Entry
Reader's guide
Entries A-Z
Action Research
Action research is a strategy for addressing research issues in partnership with local people. Defining characteristics of action research are collaboration, mutual education, and action for change. This approach increases the validity of research by recognizing contextual factors within the research environment that are often overlooked with more structured approaches. Action researchers are sensitive to culture, gender, economic status, ability, and other factors that may influence research partners, results, and research communities.
Ethics is a dominant theme in action research; researchers create an intentional ethical stance that has implications for process, philosophical framework, and evaluation procedures. Ethical principles are usually negotiated at the outset by all partners to identify common values that will guide the research process. These can include consultation throughout the research process, the valuing of various kinds of knowledge, mutual respect, and negotiation of the research questions, methods, dissemination, and follow-on action.
Action research can encompass the entire research project: identification and recruitment of the research team, definition of the research question, selection of data collection methods, analysis and interpretation of data, dissemination of results, evaluation of results and process, and design of follow-on programs, services, or policy changes. Although the degree of collaboration and community involvement varies from one research project to another, action research can be “active” in many ways depending on the needs or wishes of participants. All partners, including community members, play an active role in the research process; the research process itself is a training venue that builds research capacity for all partners; local knowledge and research skills are shared within the team; and the research outcome is a program or policy. Ideally, action research is transformative for all participants.
History
Action research has its roots in the work of Kurt Lewin (1935/1959) and the subsequent discourse in sociology, anthropology, education, and organizational theory; it is also based on the development theories of the 1970s, which assume the equality and complementarity of the knowledge, skills, and experience of all partners. As the human rights movement has challenged traditional scientific research models, new models for collaborative research have emerged. These models have various names: action research, participatory action research (PAR), collaborative research, and emancipatory or empowerment or community-based research, with considerable overlap among them. All models share a commitment to effecting positive social change by expanding the traditional research paradigm to include the voices of those most affected by the research; thus, “research subjects” can become active participants in the research process. Most models include an element of capacity building or training that contributes to the empowerment of the community, the appropriateness of the dissemination process, and the sustainability of action research results.
CASE EXAMPLE: THE CANADIAN TUBERCULOSIS PROJECT
The Canadian Tuberculosis (TB) Project was a 3-year project that addressed the sociocultural factors influencing the prevention and treatment of TB among the most affected people: foreign-born and aboriginal populations. Initiated by a nurse at the TB clinic in the province of Alberta, the need for this research was echoed by leaders within the affected groups. Beginning with the establishment of a community advisory committee (CAC), a set of guiding principles was negotiated. This process contributed to team building and the establishment of trust among the various players, including community, government, and academic partners. The CAC then worked with the administrative staff to recruit two representatives from each of the four aboriginal and six foreign-born communities. These 20 community research associates were trained in action research principles, interview techniques, and qualitative data analysis. They conducted interviews within four groups in each of their communities: those with active TB, those on prophylaxis, those who refused prophylaxis, and those with a more distant family history of TB in their country of origin or on aboriginal reserves. The community research associates, the CAC, and the academic staff then analyzed the interview data using both manual and electronic techniques. The multi method and multi-investigator analysis strategy maximized the validity of the data and the research findings.
...
- Analysis of Variance
- Association and Correlation
- Association
- Association Model
- Asymmetric Measures
- Biserial Correlation
- Canonical Correlation Analysis
- Correlation
- Correspondence Analysis
- Intraclass Correlation
- Multiple Correlation
- Part Correlation
- Partial Correlation
- Pearson's Correlation Coefficient
- Semipartial Correlation
- Simple Correlation (Regression)
- Spearman Correlation Coefficient
- Strength of Association
- Symmetric Measures
- Basic Qualitative Research
- Basic Statistics
- F Ratio
- N(n)
- t-Test
- X¯
- Y Variable
- z-Test
- Alternative Hypothesis
- Average
- Bar Graph
- Bell-Shaped Curve
- Bimodal
- Case
- Causal Modeling
- Cell
- Covariance
- Cumulative Frequency Polygon
- Data
- Dependent Variable
- Dispersion
- Exploratory Data Analysis
- Frequency Distribution
- Histogram
- Hypothesis
- Independent Variable
- Measures of Central Tendency
- Median
- Null Hypothesis
- Pie Chart
- Regression
- Standard Deviation
- Statistic
- Causal Modeling
- DISCOURSE/CONVERSATION ANALYSIS
- Econometrics
- Epistemology
- Ethnography
- Evaluation
- Event History Analysis
- Experimental Design
- Factor Analysis and Related Techniques
- Feminist Methodology
- Generalized Linear Models
- HISTORICAL/COMPARATIVE
- Interviewing in Qualitative Research
- Latent Variable Model
- LIFE HISTORY/BIOGRAPHY
- LOG-LINEAR MODELS (CATEGORICAL DEPENDENT VARIABLES)
- Longitudinal Analysis
- Mathematics and Formal Models
- Measurement Level
- Measurement Testing and Classification
- Multilevel Analysis
- Multiple Regression
- Qualitative Data Analysis
- Sampling in Qualitative Research
- Sampling in Surveys
- Scaling
- Significance Testing
- Simple Regression
- Survey Design
- Time Series
- ARIMA
- Box-Jenkins Modeling
- Cointegration
- Detrending
- Durbin-Watson Statistic
- Error Correction Models
- Forecasting
- Granger Causality
- Interrupted Time-Series Design
- Intervention Analysis
- Lag Structure
- Moving Average
- Periodicity
- Serial Correlation
- Spectral Analysis
- Time-Series Cross-Section (TSCS) Models
- Time-Series Data (Analysis/Design)
- Trend Analysis
Get a 30 day FREE TRIAL
-
Watch videos from a variety of sources bringing classroom topics to life
-
Read modern, diverse business cases
-
Explore hundreds of books and reference titles
Sage Recommends
We found other relevant content for you on other Sage platforms.
Have you created a personal profile? Login or create a profile so that you can save clips, playlists and searches