Using local bioindicators and digital tools to assess water quality in school communities: an interdisciplinary approach in natural sciences.
DOI:
https://doi.org/10.70577/asce.v4i4.534Keywords:
Local Bioindicators, Digital Tools, Water Quality, School Communities, Natural Sciences, Environmental Education, Interdisciplinary Approach.Abstract
This study presents an interdisciplinary methodological proposal focused on the use of local bioindicators and digital tools to assess water quality in school communities, with the purpose of linking the teaching of Natural Sciences to the real-world resolution of environmental problems. The research is framed within a systemic transformation approach to education, responding to the need to train citizens capable of addressing complex challenges such as the sustainable management of water resources. A mixed-methods design was employed, combining participatory environmental monitoring through the analysis of aquatic macroinvertebrates (bioindicators) with the use of digital technologies (mobile applications, sensors, and visualization on collaborative platforms). The study population consisted of basic-level students from three rural and peri-urban school communities. The results revealed significant improvements in water quality parameters, particularly in dissolved oxygen, as well as an inverse correlation between conductivity and EPT taxa richness, validating the effectiveness of the bioindicators used. From an educational perspective, notable advances were identified in students’ ecological scientific thinking, increased environmental engagement, and the acquisition of digital competencies. The triangulation of qualitative and quantitative data confirmed the relevance of the adopted approach in integrating ecological, technological, and pedagogical knowledge. In conclusion, this study demonstrates that it is possible to meaningfully incorporate scientific environmental monitoring practices into the school curriculum, contributing to scientific literacy and the transformation of education toward more participatory, contextualized, and sustainability-oriented models.
Downloads
References
Aguilar Tinoco, R. J., Carvallo Lobato, M. F., Román Camacho, D. E., Liberio Anzules, A. M., Hernández Centeno, J. A., Duran Fajardo, T. B., & Bernal Párraga, A. P. (2024). El impacto del Diseño Universal para el Aprendizaje (DUA) en la enseñanza de Ciencias Naturales: Un enfoque inclusivo y personalizado. Ciencia Latina Revista Científica Multidisciplinar, 8(5), 2162–2178. https://doi.org/10.37811/cl_rcm.v8i5.13682 DOI: https://doi.org/10.37811/cl_rcm.v8i5.13682
Amador‑Castro, F., González‑López, M. E., Lopez‑Gonzalez, G., Garcia‑Gonzalez, A., Díaz‑Torres, O., & Carbajal‑Espinosa, O. (2024). Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication. Journal of Environmental Management, 352, 119959. https://doi.org/10.1016/j.jenvman.2023.119959 DOI: https://doi.org/10.1016/j.jenvman.2023.119959
Araújo, J. L., Morais, C., & Paiva, J. C. (2022). Student participation in a coastal water quality citizen science project and its contribution to the conceptual and procedural learning of chemistry. Chemistry Education Research and Practice, 23(1), 100‑112. https://doi.org/10.1039/D1RP00190F DOI: https://doi.org/10.1039/D1RP00190F
Bernal Parraga, A. P., Cadena Morales, A. G., Cadena Morales, J. A., Mejía Quiñonez, J. L., Alcívar Vélez, V. E., Pinargote Carreño, V. G., & Tello Mayorga, L. E. (2024). Impacto de las plataformas de gamificación en la enseñanza: Un análisis de su efectividad educativa. Ciencia Latina Revista Científica Multidisciplinar, 8(5), 2851–2867. https://doi.org/10.37811/cl_rcm.v8i5.13742 DOI: https://doi.org/10.37811/cl_rcm.v8i5.13742
Bernal Párraga, A. P., Haro Cedeño, E. L., Reyes Amores, C. G., Arequipa Molina, A. D., Zamora Batioja, I. J., Sandoval Lloacana, M. Y., & Campoverde Duran, V. D. R. (2024). La gamificación como estrategia pedagógica en la educación matemática. Ciencia Latina Revista Científica Multidisciplinar, 8(3), 6435–6465. https://doi.org/10.37811/cl_rcm.v8i3.11834 DOI: https://doi.org/10.37811/cl_rcm.v8i3.11834
Bernal Párraga, A. P., Ibarvo Arias, J. A., Amaguaña Cotacachi, E. J., Gloria Aracely, C. T., Constante Olmedo, D. F., Valarezo Espinosa, G. H., & Poveda Gómez, J. A. (2025). Innovación metodológica en la enseñanza de las Ciencias Naturales: Integración de realidad aumentada y aprendizaje basado en proyectos para potenciar la comprensión científica en educación básica. Revista Científica de Salud y Desarrollo Humano, 6(2), 488–513. https://doi.org/10.61368/r.s.d.h.v6i2.613 DOI: https://doi.org/10.61368/r.s.d.h.v6i2.613
Bernal Párraga, A. P., Jaramillo Rodríguez, V. A., Correa Pardo, Y. C., Andrade Avilés, W. A., Cruz Gaibor, W. A., & Constante Olmedo, D. F. (2024). Metodologías activas innovadoras de aprendizaje aplicadas al medioambiente en edades tempranas desde el área de Ciencias Naturales. Ciencia Latina Revista Científica Multidisciplinar, 8(4), 2892–2916. https://doi.org/10.37811/cl_rcm.v8i4.12536 DOI: https://doi.org/10.37811/cl_rcm.v8i4.12536
Bernal Párraga, A. P., Orozco Maldonado, M. E., Salinas Rivera, I. K., Gaibor Dávila, A. E., Gaibor Dávila, V. M., Gaibor Dávila, R. S., & García Monar, K. R. (2024). Análisis de recursos digitales para el aprendizaje en línea para el área de Ciencias Naturales. Ciencia Latina Revista Científica Multidisciplinar, 8(4), 9921–9938. https://doi.org/10.37811/cl_rcm.v8i4.13141 DOI: https://doi.org/10.37811/cl_rcm.v8i4.13141
Bernal Párraga, A. P., Sandra Verónica, L. P., Orozco Maldonado, M. E., Arreaga Soriano, L. L., Vera Figueroa, L. V., Chimbay Vallejo, N. M., & Zambrano Lamilla, L. M. (2024). Análisis comparativo de la metodología STEM y otras metodologías activas en la educación general básica. Ciencia Latina Revista Científica Multidisciplinar, 8(4), 10094–10113. https://doi.org/10.37811/cl_rcm.v8i4.13153 DOI: https://doi.org/10.37811/cl_rcm.v8i4.13153
Bonney, R., Phillips, T. B., Ballard, H. L., & Enck, J. W. (2016). Can citizen science enhance public understanding of science? Public Understanding of Science, 25(1), 2–16. https://doi.org/10.1177/0963662515607406 DOI: https://doi.org/10.1177/0963662515607406
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa DOI: https://doi.org/10.1191/1478088706qp063oa
Brody, H., & Ragin, D. F. (2022). Teaching environmental science through interdisciplinary approaches in K-12 education. Journal of Environmental Studies and Sciences, 12(4), 612–623. https://doi.org/10.1007/s13412-022-00752-1
Capdevila, A. S., Perelló, J., & Bonhoure, I. (2020). Citizens’ perception of water quality: A key factor for the success of citizen science projects. Science of The Total Environment, 715, 136865. https://doi.org/10.1016/j.scitotenv.2020.136865
Capps, D. K., & Crawford, B. A. (2017). Inquiry-based instruction and teaching about nature of science: Are they happening? Journal of Science Teacher Education, 28(5), 433–449. https://doi.org/10.1080/1046560X.2017.1356560
Chandel, C. P. S. (2024). Use of algae as bioindicators of water quality: A review. Water and Environment Journal, 38(1), 14–22. https://doi.org/10.1002/wwp2.12137 DOI: https://doi.org/10.1002/wwp2.12137
Chen, T., et al. (2025). Construction of a comprehensive water quality assessment: The BE‑WQI framework. Journal of Water Quality, https://doi.org/10.1016/j.jwqa.2025.720.
Chen, T., Song, C., Zhan, P., Yao, J., Li, Y., & Zhu, J. (2022). Remote sensing estimation of the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions. Science of The Total Environment, 807(Part 1), 150772. https://doi.org/10.1016/j.scitotenv.2021.150772 DOI: https://doi.org/10.1016/j.scitotenv.2021.150772
Cho, Y. (2024). Geo-participation of youth in school-based environmental education using mobile mapping tools. Urban Science, 4(4), 53. https://doi.org/10.3390/urbansci4040053 DOI: https://doi.org/10.3390/urbansci4040053
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications.
D’Alessio, M., Berta, M., & Ghezzi, L. (2021). Digital tools for participatory environmental monitoring: Integrating citizen science and IoT. Environmental Monitoring and Assessment, 193(5), 287. https://doi.org/10.1007/s10661-021-09034-1
Fernández-Llamazares, Á., Garteizgogeascoa, M., Basu, N., & Reyes-García, V. (2020). The role of schools in biodiversity conservation: Linking education and citizen science. Ambio, 49, 126–137. https://doi.org/10.1007/s13280-019-01124-3
Fraisl, D., Campbell, J., See, L., Wehn, U., Wardlaw, J., Gold, M., & Moorthy, I. (2020). Mapping citizen science contributions to the UN sustainable development goals. Sustainability Science, 15(6), 1735–1751. https://doi.org/10.1007/s11625-020-00833-7 DOI: https://doi.org/10.1007/s11625-020-00833-7
Guerrero‑Aguilar, A., Rodríguez‑Castrejón, U. E., Serafín‑Muñoz, A. H., Schüth, C., & Noriega‑Luna, B. (2022). Bioindicators and biomonitoring: Review of methodologies applied in water bodies and use during the Covid‑19 pandemic. Acta Universitaria, 32, e3388. https://doi.org/10.15174/au.2022.3388 DOI: https://doi.org/10.15174/au.2022.3388
Hajj-Hassan, A., Chaker, A., & Cederqvist, L. (2024). Leveraging digital tools for environmental education: A review of mobile applications for sustainability learning. Sustainability, 16(9), 3733. https://doi.org/10.3390/su16093733
Hassan, A., Chaker, A., & Cederqvist, L. (2024). Leveraging digital tools for environmental education: A review of mobile applications for sustainability learning. Sustainability, 16(9), 3733. https://doi.org/10.3390/su16093733 DOI: https://doi.org/10.3390/su16093733
Hsu, Y.‑S., Kao, H.‑L., & Chai, C.‑S. (2023). Revolutionizing informal education: Intersection of citizen science and learning theories. International Journal of Environmental and Science Education, 18(3), 1–17. https://www.ijese.com/download/revolutionizing-informal-education-intersection-of-citizen-science-and-learning-theories-13726.pdf DOI: https://doi.org/10.29333/ijese/13726
Irawati, S., & Sulisworo, D. (2023). The integration of digital platforms in environmental education: A case of blended learning in Indonesian schools. Heliyon, 9(3), e15009. https://doi.org/10.1016/j.heliyon.2023.e15009 DOI: https://doi.org/10.1016/j.heliyon.2023.e15009
Lausch, A., et al. (2024). Monitoring water diversity and water quality with remote sensing: A trait‑based integrative approach. Remote Sensing, 16(13), 2425. https://doi.org/10.3390/rs16132425 DOI: https://doi.org/10.3390/rs16132425
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications. https://books.google.com/books/about/Naturalistic_Inquiry.html?id=2oA9aWlNeooC DOI: https://doi.org/10.1016/0147-1767(85)90062-8
Lukhabi, D. K., Mensah, P. K., Asare, N. K., Awushie Akwetey, M. F., & Faseyi, C. A. (2024). Benthic macroinvertebrates as indicators of water quality: A case study of estuarine ecosystems along the coast of Ghana. Heliyon, 10 (7), e28018. https://doi.org/10.1016/j.heliyon.2024.e28018 DOI: https://doi.org/10.1016/j.heliyon.2024.e28018
McCarty, J., Tuffnell, N., & Caruso, B. (2025). Validating citizen-generated data for environmental monitoring: A multi-site comparison. Environmental Science & Policy, 161, 104–117. https://doi.org/10.1016/j.envsci.2025.103908
McKinley, D. C., Miller-Rushing, A. J., Ballard, H. L., Bonney, R., Brown, H., Cook-Patton, S. C., . & Soukup, M. A. (2017). Citizen science can improve conservation science, natural resource management, and environmental protection. Biological Conservation, 208, 15–28. https://doi.org/10.1016/j.biocon.2016.05.015 DOI: https://doi.org/10.1016/j.biocon.2016.05.015
Orozco‑González, C. E., & Ocasio‑Torres, M. E. (2023). Aquatic macroinvertebrates as bioindicators of water quality: A study of an ecosystem regulation service in a tropical river. Ecologies, 4(2), 209‑228. https://doi.org/10.3390/ecologies4020015 DOI: https://doi.org/10.3390/ecologies4020015
Parmar, T. K., Rawtani, D., & Agrawal, Y. K. (2016). Bioindicators: The natural indicator of environmental pollution. BioInorganic Chemistry and Applications, 2016, 1–11. https://doi.org/10.1155/2016/4569724
Peeters, E. T. H. M., Gerritsen, A. A. M., Seelen, L. M. S., Begheyn, F., Rienks, H., & Weijters, M. J. H. (2022). Monitoring biological water quality by volunteers complements professional assessments. PLOS ONE, 17(2), e0263899. https://doi.org/10.1371/journal.pone.0263899 DOI: https://doi.org/10.1371/journal.pone.0263899
Ramesh, A., Raj, A., & Shrestha, A. (2024). Community-based monitoring of drinking water quality by minimally trained users using low-cost sensors. ACS ES&T Water, 4(7), 1560–1570. https://doi.org/10.1021/acsestwater.4c00164 DOI: https://doi.org/10.1021/acsestwater.4c00164
Ruiz-Moreno, D., Salazar-González, A., & Bustamante, A. (2021). Ética y participación comunitaria en la investigación ambiental: lineamientos para contextos educativos. Revista Colombiana de Bioética, 16(1), 95–112. https://doi.org/10.18270/rcb.v16i1.3501
Saleem, F., Rehman, S. U., & Saeed, M. (2024). Mobile sensor networks and participatory sensing for water quality monitoring: Review and research challenges. Environmental Technology & Innovation, 35, 103467. https://doi.org/10.1016/j.eti.2023.103467 DOI: https://doi.org/10.1016/j.eti.2023.103467
Santana Mero, A. P., Bernal Párraga, A. P., Herrera Cantos, J. F., Bayas Chacha, L. M., Muñoz Solórzano, J. M., Ordoñez Ruiz, I., Santín Castillo, A. P., & Jijón Sacon, F. J. (2024). Aprendizaje adaptativo: Innovaciones en la personalización del proceso educativo en Lengua y Literatura a través de la tecnología. Ciencia Latina Revista Científica Multidisciplinar, 8(4), 480–517. https://doi.org/10.37811/cl_rcm.v8i4.12292 DOI: https://doi.org/10.37811/cl_rcm.v8i4.12292
Shams El-Din, N. G., Ibrahim, A. M., & El-Gohary, F. A. (2022). Using aquatic macroinvertebrates as bioindicators for water quality assessment in the Nile Delta. Egyptian Journal of Aquatic Biology and Fisheries, 26(3), 45–60. https://doi.org/10.21608/ejabf.2022.236331
Shao, G. P., & Bishop, I. J. (2025). Citizen science in river monitoring: A systematic literature review. Environmental Science & Policy, https://doi.org/10.3389/fenvs.2025.1609084 DOI: https://doi.org/10.3389/fenvs.2025.1609084
Stankiewicz, J., König, A., & Pickar, K. (2023). How certain is good enough? Managing data quality & uncertainty in citizen science water monitoring. Citizen Science: Theory and Practice, 8(1), 39. https://doi.org/10.5334/cstp.592 DOI: https://doi.org/10.5334/cstp.592
Staude, A., Förster, T., & Liess, M. (2024). Low-cost IoT-based water quality sensors: Validation and field application in school projects. Sensors, 24(8), 2675. https://doi.org/10.3390/s24082675
Tang, J., Zhang, L., & Huang, Z. (2024). Internet of Things applications for environmental monitoring: A review of recent developments. Environmental Research, 246, 118890. https://doi.org/10.1016/j.envres.2023.118890
von Gönner, J., Masson, T., Köhler, S., Fritsche, I., & Bonn, A. (2024). Citizen science promotes knowledge, skills and collective action to monitor and protect freshwater streams. People and Nature, 6(6), 2357–2373. https://doi.org/10.1002/pan3.10714 DOI: https://doi.org/10.1002/pan3.10714
Woods, S. (2025). How citizen science can help to solve the global freshwater crisis. Nature, 644, 582. https://doi.org/10.1038/d41586-025-02614-7 DOI: https://doi.org/10.1038/d41586-025-02614-7
Yin, R. K. (2014). Case Study Research: Design and Methods (5th ed.). SAGE Publications. Enlace: https://books.google.com/books/about/Case_Study_Research.html?id=Cdk5DQAAQBAJ
Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). SAGE Publications. Enlace: https://books.google.com/books/about/Case_Study_Research_and_Applications.html?id=6DwmDwAAQBAJ
Zamora Arana, M. G., Bernal Párraga, A. P., Ruiz Cires, O. A., Cholango Tenemaza, E. G., & Santana Mero, A. P. (2024). Impulsando el aprendizaje en el aula: El rol de las aplicaciones de aprendizaje adaptativo impulsadas por inteligencia artificial en la educación básica. Ciencia Latina Revista Científica Multidisciplinar, 8(3), 4301–4318. https://doi.org/10.37811/cl_rcm.v8i3.11645 DOI: https://doi.org/10.37811/cl_rcm.v8i3.11645
Zhu, X., Lin, Q., & Ma, J. (2022). Temporal analysis of surface water quality using multivariate statistical techniques. Science of the Total Environment, 830, 154765. https://doi.org/10.1016/j.scitotenv.2022.154765 DOI: https://doi.org/10.1016/j.scitotenv.2022.154765
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Elvis Renato Flores Abad, Nancy Fabiola Chiluisa Parra, Lastra Ordóñez Rudy Fernando, Verónica Elizabeth Flores Palma, David Alciviades Gómez Mezones
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Eres libre de:
- Compartir : copiar y redistribuir el material en cualquier medio o formato
- Adaptar : remezclar, transformar y desarrollar el material
- El licenciante no puede revocar estas libertades siempre y cuando usted cumpla con los términos de la licencia.
En los siguientes términos:
- Atribución : Debe otorgar el crédito correspondiente , proporcionar un enlace a la licencia e indicar si se realizaron cambios . Puede hacerlo de cualquier manera razonable, pero no de ninguna manera que sugiera que el licenciante lo respalda a usted o a su uso.
- No comercial : no puede utilizar el material con fines comerciales .
- CompartirIgual — Si remezcla, transforma o construye sobre el material, debe distribuir sus contribuciones bajo la misma licencia que el original.
- Sin restricciones adicionales : no puede aplicar términos legales ni medidas tecnológicas que restrinjan legalmente a otros hacer algo que la licencia permite.
