Dedoose Interface
Codification of Qualitative Data
Integration of Quantitative Data
Interactive Mixed Methods Data Visualization Bubble Chart
Dedoose is a web application for mixed methods research developed by academics from UCLA, with support from the William T. Grant Foundation, and is the successor to EthnoNotes. [1]
Dedoose is an alternative to other qualitative data analysis software, explicitly aimed at facilitating rigorous mixed methods research. It is used by researchers funded by the William T. Grant Foundation, including among those in its Faculty Scholars Program. [2] [3] Dedoose and EthnoNotes have gained recognition for their integration of qualitative and quantitative data analysis methods in combination with interactive data visualizations. [4] The Dedoose family of tools has been used in a wide variety of studies in many industries from medical, [5] market research, [6] social policy research, [7] and other academic social science research [8]
Dedoose is designed, developed, and operated by SocioCultural Research Consultants (SCRC), whose majority of ownership (i.e. 2 people) consists of academics from UCLA. [9]
On May 6, 2014, Dedoose suffered a major system failure, resulting in the corruption and loss of significant amounts of data and service availability problems. All accounts created after March 2 and all data added after March 30 were erased. Data added to the system in March by existing users was restored to Dedoose on May 16. According to SCRC, the system crash involved a failure of its Microsoft Azure cloud services during a database backup. SCRC took full responsibility for the crash and pledged "to do all we can to help rebuild any project if there are tangible ways we can assist." [10] Carl Straumsheim noted that "the Dedoose crash should serve as a warning to colleges and universities as they consider moving sensitive information to the cloud". [11]
Research is "creative and systematic work undertaken to increase the stock of knowledge". It involves the collection, organization, and analysis of evidence to increase understanding of a topic, characterized by a particular attentiveness to controlling sources of bias and error. These activities are characterized by accounting and controlling for biases. A research project may be an expansion of past work in the field. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole.
Marketing research is the systematic gathering, recording, and analysis of qualitative and quantitative data about issues relating to marketing products and services. The goal is to identify and assess how changing elements of the marketing mix impacts customer behavior.
Social statistics is the use of statistical measurement systems to study human behavior in a social environment. This can be accomplished through polling a group of people, evaluating a subset of data obtained about a group of people, or by observation and statistical analysis of a set of data that relates to people and their behaviors.
Multimethodology or multimethod research includes the use of more than one method of data collection or research in a research study or set of related studies. Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies. One could argue that mixed methods research is a special case of multimethod research. Another applicable, but less often used label, for multi or mixed research is methodological pluralism. All of these approaches to professional and academic research emphasize that monomethod research can be improved through the use of multiple data sources, methods, research methodologies, perspectives, standpoints, and paradigms.
Qualitative research is a type of research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or field observations in order to collect data that is rich in detail and context. Qualitative research is often used to explore complex phenomena or to gain insight into people's experiences and perspectives on a particular topic. It is particularly useful when researchers want to understand the meaning that people attach to their experiences or when they want to uncover the underlying reasons for people's behavior. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis. Qualitative research methods have been used in sociology, anthropology, political science, psychology, communication studies, social work, folklore, educational research, information science and software engineering research.
Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.
Educational research refers to the systematic collection and analysis of evidence and data related to the field of education. Research may involve a variety of methods and various aspects of education including student learning, interaction, teaching methods, teacher training, and classroom dynamics.
Content analysis is the study of documents and communication artifacts, which might be texts of various formats, pictures, audio or video. Social scientists use content analysis to examine patterns in communication in a replicable and systematic manner. One of the key advantages of using content analysis to analyse social phenomena is their non-invasive nature, in contrast to simulating social experiences or collecting survey answers.
In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal, like acquiring knowledge or verifying knowledge claims. This normally involves various steps, like choosing a sample, collecting data from this sample, and interpreting the data. The study of methods concerns a detailed description and analysis of these processes. It includes evaluative aspects by comparing different methods. This way, it is assessed what advantages and disadvantages they have and for what research goals they may be used. These descriptions and evaluations depend on philosophical background assumptions. Examples are how to conceptualize the studied phenomena and what constitutes evidence for or against them. When understood in the widest sense, methodology also includes the discussion of these more abstract issues.
Group concept mapping is a structured methodology for organizing the ideas of a group on any topic of interest and representing those ideas visually in a series of interrelated maps. It is a type of integrative mixed method, combining qualitative and quantitative approaches to data collection and analysis. Group concept mapping allows for a collaborative group process with groups of any size, including a broad and diverse array of participants. Since its development in the late 1980s by William M.K. Trochim at Cornell University, it has been applied to various fields and contexts, including community and public health, social work, health care, human services, and biomedical research and evaluation.
Digital humanities (DH) is an area of scholarly activity at the intersection of computing or digital technologies and the disciplines of the humanities. It includes the systematic use of digital resources in the humanities, as well as the analysis of their application. DH can be defined as new ways of doing scholarship that involve collaborative, transdisciplinary, and computationally engaged research, teaching, and publishing. It brings digital tools and methods to the study of the humanities with the recognition that the printed word is no longer the main medium for knowledge production and distribution.
ATLAS.ti is a computer-assisted qualitative data analysis software that facilitates analysis of qualitative data for qualitative research, quantitative research, and mixed methods research.
Computer-assistedqualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, grounded theory methodology, etc.
MAXQDA is a software program designed for computer-assisted qualitative and mixed methods data, text and multimedia analysis in academic, scientific, and business institutions. It is being developed and distributed by VERBI Software based in Berlin, Germany.
QDA Miner is mixed methods and qualitative data analysis software developed by Provalis Research. The program was designed to assist researchers in managing, coding and analyzing qualitative data.
Thematic analysis is one of the most common forms of analysis within qualitative research. It emphasizes identifying, analysing and interpreting patterns of meaning within qualitative data. Thematic analysis is often understood as a method or technique in contrast to most other qualitative analytic approaches – such as grounded theory, discourse analysis, narrative analysis and interpretative phenomenological analysis – which can be described as methodologies or theoretically informed frameworks for research. Thematic analysis is best thought of as an umbrella term for a variety of different approaches, rather than a singular method. Different versions of thematic analysis are underpinned by different philosophical and conceptual assumptions and are divergent in terms of procedure. Leading thematic analysis proponents, psychologists Virginia Braun and Victoria Clarke distinguish between three main types of thematic analysis: coding reliability approaches, code book approaches and reflexive approaches. They describe their own widely used approach first outlined in 2006 in the journal Qualitative Research in Psychology as reflexive thematic analysis. Their 2006 paper has over 120,000 Google Scholar citations and according to Google Scholar is the most cited academic paper published in 2006. The popularity of this paper exemplifies the growing interest in thematic analysis as a distinct method.
Cassandre is a free open source software for computer assisted qualitative data analysis and interpretation in humanities and social sciences. Although it refers, like other CAQDAS-software, to Grounded Theory Method, it also allows to conduct discourse analysis or quantitative content analysis. The software is designed as a server to support collaborative work. Formerly focused on semi-automatic coding, it now provides diaries assisting qualitative analysis.
Quirkos is a CAQDAS software package for the qualitative analysis of text data, commonly used in social science. It provides a graphical interface in which the nodes or themes of analysis are represented by bubbles. It is designed primarily for new and non-academic users of qualitative data, to allow them to quickly learn the basics of qualitative data analysis. Although simpler to use, it lacks some of the features present in other commercial CAQDAS packages such as multimedia support. However, it has been proposed as a useful tool for lay and participant led analysis and is comparatively affordable. It is developed by Edinburgh, UK based Quirkos Software, and was first released in October 2014.
Qualitative research in criminology consists of research in the criminology field that employs qualitative methods. There are many applications of this research, and they can often intersect with quantitative research in criminology in order to create mixed method studies.
Social data science is an interdisciplinary field that addresses social science problems by applying or designing computational and digital methods. As the name implies, Social Data Science is located primarily within the social science, but it relies on technical advances in fields like data science, network science, and computer science. The data in Social Data Science is always about human beings and derives from social phenomena, and it could be structured data or unstructured data. The goal of Social Data Science is to yield new knowledge about social networks, human behavior, cultural ideas and political ideologies. A social data scientist combines cdomain knowledge and specialized theories from the social sciences with programming, statistical and other data analysis skills.