action-research-guide
Design and conduct action research and participatory studies
Best use case
action-research-guide is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Design and conduct action research and participatory studies
Teams using action-research-guide should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/action-research-guide/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How action-research-guide Compares
| Feature / Agent | action-research-guide | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Design and conduct action research and participatory studies
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Action Research Guide
A skill for designing and conducting action research (AR), participatory action research (PAR), and community-based participatory research (CBPR). Covers the cyclical AR process, stakeholder engagement, data collection within action cycles, and balancing rigor with practical impact.
## What Is Action Research?
### Defining Characteristics
```
Action research is research conducted WITH and FOR participants,
not ON them. It aims to produce both practical improvements and
new knowledge simultaneously.
Key principles:
1. Collaboration: Researchers and participants work as partners
2. Cyclical process: Plan -> Act -> Observe -> Reflect -> Repeat
3. Practical focus: Solving a real problem in a real setting
4. Democratic: Participants have voice in research design
5. Reflexive: Ongoing critical reflection on the process
Contrast with traditional research:
Traditional: Researcher studies participants at arm's length
Action research: Researcher and participants co-investigate
```
### Types of Action Research
| Type | Focus | Who Leads |
|------|-------|----------|
| Practical AR | Improving professional practice | Practitioner-researcher |
| Participatory AR (PAR) | Empowerment and social change | Community members + researcher |
| CBPR | Health equity and community needs | Community-academic partnership |
| Educational AR | Improving teaching and learning | Teachers |
| Organizational AR | Improving organizational processes | Internal change agents |
## The Action Research Cycle
### Plan-Act-Observe-Reflect
```python
def action_research_cycle(cycle_number: int,
problem: str,
planned_action: str) -> dict:
"""
Structure one cycle of action research.
Args:
cycle_number: Which iteration of the cycle (1, 2, 3...)
problem: The problem or question being addressed
planned_action: The intervention or change being implemented
"""
cycle = {
"cycle": cycle_number,
"problem_definition": problem,
"phases": {
"plan": {
"activities": [
"Collaboratively define the problem with stakeholders",
"Review evidence and prior knowledge",
"Design the intervention or action step",
"Determine data collection methods",
"Establish success criteria"
],
"planned_action": planned_action
},
"act": {
"activities": [
"Implement the planned action",
"Document the implementation process",
"Note deviations from the plan and why they occurred",
"Maintain a reflective journal"
]
},
"observe": {
"activities": [
"Collect data during and after the action",
"Gather participant feedback",
"Record outcomes (intended and unintended)",
"Compile evidence of change or no change"
],
"data_sources": [
"Observations and field notes",
"Interviews with participants",
"Surveys or questionnaires",
"Artifacts (documents, records, student work)",
"Quantitative measures (if applicable)"
]
},
"reflect": {
"activities": [
"Analyze collected data",
"Discuss findings with stakeholders",
"Identify what worked and what did not",
"Determine modifications for the next cycle",
"Document lessons learned"
]
}
},
"next_cycle": (
"Revise the plan based on reflections and begin the next cycle. "
"Each cycle should show progressive refinement of the intervention."
)
}
return cycle
```
## Stakeholder Engagement
### Building Genuine Partnerships
```
Spectrum of Participation (from low to high):
Inform: One-way communication to participants
Consult: Gather input, researcher makes decisions
Involve: Participants contribute to some decisions
Collaborate: Shared decision-making throughout
Empower: Participants lead, researcher supports
True action research operates at the Collaborate or Empower level.
Strategies for genuine engagement:
- Hold meetings at times and locations convenient for participants
- Use accessible language (avoid academic jargon)
- Share data and findings openly with all partners
- Negotiate authorship and credit transparently
- Build relationships before starting the research
- Compensate participants for their time and expertise
```
## Data Collection in Action Research
### Mixed Methods Within Cycles
```
Qualitative data:
- Reflective journals (researcher and participants)
- Focus groups after each action cycle
- Semi-structured interviews with key stakeholders
- Photographs and video documentation
- Meeting minutes and decision logs
Quantitative data:
- Pre/post surveys measuring target outcomes
- Performance metrics (test scores, health indicators)
- Process metrics (attendance, participation rates)
- Time series data across multiple cycles
Integration:
- Use quantitative data to measure change
- Use qualitative data to understand WHY change did or did not occur
- Triangulate across sources for credibility
```
## Ensuring Rigor
### Quality Criteria for Action Research
| Criterion | Strategy |
|-----------|---------|
| Outcome validity | Did the action solve the problem? |
| Process validity | Were methods adequate and appropriate? |
| Democratic validity | Were all stakeholders' perspectives included? |
| Catalytic validity | Did the research energize participants to act? |
| Dialogic validity | Has the work been peer-reviewed or scrutinized? |
### Common Critiques and Responses
```
Critique: "It is not generalizable."
Response: Action research produces transferable insights, not
statistical generalizations. Thick description allows
readers to judge applicability to their own context.
Critique: "The researcher is biased (they are part of the setting)."
Response: AR is transparent about the researcher's positionality.
Reflexive journaling, peer debriefing, and member checking
mitigate bias. Insider knowledge is a strength, not a flaw.
Critique: "It is just practice improvement, not real research."
Response: AR produces systematic, evidence-based knowledge that is
publicly shared and peer-reviewed. The dual focus on action
and research is by design, not a limitation.
```
## Reporting Action Research
Follow the ARCS (Action Research Cycle Reporting Standards) or use the general structure: describe the context and problem, explain the partnership and roles, present each cycle (plan-act-observe-reflect) chronologically, show how the intervention evolved across cycles, report both practical outcomes and theoretical contributions, and reflect on limitations and what you would do differently.Related Skills
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