In order to conduct a complete qualitative research and present a cohesive qualitative research plan, it is necessary to match the structure and topic of the study with existing data collection and management techniques. There are specific patterns and models for organizing data that would immediately allow a researcher to gather pertinent information about particular research questions. Given the fact that the qualitative research plan involves two stages of data collection analysis – to gather data abut age, race, and dander characteristics and to conduct interviews for defining the basic reasons why adolescents consume alcohol – it is purposeful to involve observation and interviewing as the basic techniques for obtaining information. During the interviews, it is necessary to capture important quotes from the participants and analyze people’s experiences and perspectives. Importantly, it is imperative for an interviewer to consider specific peculiarities of gender characteristics while analyzing the behavior of adolescents because this age category undergoes constant transformations in psychological terms (Patton, 2002). Social and cultural backgrounds are also important because they influence the process of interpreting data, which slightly differs from the actual data collection procedures because of its naturalistic nature.
According to Creswell (2007), qualitative research analysis can be significantly facilitated when introducing computer software. A researcher, therefore, should make use of existing technological advances to extract as much valuable information as possible (Patton, 2002). Because the collected data is voluminous, specific automated approaches to data sorting out should be introduced. Organizing and establishing the priorities from the least important to the most important information is a very time-consuming task. In this respect, the majority of the collected materials can be processed with the help of computer software packages seeking to highlight the most relevant resources and discuss similar research cases.
Application of automated devices can also significantly contribute to information coding. By combing the data by specific themes, concepts, and ideas, it is possible to single out the patterns that will be further used in the research. Coded information can be represented in the form of terms, phrases, keywords, themes, topics, and ideas that can be drawn from observations and interviews (Gibbs & Taylor, 2005). Video and audio recording can also be used as viable sources for outsourcing (Gibbs & Taylor, 2005). Each coded passage can be used as a specific tool for analyzing further stages of data analysis. For instance, interviews serve for highlighting the information about adolescents consuming alcohol. Once the reasons are highlighted, it is possible to use this data to search for supporting evidence.
While being engaged in data analysis and collection, it is highly important to consider all details of presented information. However, a human eye cannot capture all the nuances and aspects of research. In order to enhance the research and back up scientific findings with evidence, it is purposeful to resort a software package, such as NVivo 9 that offers a wide range of opportunities (QSR International, 2011). First, the program can help researchers organize and analyze gathered information and structure it according to the relevance and importance of emerged themes. Second, the program can efficiently guide a researcher from questions to all possible answers to make sense of the obtained information. Finally, NVivo 9 can extract valuable information from interviews and observations (QSR International, 2011). For instance, while conducting an interview, the program allows a research to highlight the most widely used words during the conversation, which can help define reasons why a specific pattern occurs more regularly than another. Additionally, information visualization is possible by means of charts, statistics, and maps created by the program out of qualitative data. Most importantly, NVivo 9 can help gather information from all possible sources with already given arguments. The program can effectively be applied while coding raw data into more meaningful patterns and passages. For instance, the received qualitative data about the number of people under the age of 12-20 can be further used to apply this information to other people of the defined population. Similar samples can be found in other databases all over the world. With the help NVivo 9, it is possible to find identical studies and compare those with your conclusions (QSR International, 2011). In such a manner, it is possible to bring in a more evaluative character to the research and make it more valid and reliable. Overall, presenting and combining information is important for the studies because it enhances its validity and reliability.
Evaluating and organizing data into meaningful ideas and conclusions is not a challenging task as far as qualitative data analysis is concerned. In this regard, there should be specific method that can help a research to effectively assess the received pieces of information and sort out important concepts, idea, and themes. Using computer software is the best solution for overcoming time boundaries and delivering worthy results at the end of the research. Regarding the qualitative research plan under analysis, it should be stressed that using NVivo 9 can endow the study with all necessary facts and supporting arguments.
References
Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches. Thousand Oaks, CA: Sage Publications, Inc.
Gibbs, G. R., & Taylor, C. (2005). How and What to Code. Web.
Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage Publications, Inc.
QSR International (2011). Products: NVivo. Web.