Leveraging Micronesian Intelligence for Data Science Using Culturally Relevant Data

Richard Velasco, Ph.D.

Presentation Objective

Provide an update and some preliminary findings on current 2-year grant project currently about to start its second year.

YouCubed

https://www.youcubed.org/data-science-lessons/

Defining Data Science and

Culturally Relevant Data

According to the U.S. Census Bureau, data science is a field of study that uses scientific methods, processes, and systems to extract knowledge and insights from data.

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Culturally relevant data are structured datasets or entities that contain variables and statistics that are relevant to and considered in relation to 1) a concern that is relevant to students based on their communities or cultures they identify with or 2) an issue of social justice that impacts a student's community or culture. (Weiland & Williams, 2023, p. 7)

Social Justice Mathematics and Indigenous Value Framework

• Centers Indigenous knowledge and lived experiences
• Integrates cultural perspectives into data science education
• Guided by the CHamoru value of inafa’maolek (restore harmony, reciprocity)
• Modules address sociopolitical issues: militarization, food insecurity, land use, language loss, etc.

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Sample Teacher Lessons

Sample Teacher Lessons

CODAP - https://codap.concord.org/

Study 1: Youth & Language Preservation

• Participants: 22 high school students (Guam & Saipan)
• Activity: Collected 24-hour data on CHamoru language use
• Created personal data visualizations

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Key Findings – Study 1

• Generational language loss surfaced through data, “especially for the younger generation.”
• Self-reflection of ethnic identity - “it made me think about my own culture and how much I don’t speak my language either.”
• Visualizations relevant to student, not necessarily culture itself (flowers, coconut trees, meals)

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Samples of Students’ Visualizations

More Samples

Study 2: Teacher Narrative – Ana

• Veteran CHamoru math teacher in Saipan
• Co-developed lessons with political scientists
• Adapted YouCubed curriculum to local sociopolitical issues
• Focus: How culturally relevant data informed her sociopolitical consciousness

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Methods – Study 2

• Narrative inquiry with one teacher (Ana)
• Data: Interviews, reflections, planning documents
• Timeline: Aug 2024 – June 2025
• Analysis: Narrative themes of identity & pedagogy

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Key Findings – Study 2

• Ana rooted teaching in her CHamoru identity - “This work is very important to me because I am CHamoru and this is my culture”
• Shift from conventional graphs to creative visualizations - “I feel like doing this activity with the students also helped me to expand the way I want to visualize data.”
• Lessons opened dialogue on colonization, language loss, environmental change - “We never talked about these things in class before.”
• Students engaged across cultures, showing empathy & awareness

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Scholarly Significance

• Shows potential of culturally relevant data science
• Connect data to cultural identity
• Develops sociopolitical consciousness through local data
• Contributes to reimagining math education for equity & cultural futurity

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Challenges Expressed by Teachers

1. Timing of integration of content within typical math curriculum
2. Access to large data sets specific to the Marianas
3. More PD needed, not just in terms of data science content, but also sociopolitical issues pertinent to the islands, and getting students interested in them.

Opportunities Expressed by Teachers

• Students were more engaged in discussions in math class because content was connected to real life contexts.
• Students were faster in picking up technology than they were so it was a collective learning experience.
• Students learned more about sociopolitical issues.

Conclusion

• Data science (and mathematics) can be culturally sustaining
• Projects like MINDS affirm Indigenous knowledge
• Education as both academic and sociopolitical work

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Next Steps for Year 2

1. Continue to adapt remaining YouCubed data science units.
2. Integrate all units after revising current ones from last year.
3. Apply for more grants to continue and expand project.

Long term goals

1. Local data Science Clubs in Guåhan and CNMI (Saipan)
2. Scaling and sustaining this work in Pacific contexts
3. Expand partnerships (e.g. Pacific Community)

What questions do you have for me? :)

Si Yu'us Ma'åse

and

Vinaka Vaka Levu!