SayPro – A/B Testing for Behaviour Assessments
Purpose
To systematically evaluate how different versions of a training module, assessment method, or environmental variable affect participant behaviour or learning outcomes. A/B testing allows SayPro to make data-driven decisions about the effectiveness of behavioural interventions or training strategies.
Step-by-Step Process
🔹 1. Define the Objective
Clearly outline what behaviour or outcome you want to test. Examples:
- Increase in focus or completion rate during online modules.
- Improvement in ethical decision-making.
- Preference or retention of content in different formats (e.g., video vs text).
🔹 2. Identify the Variables
- Version A (Control): The standard or current version.
- Version B (Variation): The modified version you’re testing.
Example:
- A = Traditional slide-based training
- B = Interactive video-based training
🔹 3. Select the Assessment Criteria
Use observable and measurable behaviours such as:
- Time spent on task
- Completion rates
- Scores on post-assessments
- Self-reported engagement
- Ethical reasoning choices in scenarios
🔹 4. Randomly Assign Participants
Divide your participants randomly into two groups to eliminate selection bias:
- Group A: Receives the control condition.
- Group B: Receives the experimental condition.
Ensure the groups are similar in terms of demographics, baseline skill, or any other relevant variable.
🔹 5. Conduct the Behavioural Assessment
Have both groups complete the assigned versions under similar conditions (duration, tools, facilitation, etc.).
Use observation, system logs, or self-assessment tools to gather behavioural data.
🔹 6. Analyze the Results
Compare results between A and B using:
- Descriptive statistics (mean, median, % change)
- Inferential tests (e.g., t-tests, chi-square) to assess if differences are statistically significant
- Qualitative feedback (if applicable)
🔹 7. Report Findings
Document:
- Which version performed better and why
- Recommendations for scaling or adjusting the more effective approach
- Limitations or confounding variables observed during testing
Example Scenario
Objective: Test whether adding motivational prompts increases module completion.
- Group A: Sees standard training module.
- Group B: Sees training module + motivational prompts every 10 minutes.
- Measured behaviour: % of participants who complete the module.
Outcome:
- A = 68% completion
- B = 85% completion
→ Conclusion: Prompts are effective.
✅ Benefits of SayPro’s A/B Behaviour Testing
- Drives evidence-based improvements to training.
- Enhances learner outcomes by testing what works.
- Allows for iterative development of behavioural interventions.
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