Micronarratives

Also known as micro-stories or participatory vignettes, micronarratives are a collection of short stories written by participants.

Related Tools

Audio Surveys

Unpacking significance

Thematic Analysis

Personas

Sensemaking Workshop

Inspiration

Where Most Significant Change involves the collection of stories, to select a single story, micro-narrative generation creates a collection of stories. Viewed as a set, the collection of stories creates a ‘map’ of the broader streams of change within a program. Micronarratives also include a process of ‘self-signification’ or ‘tagging’ by respondents to help understand the significance of stories.

Micronarratives can be supported by a variety of tools and techniques. For example, audio surveys are a useful way to collect generated stories. The use of visuals (physical or digital cards) to elicit responses is also recommended in micro-narrative generation. This allows participants to select the direction of the story they wish to share. Lastly, the analysis method of personas helps give life to the different clusters of responses.

For MEL, micronarratives can be used in three different ways:

  1. Retrospective– single point of time reflecting on the past
  2. Comparative – single point of time comparing different types of people
  3. Longitudinal – multiple points of time comparing different responses from the same people

Micronarratives have four objectives:

  • Encourage participants to reflect on their own lives
  • Start deeper conversations around complex topics
  • Collect GESI-related insights through micronarratives
  • Create a broad map of the streams of change within a program
Step 1. Clarify the objective and modality of using micronarratives

In this first step, facilitators will need to reflect on exactly what they hope to achieve using micronarratives. Some points to think through include:

  • Facilitated or self-administered?
  • Change agents, beneficiaries, or staff?
  • Paper or digital? We recommend digital to speed up the analysis process.
  • Audio, text, or both? We recommend both to increase the inclusivity.
  • Thematic or verb-based? We recommend verb-based prompts to create a strong diversity of personal narratives. Thematic narratives tend to only focus on women’s experiences.

 

Step 2. Prepare the prompt and signifying questions

Based on the decisions in the first step, create a system to collect the generated micronarratives.

  1. Formulate the prompt questions. Balancing simplicity and specificity, adapt the question prompt to elicit micro-narratives.
  2. Clarify the self-signification questions. We recommend using an adaptation of the VOICE framework as shown in the example template.
  3. Review distress protocols. As story collection can be quite personal, it is important that teams are prepared to support distress.
Step 3. Conduct micronarrative generation

Based on the decisions in the first step, collect the generated micronarratives. Provide technical support and coaching as required. Follow ethical procedures and ensure anonymity in responses.

Step 4. Data analysis, sensemaking and sharing

The final step is to analyse the micro-narratives. Remember that micro-narratives are intended to be viewed as a set of stories that represent the whole.

  • Compile stories. Transcribe audio responses and translate if required. If stories are collected in smaller components, compile them together into a single string of text.
  • Analyse self-signification responses. Using basic statistics, create a summary of the types of micro-narratives collected.
  • Create personas. Using either thematic analysis or machine learning approaches create clusters of stories, to create personas. For thematic analysis code the ‘verbs’ used in stories to help quickly create clusters. You may need to remove incomplete stories from the sample.
  • Sensemaking workshop. In a workshop setting, explore the data with a group of key stakeholders.
Travel Restricted Times

Micro-narrative generation can be done in both face-to-face and remote modalities. Keeping in mind differences in access and literacy, think about different ways to facilitate and plan the activity.

Computer and internet access

  • Encourage participants to share micro-narratives through an online survey (Mentimeter, Phonic, Google or Microsoft Forms, Kobo, Airtable)

Smartphone and internet access

  • Encourage participants to share micro-narratives through an online survey (Mentimeter, Phonic, Google or Microsoft Forms, Kobo, Airtable)

Basic phone access

  • Collect micro-narratives over the phone as an interview.

Learn more on the digital tools page.

Materials and Resources

Story collection template

This word template, includes consent and story collection format that can be adapted to paper or digital micro-narrative generation.

 
download

DOCX | 2 MB

Prompt design template

This template includes includes sentence starters and ideas to help you create a prompt for your micronarrative approach.

 
DOWNLOAD

PDF | 136 KB

Sample Participant Information Sheet

This information sheet is to be shared with participants prior to story collection. The template should be updated and translated as required.

download

DOCX | 976 KB

Planning Template

GOOGLE DOC

Logistics Checklist

DOCX | 972 KB

Do-no-harm Strategy

DOCX | 982 KB

Integrity Checklist

DOCX | 970 KB

Effective Interviewing Guide

DOCX | 968 KB

Learn more

MacArthur, J., Carrard, N., Kozole, T., & Willetts, J. (2022). Eliciting stories of gender- transformative change: Investigating the effectiveness of question prompt formulations in qualitative gender assessments. Evaluation, 28(3), 308–329. https://doi.org/10.1177/13563890221105537

Snowden, D. (1999). Story telling: An old skill in a new context. Business Information Review, 16(1), 30–37. https://doi.org/10.1177/0266382994237045

Van der Merwe, S. E., Biggs, R., Preiser, R., Cunningham, C., Snowden, D. J., O’Brien, K., Jenal, M., Vosloo, M., Blignaut, S., & Goh, Z. (2019). Making sense of complexity: Using SenseMaker as a research tool. Systems, 7(2), 25. https://doi.org/10.3390/systems7020025

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