Project

Project Evolve

Report by:

Aninakwah Vera Yeboah

August 1, 2025

Citation

Quansah, S., Asante, V., Yeboah, V. A., & Nsiah, N. A. A. (2023)

Topics

climateEducation, LDIT, STEAM Learning

Building Climate Action Skills in K–12 Learners Through Climate Education

Abstract

Background

The Climate Change Learning Module was implemented in Cape Coast, Ghana, engaging 33 children aged 7–15 from 34 communities through a STEAM (Science, Technology, Engineering, Arts, and Mathematics) education initiative.

Objective

The initiative aimed to equip learners with skills in coding, physical computing, and problem-solving while empowering them to design community-centered solutions aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 13: Climate Action.

Methods

Using a constructionist and culturally responsive approach, the program delivered 26 hybrid sessions, combining virtual learning (Fridays) and in-person workshops (Saturdays). Learners engaged in hands-on projects involving computational thinking, coding, Internet of Things (IoT), and micro:bit programming.

Results

Surveys revealed that 90% of learners reported increased confidence in developing innovative climate solutions, shifting from passive learning to active engagement. Learners successfully applied STEAM concepts to local climate challenges such as heatwaves, energy access, and resource monitoring.

Conclusion

This hybrid, learner-centered model effectively fostered creativity, collaboration, and critical thinking. The program underscores the transformative potential of equitable STEAM education in nurturing socially conscious changemakers capable of addressing climate issues in underserved communities.

1.0 Introduction

The Climate Change Module, developed as part of the Micro:bit Do Your :bit Challenge, empowered K–12 learners to tackle local climate-related issues through interdisciplinary STEAM practices. Grounded in the development of 21st-century skills (Trilling & Fadel, 2009), the module emphasized creativity, collaboration, technological fluency, and problem-solving.

Anchored in the Sustainable Development Goals (SDGs), the initiative challenged learners to design and prototype solutions that address carbon emissions and climate-related natural disasters. Informed by constructionist learning theory (Papert, 1980; Kafai, 1995), the curriculum integrated coding, physical computing, and design thinking to support learner agency, innovation, and real-world impact.

A spiral learning approach (Bruner, 1960) guided the curriculum, gradually building learners’ competencies in electronics, sustainability, and computational thinking. This cyclical structure reinforced deep learning and applied understanding.

2.0 Method

2.1 Participants

The program engaged 33 K–12 learners (60% male, 39% female) from 34 communities in Cape Coast.

2.2 Mode of Delivery

To ensure equitable access in low-resource contexts, the program adopted a hybrid delivery model:

Video Tutorials:
Supported self-paced, flipped classroom learning.
Virtual Live Sessions:
Enabled real-time collaboration and problem-solving.
In-Person Workshops:
Provided hands-on access to tools and peer learning.

Grounded in Universal Design for Learning (UDL) principles (CAST, 2018), the model ensured multiple pathways for learner engagement, addressing diverse needs and learning styles.

3.0 Results

3.1 Learning Outcomes

Aligned with Bloom’s Taxonomy (Anderson & Krathwohl, 2001), learners:

Understood climate change impacts and sustainability strategies
Explored climate technologies such as IoT and physical computing
Applied computational thinking (Wing, 2006) to prototype climate solutions
Designed functional tools aligned with SDGs (e.g., early warning systems, clean energy devices)

3.2 Application of STEAM to Real-World Climate Challenges

Notable Projects Included:

Scratch – Heatwave Early Warning (SDG 13): Learners (ages 7–9) used Scratch to create an interactive simulation mimicking a heatwave early warning system, applying technology (visual coding), science (temperature dynamics), and arts (storytelling visuals). This aimed to raise community awareness about heatwave risks, reducing health impacts through timely alerts.
Heatwave Early Warning System (SDG 13): Learners (ages 10+, beginners) programmed micro:bits with DHT11 sensors to monitor temperature and signal alerts via LEDs, using technology (micro:bit), science (climate monitoring), and engineering (sensor integration). This prototype aimed to mitigate the effect of heatwave, enhancing community resilience.
Drought Early Warning System (SDG 13): Learners (ages 10+, beginners) built a micro:bit-based simulation to alert communities about low rainfall, using technology (micro:bit), science (water conservation), and mathematics (data thresholds). This aimed to support agricultural planning, indirectly aiding food systems and water access in drought-prone areas.
Solar Energy Exploration for EVs (SDG 7): Learners applied first principles thinking to prototype solar-powered models for electric vehicles (EVs), using science (solar energy), technology (solar panels), engineering (prototype design), and mathematics (energy calculations). This aimed to promote clean energy, reducing carbon emissions in transportation.
Solar Scouting System for EV Charging (SDG 7): Learners developed a Raspberry Pi Pico W system to measure solar electricity generation, using technology (Raspberry Pi Pico W), engineering (sensor assembly), science (solar physics), and mathematics (data logging). This aimed to optimize EV charging station placement, supporting sustainable transport

Wind Energy Scouting for EV Charging (SDG 7): Learners built a wind scouting system with sensors to measure wind intensity, using technology (Raspberry Pi Pico W), engineering (system design), science (wind dynamics), and mathematics (data analysis). This aimed to identify optimal wind turbine locations, complementing clean energy solutions.

Weather Station for EV Charging (SDG 7): Learners created a portable weather station with Raspberry Pi Pico W to capture temperature, humidity, sunlight, and wind data, using technology (Raspberry Pi Pico W), engineering (sensor integration), science (meteorology), and mathematics (data processing). This aimed to optimize renewable energy use for EV charging, reducing carbon emissions.

3.3 Projects Code Repository

This repository features code used by K–12 learners to prototype STEAM-based solutions for local food security challenges using the BBC micro:bit. Learners used Scratch, Microsoft MakeCode for Micro:bit and MicroPython, Google Teachable Machine, to create smart farming systems, and optimize farming practices in low-resource settings.

4.0 Discussion

4.1 Problem-Solving and Innovation

Through design thinking (Brown, 2009), learners developed iterative problem-solving skills, emphasizing empathy, ideation, prototyping, and testing. The creative learning spiral (Resnick, 2017), imagining, creating, playing, sharing, reflecting, enabled innovative solutions to climate challenges, fostering resilience and critical thinking in low-resource contexts.

4.2 Interdisciplinary Collaboration

Team-based projects integrated electronics, science, arts, and engineering, aligning with connectivist learning theory (Siemens, 2005). Learners collaborated on solutions like weather stations, mirroring real-world STEAM applications (Lave & Wenger, 1991). For example, the solar scouting system combined coding, sensor design, and environmental science, addressing climate issues holistically.

4.3 Creativity and Critical Thinking

Using Vygotsky’s Zone of Proximal Development (1978), learners progressed from scaffolded tasks to self-directed projects. Tinkering with Scratch, micro:bits, and Raspberry Pi Pico W fostered intrinsic motivation and agency, key to constructionist pedagogy (Papert, 1980). Creative solutions, like drought early warning systems, addressed climate resilience innovatively.

5.0 Learning Environment and Agency

Project-Based Learning (PBL): Real-world projects like heatwave early warning systems fostered ownership and systems thinking, aligning with SDG 13.
Makerspaces: Hands-on experience with micro:bits, Raspberry Pi Pico W, and recycled materials encouraged experimentation and resilience (Martinez & Stager, 2013).
Culturally Responsive Pedagogy: Projects tied to local climate issues (e.g., heatwaves, droughts) made learning relevant and identity-affirming (Gay, 2010).
Hybrid Delivery: Virtual and in-person sessions ensured accessibility, per UDL principles (CAST, 2018).
Mentorship: Facilitators and community feedback bridged theory and practice, supporting critical thinking (Vygotsky, 1978).
Fail-Forward Culture: Iterative design cycles built adaptability and confidence despite resource constraints.

6.0 Feedback and Reflections

Surveys and reflections highlighted significant learner growth:

Confidence in Problem-Solving: 63% strongly agreed and 27% agreed that they felt more confident solving climate problems, reflecting the module’s empowering, hands-on approach.
Belief in Future Impact: 64% strongly agreed and 36% agreed that they can make the world better for future generations, indicating a sense of agency and purpose.
Optimism About Climate Solutions: 77% strongly agreed and 18% agreed that human actions can reduce climate change effects, showing increased hope and proactive attitudes.
Commitment to Sustainable Resource Use: 86% strongly agreed and 14% agreed that resources should minimize environmental harm, demonstrating heightened awareness.
Importance of Environmental Action: 96% strongly agreed and 5% agreed that working on environmental issues is important, underscoring urgency.
Improved Problem-Solving Skills: 73% strongly agreed and 27% agreed that project work improved their ability to address climate issues, validating project-based learning.
Value of Collaboration: 86% strongly agreed and 9% agreed that group work enhanced understanding of climate change and stewardship, highlighting collaborative learning.
Belief in Making a Difference: 72% strongly agreed and 27% agreed that they can make a positive difference against climate change, reinforcing agency.

7.0 Broader Impacts

Empowered Changemakers: High confidence levels (90%+) in problem-solving and belief in personal impact indicate learners are equipped to lead climate initiatives, bridging the knowledge–behavior gap noted in climate education literature.
Community Resilience: Projects like renewable energy prototypes sparked community discussions during exhibitions, promoting local awareness and action toward sustainability.
Scalable Model: The bootcamp’s use of affordable tools and culturally responsive pedagogy offers a replicable framework for low-resource settings, addressing global gaps in climate education (Pearson Global Learner Survey, 58% inadequacy rate).
Emotional Resilience: The shift toward optimism and agency mitigates climate anxiety, as noted in The Guardian, fostering hope and long-term commitment to environmental stewardship.

These outcomes align with Harvard’s Agency by Design framework, emphasizing Learners as agents of change through STEAM-based making and reflection (Harvard GSE, 2018).

8.0 Challenges Faced

Limited Access to Durable Materials:
Affected the quality and longevity of some prototypes
Inconsistent Exposure to Tools:
ome learners had limited access to advanced devices like the Raspberry Pi Pico W
Financial Barriers:
A small number of learners discontinued due to cost-related challenges

9.0 Conclusion

The Climate Change Module illustrates the powerful role of hands-on, inclusive STEAM education in equipping K–12 learners to tackle climate-related challenges. Through culturally relevant projects, coding, and physical computing, learners developed agency and prototyped real-world solutions aligned with the SDGs.

This hybrid model offers a scalable framework for engaging underserved youth in climate action and long-term sustainability, nurturing a generation of climate-resilient innovators.

10.0 Learning Module Contributors

Sam Quansah – Principal Investigator
Vera Yeboah Aninakwah – Lead Facilitator & Code Developer
Nana Adwoa Nsiah – Instructional Facilitator
Victor Ofori Asante – Instructional Facilitator

11.0 References

Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. Longman.

Bell, S. (2010). Project-based learning for the 21st century: Skills for the future. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 83(2), 39–43. https://doi.org/10.1080/00098650903505415

Brown, T. (2009). Change by design: How design thinking creates new alternatives for business and society. Harvard Business Press.

Bruner, J. S. (1960). The process of education. Harvard University Press.

CAST. (2018). Universal Design for Learning guidelines version 2.2. Retrieved from https://udlguidelines.cast.org

Kafai, Y. B. (1995). Minds in play: Computer game design as a context for children’s learning. Lawrence Erlbaum Associates.

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.

Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books.

Resnick, M. (2017). Lifelong kindergarten: Cultivating creativity through projects, passion, peers, and play. MIT Press.

Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10. http://www.itdl.org/Journal/Jan_05/article01.htm

Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. Jossey-Bass.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215