Use when conducting participatory action research (PAR) involving collaborative inquiry, cycles of action and reflection.
Action research (AR) links inquiry and action in iterative cycles. Stakeholders examine practices, implement changes, and reflect on outcomes. Participatory action research (PAR) foregrounds collaboration, power-sharing, and often social justice, positioning community or practitioner co-researchers as knowledge producers.
While models differ in labeling, a robust cycle includes:
Cycles are spiraling, not one-off: each turn refines questions and practice.
Emphasizes democratic participation, local knowledge, and structural critique. Common in community health, education, and international development when done ethically and non-extractively.
Partnership between researchers and communities across all phases—agenda setting, design, analysis, dissemination. Governance and benefit-sharing are explicit.
Teachers or clinicians study their own practice for local improvement and professional learning. Often smaller scale; still requires rigor and ethical clarity.
Builds change from strengths and positive exemplars rather than deficit framing. Uses discovery, dream, design, destiny phases in organizational contexts.
Facilitators may be insiders (employees, members) or outsiders (academic partners). Critical issues:
Reflexive journaling, transparent agreements, and rotating facilitation can reduce extractive dynamics.
Traditional positivist criteria fit poorly. Common alternatives include:
Combine these with ethical validity (do no harm, consent, privacy) and ecological validity (fits real-world constraints).
Kemmis, McTaggart, and Nixon emphasize participatory and public qualities of AR. Cycles are not merely technical but social practices that can be:
They stress communicative space where arguments are tested and practice architectures (material, social, cultural-discursive arrangements) are transformed.
AR can challenge IRB templates designed for fixed protocols. Use amendment-friendly designs, document evolving consent, and clarify risks when studying workplace power or community conflict.
Use AR when change and knowledge must advance together, stakeholders can sustain cycles, and contextual adaptation matters more than controlled experimentation.
Use traditional experiments when randomization and treatment fidelity are paramount and participatory control is inappropriate.
Use grounded theory when the primary output is substantive theory rather than intervention cycles—though GT can inform AR data analysis.
Use this skill for PAR design, cycle planning, validity arguments, or Kemmis-style participatory framing.