Disclaimer:
Please be aware that the content herein has not been peer reviewed. It consists of personal reflections, insights, and learnings of the contributor(s). It may not be exhaustive, nor does it aim to be authoritative knowledge.
Overview
Prepared by (Name of the experimenter)
Ecodataton
On date (Day/Month/Year)
12/11/2023
What action learning plan is this activity related to?
The Datatón “Agua – Aire Esperanza de vida” is related to an action learning plan focused on environmental data analysis and policy innovation. The objective is to leverage data on water, air quality, and waste to generate innovative, impactful solutions for improving public awareness and guiding policy-making in La Paz. Participants use multidisciplinary collaboration to develop data-driven tools such as dashboards, maps, and visualizations, contributing to better environmental governance and sustainability efforts
Design
What is the specific learning intent of the activity? Why is it important to do this experiment?
Specific Learning Intent of the Activity:
The activity aims to teach participants how to use environmental data (air, water, and waste) to develop innovative, data-driven solutions that inform public policies and increase environmental awareness. The goal is to improve participants' skills in data analysis, visualization, and collaborative problem-solving.
Why Is It Important?
This experiment is important because it empowers citizens and experts to directly contribute to sustainability efforts by analyzing real-world data, fostering civic engagement, and generating actionable insights for better environmental governance
What is your hypothesis? IF... THEN....
IF participants analyze environmental data (air, water, and waste) and collaborate to create data-driven solutions, THEN they will generate innovative products that raise public awareness and inform better environmental policies, leading to improved sustainability efforts in La Paz.
Does the activity use a control group for comparison?
Yes, a different group entirely
Describe which actions, with whom, where, when will you (or did you) take to test your hypothesis:
Actions to Test the Hypothesis:
Data Analysis and Collaboration:
Participants from multidisciplinary teams will analyze environmental data (air quality, water resources, and waste) provided by the Municipal Secretariat of Environmental Management in La Paz.
Workshops and Training:
Conduct workshops and expert talks to equip participants with the tools needed for data analysis and innovation.
Location and Timeline:
The event will take place at Universidad Católica Boliviana on November 11-12, 2023.
Project Development:
Teams will create data-driven products (dashboards, infographics, maps) and present their solutions, which will be evaluated for policy impact
If you worked with partners, please choose what sector they belong to (select all that apply)
Academia, Government (& related)
What is the total estimated monetary resources needed for this experiment?
Between 1,000 and 9,999 USD
Please upload any supporting images or visuals for this experiment.
Please upload any supporting links
Results
Was the original hypothesis (If.. then) proven or disproven? In which way do the results support the original hypothesis or not?
The original hypothesis was proven. The results showed that participants were able to develop innovative, data-driven projects focusing on solid waste, air quality, and water management for La Paz. These projects contributed to public awareness and offered actionable insights for policy improvement, supporting the hypothesis that collaboration and data analysis would lead to impactful environmental solutions
What are the most important learning outcomes of the experiment? Are any changes recommended?
Most Important Learning Outcomes:
Data-Driven Insights: Participants effectively used environmental data to generate solutions focused on improving solid waste management, air quality, and water resources.
Collaboration: Multidisciplinary teamwork fostered creativity and innovation in addressing environmental challenges.
Public Policy Impact: The projects demonstrated the potential to influence public policy and raise awareness of environmental issues.
Recommended Changes:
Ongoing Support: Provide follow-up mentorship to help teams refine and implement their solutions.
Broader Data Sources: Integrate more diverse environmental datasets for future events.
Considering the outcomes of this experimental activity, which of the following best describe what happened after? (Please select all that apply)
This experiment influenced public policy at a national or local level, This experiment led to adoption of new ways of working by our partners
Please include any supporting images that could be used to showcase this activity
Please add any supporting links that describe the planning, implementation, results of learning of this activity? For example a tweet, a blog, or a report.
https://amun.bo/ganadores-del-concurso-ecodataton-haran-estudios-sobre-residuos-solidos-aire-y-agua-de-la-ciudad-de-la-paz/
Learning
What were the main obstacles and challenges you encountered during this activity? What advise would you give colleagues trying to replicate this experimental activity?
6Clean water and sanitation
11Sustainable cities and communities
13Climate action
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