uncommon factors that contribute to positive deviance using a large representative sample of the population Qualitative data analysis Thematic analysis Check this resource on how to do a thematic analysis https www interaction design org literature article how to do a thematic analysis of user interviews Dedoose software https www dedoose com The central themes that emerged included the typology of the farm farmer characteristics farm characteristics enablers and barriers of deforestation attitudes towards conservation practices and innovations In this case findings from interviews with positive deviants are presented to a large group of non positive deviants where potential uncommon practices are presented one by one to the entire group Participants are then asked to point out those that are known to them by a show of hands This method is mainly used to uncover the distinguishing practices and behaviors of positive deviants Photo elicitation can also be used here Positive deviance accessibility sieve This study used PD to improve student clinical performance They employed the PD accessibility sieve to identify behaviors that were truly uncommon but replicable Here individual in depth interviews were first conducted with 20 positively deviant students who were asked what they thought were the reasons for their good performance The transcribed responses were then analyzed to list potential behavioral predictors of their outperformance In a large group session with the entire batch of students these behavioral predictors were displayed one by one to the students and they were asked to point out behaviors that were common to many other students by a show of hands A list of behaviors was compiled eliminating those behaviors that were voted to be common for the batch behaviors of seven students were found to be truly novel Accessibility sieve in action In the Ecuador cattle farming project the team conducted a thematic analysis of interviews using the Dedoose software t o identify differences between positively deviant and non positively deviant farms Change in action using positive deviance to improve student clinical performance https link springer com content pdf 10 1007 s10459 011 9301 8 pdf 91 92

Hinweis: Dies ist eine maschinenlesbare No-Flash Ansicht.
Klicken Sie hier um zur Online-Version zu gelangen.