First Monday

Children using electronic sensors to create and use knowledge on environmental health by Maria Joao Silva



Abstract
The Eco-sensors4Health Project (Eco-sensors for health: Supporting children to create eco-healthy schools) is centered on the use of electronic sensors by children to become agents in the creation of healthy and sustainable environments in schools. In this project, the environmental health data, acquired by children with the sensors, with tablets or mobile phones, is managed with the support of a collaborative platform that allows entering, searching and visualizing data of the different schools. The Eco-sensors4Health Toolkit is a guide to the implementation of the environmental health activities in schools, which include the exploratory sensorial tasks, the environmental data acquisition, organization, and interpretation, and the decision making to improve schools’ environmental health. The iterative development processes of the Eco-sensors4Health Platform and Toolkit are presented in this paper as well as illustrative results of its uses in different schools. Those results indicate that the use of sensors by children in the context of authentic environmental health activities makes it possible to children to create and apply knowledge to solve schools’ environmental health problems.

Contents

Introduction
Using sensors to create environmental health knowledge in school activities
The Eco-sensors4Health Project: The iterative development of the Toolkit and the Platform
Conclusion

 


 

Introduction

The Eco-sensors4Health Project (Eco-sensors for health: Supporting children to create eco-healthy schools) is centered on children using electronic sensors to become agents in the creation of healthy and sustainable environments in primary schools. The research, presented in this paper, is part of the Eco-Sensors4Health Project and aims at exploring the potential of electronic sensors to be used by children in creating and applying environmental health knowledge in the context of authentic school activities. Nowadays, sensors can be defined as physical or virtual objects that are used for tracking, recording or measuring, given that, for instance, a software piece that track non-physical (virtual) properties can be called a sensor (Schneider, et al., 2015). In a different perspective, sensors can be defined as a device that receives a stimulus (quantity, property, or condition) and responds with an electrical signal, this way including natural and human constructed sensors (Fraden, 2016). In this paper, the expression “electronic sensors” is used to refer physical devices, integrated in mobile devices, which can be used to detect environmental (physical, chemical, or biological) properties, and that transmit electric signals to electronic devices, such as data loggers. Electronic sensors together with data loggers can be used to measure, record, and display multiple representations of environmental variables (Brandt, et al., 2011).

According to the World Health Organization (2018), environmental health aims at assessing and controlling the environmental (physical, chemical, and biological) factors that can potentially affect health. In Portugal, as well as internationally, sound pollution, air pollution, lack of thermal comfort, and bad lighting are factors with potential health risk in the primary schools’ environment (Amann, 2015). These factors of indoor environmental quality are responsible for central problems in Portuguese primary schools (Amann, 2015; Pereira, et al., 2014; Madureira, et al., 2015), causing concentration difficulties (Amann, 2015; World Health Organization, 2015) with negative consequences in teaching and learning performance and well-being (Pereira, et al., 2014; World Health Organization, 2015).

In this context, electronic sensors can be used in authentic environmental health learning activities to assess and monitor variables, such as sound level, carbon dioxide concentration, and temperature that are of central relevance to identify, explore, and solve the abovementioned environmental health problems. The Globe project (Globe Program, 2019) is a noteworthy example of the importance and magnitude of projects on environmental health knowledge in educational contexts, with 122 participating countries, 35,995 schools and 37,829 teachers involved, 162,367 Globe observers, and 173,824,781 measurements (data accessed on November 2019).

In the research here presented, which is part of the Eco-sensors4Health project, children were engaged in learning by doing activities, designed in a constructivist perspective that was based on Salomon and Perkins (1998): i) the active social mediation of individual learning; ii) the social mediation as participatory knowledge construction; and, iii) the social mediation by cultural artifacts such as sensors and tablets. This way, children used, sensors, together with tablets, in a collaborative and cooperative way, in authentic learning activities (Chinn and Malhotra, 2002; Fenton, 2008), to identify, explore, and suggest solutions to environmental health problems, in the real world, making use of scientific inquiry techniques. Those activities allowed the inclusive and civic participation of children at the local level, creating knowledge on school environmental health problems and applying that knowledge to understand and address such problems (Austin, 2010). In the research presented in this paper, which is part of the Eco-sensors4Health project, children also shared the created knowledge, using the Eco-sensors4Health collaborative platform that allows entering, searching, and visualizing data of the different schools.

The purpose of this paper is to present the Eco-sensors4Health project main activities (case studies in three community primary schools), and the iterative development of two central project tools, the Toolkit and the collaborative platform. The Toolkit will support school community teachers in promoting the use of eco-sensors by children to create and apply knowledge to improve schools’ environmental health. The collaborative platform will allow the sharing of the environmental health knowledge created by children.

Following this introduction, this paper includes: i) a section on related work, ii) a section on the development phases of the Eco-sensors4Health project that includes the development processes of two fundamental projects tools, the Eco-sensors4Health Toolkit and Platform, iii) a section that integrates illustrative results of the Eco-Sensors4Health activities in schools; iv) lessons learned; and, iv) a conclusion.

 

++++++++++

Using sensors to create environmental health knowledge in school activities

The body is the center of experience, emotions, and feelings (Damasio, 2003). This way, the knowledge, and the practices in the environment are embodied, including a fundamental sensorial dimension (Ergler, et al., 2016). Additionally, the sensorial relationship between people and the environment is being influenced by the use of sensors, often integrated in mobile devices, such as mobile phones and tablets (Schneider, et al., 2015). Those sensors are merging the physical and virtual worlds (Schneider, et al., 2015), and support the production of the multimedia data that often inform people’s interaction with environment (Evans-Cowley, 2010).

Related and previous projects

Diverse projects have been promoting the joint use of senses and mobile sensors, by school children, to sense and make sense of the environment in the context of different science disciplines, such as Physical Sciences, Life Sciences, Geography, and Environmental Sciences.

 

Table 1: Specific tasks.
Type of interventionExamples of projects
Elementary school children use senses and sensors in the classroom to explore environmental processes and properties
  • TEEMSS2
  • POLLEN
  • EcoSensors for Mountain Classrooms
Integration of Volunteer Geographic Information in schools’ curricula and in educational projects
  • The Globe Project
  • GeospatialLearning@PrimarySchool
  • SchoolSenses@Internet
  • USense2Learn

 

TEEMSS2 (Zucker, et al., 2008) and POLLEN (van den Berg, et al., 2010) are examples of well-known projects in which elementary school children use senses and sensors (probeware) in the classroom to explore environmental processes and properties, and its multiple representations, while learning Physical and Life Sciences’ topics such as temperature, sound, and plant development. Both projects have an inquiry based approach and support transitions from children’s everyday practices to scientific knowledge, aiming at bridging the gap from concrete to abstract thinking (Eberbach, 2009; Henning, 2004).

The EcoSensors for Mountain Classrooms program at Appalachian State University (n.d.) partnered with local school teachers to bring advanced digital sensor technology to their science classrooms. This program aims to help students develop a deeper understanding of local environmental issues such as stream water quality through the use of digital environmental science devices that they may otherwise not have access to in school. It allows K-12 students to study environmental education concepts outside of the classroom and apply science skills like observation, measurement, and data analysis in real time using devices that are used at the university level and by researchers in the field.

Regarding geography, the development and availability (low cost) of geospatial technologies (GST), make possible the educational use of digital globes (such as Google Earth) and of global positioning systems (GPS), in digital mobile devices, to develop geospatial thinking (van der Schee, et al., 2015; Baker, et al., 2015). Furthermore, the use of these GST together with the use of sensors, such cameras, audio recorders, air and water sensors, have been contributing to the integration of Volunteer Geographic Information in schools’ curricula and in educational projects from primary to higher education (Bartoschek and Keßler, 2013). Some of these projects are simultaneously Environmental Sciences projects, such as the pioneer Globe Project (Globe Program, 2018), the GeospatialLearning@PrimarySchool project (Bartoschek and Keßler, 2013), the SchoolSenses@Internet (Silva, et al., 2009), and the USense2Learn (Silva, et al., 2010) projects, in which children used senses and sensors to select, acquire, interpret, and share, through mapping, georeferenced information, regarding environmental elements and factors, such as water, flora, urban equipment, sound, air, and water properties in the school environment.

Participatory environmental health knowledge creation

The Eco-sensors4Health project follows the lessons learned in the abovementioned projects to promote the participatory environmental health knowledge creation by school children, making use of senses and sensors with different goals:

 

++++++++++

The Eco-sensors4Health Project: The iterative development of the Toolkit and the Platform

The Eco-sensors4Health Project aims at supporting children in using sensors to acquire environmental data to identify, explore, and contribute to solve schools’ environmental health problems, along with facilitating child-driven sharing of the created environmental health information using the collaborative platform. The Eco-sensors4Health collaborative platform is meant to allow multiple queries and comparisons of environmental health conditions in different schools and circumstances. To support school teachers in scaffolding children’s participation in such activities, the Eco-sensors4Health Project developed iteratively a Toolkit that includes suggestions for problem solving and scientific inquiry tasks, documents for data registration, as well as suggestions for facilitating data sharing in the Eco-sensors4Health platform (www.eco-sensors4health.pt).

In order to achieve those goals, the Eco-sensors4Health Project was structured in different phases, including the following: i) Iterative development of the Toolkit; ii) Iterative development of the collaborative platform; iii) Use of the Toolkit and of the collaborative platform in the case studies with primary school children; and, iv) Assessment of the use of the collaborative platform and of children learning outcomes.

The iterative development of the Toolkit and the iterative development of the collaborative platform are described in this section, while the use of the Toolkit and of the collaborative platform in the case studies with primary school children and the assessment of the use of the collaborative platform and of children learning outcomes are addressed in the next section.

The iterative development of the Eco-sensors4Health Toolkit

The iterative development of the Toolkit (Silva, et al., 2018a) was guided by using research-based solutions for complex problems in the context of an educational practice (Plomp, 2010). The first step was the design of the children’s activities that would be supported by the Toolkit. The main school environmental health problems identified in Portugal and the results of previous and related projects (Silva, et al., 2009; Silva, et al., 2010) were the triggers for avenues of inquiry. The children’s activities were designed as scientific inquiries centered on the topics of sound pollution, air pollution (measured as carbon dioxide concentrations), and thermal (dis)comfort. Each activity was guided by a collaborative document (experiment plan, designed by the Eco-Sensors4Health researchers) that is meant to be completed during the activity. Children were asked to structure their work in six stages: i) definition of the problem and of the research questions; ii) sensorial exploration of the sound/air properties/temperature; iii) debates centered on related main concepts; iv) environmental data acquisition, organization and interpretation by children, using sensors and senses; v) critical reflection on the basis of a previously defined set of questions, and, vi) suggestions to improve school’s environmental health.

To enable these activities, it was decided to use a set of sensors that were considered robust and easy to use by primary school children: Sound sensor (tablets have an built-in sound sensor); Carbon dioxide sensor (PASPORT Carbon Dioxide Gas Sensor — PS–2110); Temperature and humidity sensor (PASPORT Weather Anemometer Sensor — PS–2174). These sensors were used with the free app SparkVUE (for tablets and mobile phones).

The Eco-Sensors 4Health pilot activities were implemented during the 2016–2017 and 2017–2018 school years, in the Ciência Viva School (CVS), a science museum primary school project in Portugal, which receives, each week, two classes of the third or fourth grade classes from different schools. This implementation involved more than 900 primary school children, and two CVS teachers that are researchers in the Eco-sensors4Health Project. The school teachers collaborated with the CVS teachers in the implementation of the project pilot activities.

An in-depth analysis of the results of three classes (90 children) evidenced that children (Silva, et al., 2018c): i) showed no technical difficulties in acquiring data with the sensors and tablets; ii) improved, from the pre- to post-tests on most of the ‘topic specific Knowledge’ questions; iii) performed a set of epistemic practices, (practices that construct knowledge and are similar to scientists’ practices), such as “Describe”, “Forecast”, “Use sensors”, “Interpret”, “Organize information”, and “Relate”, which are essential elements of scientific inquiries. These practices were observed in both sensorial explorations and the tasks of data acquisition and interpretation. Furthermore, the epistemic practices were guided by research questions defined by the teacher/researchers in collaboration with the children, such as “How does sound level change when we change classroom activities?”, and “How does carbon dioxide concentration change when we change our location in the school environment?”

Following the exploratory implementation, the structured activities were integrated into the Toolkit. The final Toolkit included: i) an introduction to the fundamental concepts related to the three school environmental health problems addressed in the activities; ii) the data collection forms to organize and interpret the acquired data; and, iii) the collaborative documents (experiment plans) and the pre- and post-tests. All these elements have been iteratively improved during the exploratory activities, as well as during the case studies with community primary schools that are described in section four.

The iterative development of the Eco-sensors4Health collaborative platform

The main goal of the Eco-sensors4Health collaborative platform is to share, in a meaningful way, the environmental health data produced by the different schools. The users of the Eco-sensors4Health collaborative platform can access three main areas: blogs area; data query area; data introduction area. All the users can query data and visit the blogs (one of each school). However, only participant teachers and children can introduce environmental data, and publish in their school blog. Each blog contextualizes data, and authors (children) reflect critically on the activities developed by the classes and on the produced data. The query area is twofold: users can consult a data set, after defining the parameters of that set, or can compare two sets of data, for instance: compare the sound level data, when children “make silence” in two different schools, or the carbon dioxide concentration in two places of the same school.

The iterative development of the collaborative platform involved Eco-sensors4Health project researchers from different areas, such as environmental education, environmental health and information and communication technologies (ICT) experts, based on previous projects, on ICT in education knowledge, and on the exploratory implementation of the Toolkit activities in the science museum Ciência Viva School. The iterative development process included the implementation of a rapid prototype, and multiple usability tests of the diverse versions of the platform. The user interface was designed based on the guidelines for child-user interfaces (Sherwin and Nielsen, 2019), such as: use fonts larger than the fonts for adults; minimize scrolling; minimize typing; make the interaction consistent.

The main goal of the Eco-sensors4Health platform is to allow querying and visualizing the environmental health data (sound level, carbon dioxide concentration, temperature, relative humidity, light level data) acquired by community primary school children using the electronic sensors, during the Toolkit activities. This way, the collaborative platform should allow entering, searching and visualizing the environmental health data across the different schools. That is why, the data model of the platform was designed to have two key entities: “Experiment” and “Measurement” (Silva, et al., 2018b). The Experiment entity encompasses students and teacher characterization, a description about the experience (the Toolkit activity), the variable studied in the experience/activity (sound level, carbon dioxide concentration, temperature, relative humidity or light level), and the beginning and ending date of the experience/activity. The Measurement entity integrates the following attributes: locale, date and hour of the data acquisition; sensor data; conditions, such as interventions and activities affecting the variable; and, complimentary multimedia information.

In order to improve the significance of the platform to the school communities and to scaffold children in using it, the design of the platform was linked to the design of the Toolkit. The data collection forms included in the Toolkit, have data fields similar to the ones of the data introduction page in the platform, supporting children in entering the data acquired with the sensors. Furthermore, the filled collaborative documents (experiment plans), can be uploaded and downloaded in the platform, giving a context to the data acquired by children with the sensors. The template of the collaborative documents is also included in the Toolkit to guide the scientific inquiry in each activity, and to be collaboratively filled by teachers and children during the activity.

Eco-Sensors4Health case studies in three primary schools

The Eco-sensors4Health Toolkit and collaborative platform were used in three case studies in three Lisbon community primary schools, involving 131 children of six fourth grade classes, six teachers (one of each class), and one project researcher that is also a teacher (T/R). All the participant school teachers selected sound pollution topic as the most relevant to their classes’ contexts. Therefore, the three case studies were on sound pollution data.

For each class, four sessions of one hour (Table 2) were led by the T/R that planned the activities, using the Toolkit, and following its sequence: sensorial exploration tasks, environmental data acquisition, organization and interpretation, and the decision-making to improve schools’ environmental health. The activities were developed using the scientific inquiry method, guided and registered in the collaborative documents (experiment plans).

Children actively participated in the diverse tasks. They observed and described both data acquisition and sensorial tasks. For instance, in the experiment with the sound pollution research question “What happens when the tympanic membrane is damaged?”, children observed the behavior of sugar grains on a tightly stretched and a poorly stretched adherent film on the top of two drums, while producing sound with a stick on a pan lid and moving away from the drums. Then, it was possible to record children’s statements of what happened (description): the T/R asked what happened to the sugar grains on the poorly stretched adherent film, when she was producing the sound and moving away. A child said “It stopped”. “That one [the drum with the sugar on the tightly stretched adherent film] moved more than the other [the drum with the sugar on the poorly stretched adherent film]” said another child. The T/R asked to the other children “And you, what did you observe?”. “The same” answered the children. With teacher (T/R) mediation, children were able to interpret what they have observed, identifying the tightly stretched adherent film with healthy tympanic membrane, and the poorly stretched adherent film with the tympanic membrane of people that have already been exposed to sound pollution for years.

In another sensorial experiment, with the research question “Does the sound propagate in the same way in solids and gases?”, children heard the sound of a pencil hitting a hanger that was touching their ear. Afterwards, they heard the sound of the pencil hitting the hanger that was a few centimeters distant from their ear. When the T/R asked how the sound traveled to the ear, when the hanger was touching it, children answered: “Through the hanger”. Moreover, when the T/R asked how the sound traveled to the ear, when the hanger was a few centimeters distant from their ear, children answered: “Through the air”. This way, children interpreted what they were observing. This experiment was followed by a simulation to complete the answer to the research question.

 

Table 2: Tasks of the four sound pollution activity sessions.
First sessionSecond sessionThird sessionFourth session
  • Introduction to the Eco-sensors4Health project
  • What is sound?
  • What is needed to have sound?
  • What happens when the tympanic membrane is damaged?
  • Experiment and video on sound pollution risks and protective equipment
  • Sound propagation in liquid and solids (experiments and simulations)
  • Filling the collaborative documents (experiment plans)
  • Measurement of sound levels in the canteen and in the schoolyard
  • Measurement of sound levels indoors and outdoors, while making silence, singing and clapping hands
  • Measurement of the sound level produced by an alarm clock, and by the same alarm clock inside an empty box, and inside the same box with crumpled paper
  • Registration of the acquired data in the data collection forms
  • Classification of the acquired data, using health criteria
  • Introduction of the acquired data in the collaborative platform
  • Analysis and interpretation of the data, using the platform
  • What do you suggest to solve the noise pollution problem in your school?

 

Children were also able to use the sound sensors in diverse locations and during diverse activities. They acquired and interpreted the data, using a critical approach. An illustrative occurrence: children of a class were using the sensors to measure the maximum sound level, while all the children were singing; a boy read the value in the SparkVUE app and said “70”; a girl answered “70, no, it is very little”, this way showing that she was expecting (forecasting) a higher value. And she was right. It was verified that the sensor has not been set up properly.

The children of the six classes were able to fill the data collection forms (see Figure 1) with the acquired data, as well as to classify each value as harmful or safe to health, and to enter that same data in the collaborative platform (see Figure 2), helping to organize information.

 

Detail of a data collection form filled in by one girl with the sound level data acquired with the sound sensor, during the sound pollution activity
 
Figure 1: Detail of a data collection form filled in by one girl with the sound level data acquired with the sound sensor, during the sound pollution activity.
 

 

Detail of the data entry screen of the collaborative platform, with the sound level data acquired in the canteen at lunch time
 
Figure 2: Detail of the data entry screen of the collaborative platform, with the sound level data acquired in the canteen at lunch time.
 

The platform allows querying the entered data, in the same or in different schools. For instance, children can compare, in a specific school, the sound level data in the classroom with the sound level data in the canteen (Figure 3). When clicking with the mouse on each point, its value and the conditions in which the data was acquired are presented.

 

Graph produced by the platform showing the results of a query
 
Figure 3: Graph produced by the platform showing the results of a query.
 

In Figure 3 we can see a graph displaying the comparison of the sound level data in the classroom (orange points) with the sound level data in the canteen (blue points). The values near 50 dB or less were acquired with children “making silence” in the classroom. The other orange points represent the data acquired with children clapping hands or singing in the classroom. The blue points represent the data acquired with children having lunch in the canteen.

When asked to draw their day-to-day sounds, children created multiple representations. They drew the sound sources with adjacent sound waves. The most common sound sources were people, cars, sound equipment, and animals (Figure 4).

 

Drawings made by a girl (on the top) and a boy (at the bottom), when asked to draw their day to day sounds
 
Figure 4: Drawings made by a girl (on the top) and a boy (at the bottom), when asked to draw their day to day sounds.
 

At the end of all tasks, children were asked to suggest solutions to the sound pollution in their school. The children in these case studies suggested four types of solutions: don’t make loud noise; don’t stay in noisy places; use ear protectors; use insulating materials on the walls and floor. For instance, one girl wrote “Putting materials that absorb the sound, protective earphones, earplugs and not saying things too loudly”. This way, their answers showed that they related knowledge learned in one situation to a different situation, applying the previously acquired knowledge (see tasks in Table 2) to solve the real noise problem.

Lessons learned and limitations

The project activities, developed in the science museum Ciência Viva School with the primary school children, allowed the learning of the following lessons, in line with related research:

After the project activities in the science museum Ciência Viva School the data registration forms to be included in the Toolkit, and used off-line by children, were adapted to be consistent with the platform data entry forms.

Subsequently, the structured activities, with all the tested learning resources, were integrated in the Toolkit, which was used to guide the project activities in the community schools.

The Toolkit was very useful in supporting the Teacher Researcher (T/R) in implementing the activities with community schools children. The collaborative documents were especially important in guiding all the inquiry activities, since they guided the definition of the research questions, the design of the inquiry tasks, the interpretation of the sensors’ data, and the final critical reflection. Consequently, after the intervention in the community schools, the Toolkit was distributed online and off-line to school teachers.

All the lessons learned in the science museum Ciência Viva School were also witnessed in the intervention in the community schools. Furthermore, children in the community school successfully used the collaborative platform to entry, share and query sensors’ data.

The main identified limitations were:

 

++++++++++

Conclusion

The research presented in this paper was developed as part of the Eco-Sensors4Health project and was centered on the use of electronic sensors by children in their schools to create and apply knowledge to improve schools’ environmental health.

The Eco-Sensors4Health project Toolkit and the collaborative platform are two fundamental tools in the Eco-Sensors4Health project. The Toolkit is an activity guide to support elementary school teachers in scaffolding children in scientific inquiries, which make use of sensors to solve environmental health problems, such as sound pollution, air pollution, and thermal discomfort. The collaborative platform allows to children to introduce/enter, query, and visualize the schools’ environmental data using data they acquired with sensors. This platform also allows the visualization of the conditions of data acquisition, as well as of the data interpretation in the context of children’s scientific inquiries.

The Toolkit and the collaborative platform were iteratively designed and implemented. These two processes were linked to assure consistency between the Toolkit and the platform in what concerns data entry and data contextualization.

Three case studies were developed from community primary schools’ implementation. In each of the case studies, teachers selected sound pollution as the environmental health problem to address, showing its relevance to primary schools, as reported in the literature (Aman, 2015; Woolner and Hall, 2010). The activities implemented in these case studies were planned on the basis of the Toolkit’s strategies, using a constructivist and embodied approach, and making explicit the joint use of senses and sensors to solve environmental problems, in real world authentic activities.

In the three case studies, it was possible to observe that children:

In view of these outcomes, we conclude that children used the electronic sensors, in authentic activities, created situated knowledge and applied that knowledge to suggest improvements in schools’ environmental health, specifically as to what concerns solving sound pollution problems that were mainly caused by children’s activities, a source highlighted in related studies (Woolner and Hall, 2010).

This research illustrates how children’s involvement in collaborative activities with eco-sensors to solve environmental health problems can promote higher proficiency levels of digital competences. Collaborative activities with eco-sensors to solve environmental health problems — including browsing, searching, filtering, managing and evaluating digital content; entering data and querying in a digital platform; sharing, collaborating and engaging in citizenship through digital technologies — can enhance specific digital competences, such as information and data literacy, communication, and collaboration (Silva, et al., 2018c).

Future work will include one more case study, and the assessment of children’s learning results through the analysis of pre- and post-tests that include questions in the following categories: Knowledge, Environmental and Health Awareness, Attitudes, Perception of the Physical Environment, Personal Investment, and Responsibility. End of article

 

About the author

Maria João Silva is Professor in the Physical and Natural Sciences Domain of Lisbon School of Education, Polytechnic Institute of Lisbon, and Principal Investigator of the Eco-Sensors4Health Project (Eco-sensors for health: Supporting children to create eco-healthy schools).
E-mail: mjsilva [at] eselx [dot] ipl [dot] pt

 

Acknowledgements

This paper was produced in the context of the Eco-Sensors4Health project (Eco-sensors for health: Supporting children to create eco-healthy schools). The Eco-Sensors4Health project (LISBOA-01-0145-FEDER-023235) is supported by FEDER (PORTUGAL2020) and Portugal State Budget.

The author thanks the participant schools, teachers, children and the Grant Holder Researcher Camila Almeida for making possible the here described activities.

 

References

G. von Amann (coordinator), 2015. School health program 2015 (Programa de sade escolar 2015). Lisboa: Direcç,ão-Geral de Saúde (DGS).

Appalachian State University, n.d. “EcoSensors for Mountain Classrooms program,” at https://sites.google.com/site/appecosense/home, accessed 5 November 2019.

S.L. Austin, 2010. “Children’s participation in citizenship and governance,” In: B. Percy-Smith and N. Thomas (editors). A handbook of children and young people’s participation: Perspectives from theory and practice. New York: Routledge, pp. 245–253.

T.R. Baker, S. Battersby, S.W. Bednarz, A.M. Bodzin, B. Kolvoord, S. Moore, D. Sinton, and D. Uttal, 2015. “A research agenda for geospatial technologies and learning,” Journal of Geography, volume 114, number 3, pp. 118–130.
doi: https://doi.org/10.1080/00221341.2014.950684, accessed 21 February 2020.

T. Bartoschek and C. Keßler, 2013. “VGI in education: From K-12 to graduate studies,” In: D. Sui, S. Elwood, and M. Goodchild (editors). Crowdsourcing geographic knowledge: Volunteered geographic information (VGI) in theory and practice. Dordrecht: Springer, pp. 341–360.
doi: https://doi.org/10.1007/978-94-007-4587-2_19, accessed 21 February 2020.

H. Brandt, G.M. Simmie, A. Zeidler, and P. Vassbotn, 2011. “Data logging in science,” European Commission Education and Culture DG, at https://www.ucviden.dk/portal/files/45515409/Data_Logging_in_Science.pdf, accessed 16 January 2019.

C.A. Chinn and B.A. Malhotra, 2002. “Epistemologically authentic inquiry in schools: A theoretical framework for evaluating inquiry tasks,” Science Education, volume 86, number 2, pp. 175–218.
doi: https://doi.org/10.1002/sce.10001, accessed 21 February 2020.

A. Damasio, 2003. Looking for Spinoza: Joy, sorrow, and the feeling brain. Orlando, Fla.: Harcourt.

C. Eberbach and K. Crowley, 2009. “From everyday to scientific observation: How children learn to observe the biologist’s world,” Review of Educational Research, volume 79, number 1, pp. 39–68.
doi: https://doi.org/10.3102/0034654308325899, accessed 21 February 2020.

C.R. Ergler, R. Kearns, K. Witten, and G. Porter, 2016. “Digital methodologies and practices in children’s geographies,” Children’s Geographies, volume 14, number 2, pp. 129–140.
doi: https://doi.org/10.1080/14733285.2015.1129394, accessed 21 February 2020.

I. Eriksson and V. Lindberg, 2016. “Enriching ‘learning activity’ with ‘epistemic practices’ — Enhancing students’ epistemic agency and authority,” Nordic Journal of Studies in Educational Policy, volume 2016, number 1, article 32432.
doi: https://doi.org/10.3402/nstep.v2.32432, accessed 21 February 2020.

J. Evans-Cowley, 2010. “Planning in the real-time city: The future of mobile technology,” Journal of Planning Literature, volume 25, number 2, pp. 136–149.
doi: https://doi.org/10.1177/0885412210394100, accessed 21 February 2020.

M. Fenton, 2008. “Authentic learning using mobile sensor technology with reflections on the state of science education in New Zealand: A research project for the New Zealand Ministry of Education,” at https://www.core-ed.org/assets/Uploads/UploadsVince-Ham-eFellowships/Michael-Fenton-Authentic-learning-using-mobile-sensor-technology.compressed.pdf, accessed 21 February 2020.

J. Fraden, 2010. Handbook of modern sensors: Physics, designs, and applications. New York: Springer-Verlag.
doi: https://doi.org/10.1007/978-1-4419-6466-3, accessed 21 February 2020.

Globe Program, 2019. “GLOBE by the numbers,” at https://www.globe.gov/, accessed 5 November 2019.

Globe Program, 2018. “The GLOBE Program: Global learning and observations to benefit the environment,” at https://www.globe.gov/, accessed 19 January 2019.

P.H. Henning, 2004. “Everyday cognition and situated learning,” In: D.H. Jonassen (editor). Handbook of research on educational communications and technology. Mahwah, N.J.: Lawrence Erlbaum, pp. 143–168.

J. Madureira, I. Paciência, E. Ramos, H. Barros, C. Pereira, J.P. Teixeira, and E. de Oliveira Fernandes, 2015. “Children’s health and indoor air quality in primary schools and homes in Portugal — Study design,” Journal of Toxicology and Environmental Health, Part A: Current issues, volume 78, numbers 13–14, pp. 915–930.
doi: https://doi.org/10.1080/15287394.2015.1048926, accessed 21 February 2020.

L. Pereira, D. Raimondo, S. Corgnati, and M. Gameiro da Silva, 2014. “Assessment of indoor air quality and thermal comfort in Portuguese secondary classrooms: Methodology and results,” Building and Environment, volume 81, pp. 69–80.
doi: https://doi.org/10.1016/j.buildenv.2014.06.008, accessed 21 February 2020.

T. Plomp, 2010. “Educational design research: An introduction,” In: T. Plomp and N. Nieveen (editors). An introduction to educational design research. Enschede: Netherlands Institute for Curriculum Development (SLO), pp. 9–35, and at https://ris.utwente.nl/ws/portalfiles/portal/14472302/Introduction_20to_20education_20design_20research.pdf, accessed 21 February 2020.

G. Salomon and D.N. Perkins, 1998. “Individual and social aspects of learning,” Review of Research in Education, volume 23, number 1, pp. 1–24.
doi: https://doi.org/10.3102/0091732X023001001, accessed 21 February 2020.

J. Schneider, D. Börner, P. van Rosmalen, and M. Specht, 2015. “Augmenting the senses: A review on sensor-based learning support,” Sensors, volume 15, number 2, pp. 4,097–4,133.
doi: https://doi.org/10.3390/s150204097, accessed 21 February 2020.

K. Sherwin and J. Nielsen, 2019. “Children’s UX: Usability issues in designing for young people,” Nielsen Norman Group (13 January), at https://www.nngroup.com/articles/childrens-websites-usability-issues/, accessed 23 January 2019.

M.J. Silva, E. Ferreira, A. Souza, and A.R. Alves, 2018a. “Eco-Sensors4Health Toolkit: Scaffolding children participation in schools environmental health,” Proceedings of GLOBAL HEALTH 2018, Seventh International Conference on Global Health Challenges, pp. 47–52, and at https://www.thinkmind.org/index.php?view=article&articleid=global_health_2018_4_10_70026, accessed 21 February 2020.

M.J. Silva, E. Ferreira, A. Souza, A.R. Alves, P. Rito, and C. Gomes, 2018b. “Beyond technology, through research in education: The collaborative situated design of an environmental health education platform,” Proceedings of the 2018 International Symposium on Computers in Education (SIIE).
doi: https://doi.org/10.1109/SIIE.2018.8586699, accessed 21 February 2020.

M.J. Silva, E. Ferreira, A. Souza, A.R. Alves, and S. Batista, 2018c. “Using eco-sensors to support children’s participation in environmental health,” International Journal of Digital Literacy and Digital Competence, volume 9, number 4, pp. 33–45.
doi: https://doi.org/10.4018/IJDLDC.2018100103, accessed 21 February 2020.

M.J. Silva, J.B. Lopes, and A.A. Silva, 2013. “Using senses and sensors in the environment to develop abstract thinking — A theoretical and instrumental framework,” Problems of Education in the 21st Century, volume 53, pp. 99–119, and at http://www.scientiasocialis.lt/pec/node/826, accessed 21 February 2020.

M.J. Silva, J.C. Lopes, P.M. de Silva, and M.J. Marcelino, 2010. “Sensing the schoolyard: Using senses and sensors to assess georeferenced environmental dimensions,” COM.Geo ’10: Proceedings of the First International Conference and Exhibition on Computing for Geospatial Research & Application, article number 40, pp. 1–4.
doi: https://doi.org/10.1145/1823854.1823899, accessed 21 February 2020.

M.J. Silva, C.A. Gomes, B. Pestana, J.C. Lopes, M.J. Marcelino, C. Gouveia, and A. Fonseca, 2009. “Adding space and senses to mobile world exploration,” In: A. Druin (editor). Mobile technology for children: Designing for interaction and learning. Boston: Morgan Kaufmann, pp. 147–169.
doi: https://doi.org/10.1016/B978-0-12-374900-0.X0001-4, accessed 21 February 2020.

J. van de Pol, M. Volman, and J. Beishuizen, 2010. “Scaffolding in teacherstudent interaction: A decade of research,” Educational Psychology Review, volume 22, number 3, pp. 271–296.
doi: https://doi.org/10.1007/s10648-010-9127-6, accessed 21 February 2020.

E. van den Berg, F. Schweickert, and R. van den Berg, 2010. “Science, sensors and graphs in primary schools,” Proceedings of the GIREP Conference 2010, pp. 1–9, and at https://www.iederkindeentalent.nl/wp-content/uploads/2012/06/sciencesensors1.pdf, accessed 21 February 2020.

J. van der Schee, H. Trimp, T. Béneker, and T. Favier, 2015. “Digital geography education in the twenty-first century: Needs and opportunities,” In: O. Muñiz Solari, A. Demirci, and J.A. van der Schee (editors). Geospatial technologies and geography education in a changing world: Geospatial practices and lessons learned. Tokyo: Springer, pp. 11–20.
doi: https://doi.org/10.1007/978-4-431-55519-3_2, accessed 21 February 2020.

P. Woolner and E. Hall, 2010. “Noise in schools: A holistic approach to the issue,” International Journal of Environmental Research and Public Health, volume 7, number 8, pp. 3,255–3,269.
doi: https://doi.org/10.3390/ijerph7083255, accessed 21 February 2020.

World Health Organization (WHO), 2018. “Health topics: Environmental health,” at https://www.who.int/westernpacific/health-topics/environmental-health, accessed 26 April 2018.

World Health Organization (WHO), 2015. “School environment: Policies and current status,” at http://www.euro.who.int/__data/assets/pdf_file/0009/276624/School-environment-Policies-current-status-en.pdf, accessed 16 January 2019.

A.A. Zucker, R. Tinker, C. Staudt, A. Mansfield, and Shari Metcalf, 2008. “Learning science in grades 3-8 using probeware and computers: Findings from the TEEMSS II Project,” Journal of Science Education and Technology, volume 17, number 1 pp. 42–48.
doi: https://doi.org/10.1007/s10956-007-9086-y, accessed 21 February 2020.

 


Editorial history

Received 2 February 2019; revised 10 November 2019; accepted 23 January 2020.


CC0
To the extent possible under law, Maria João Silva has waived all copyright and related or neighboring rights to “Children using electronic sensors to create and use knowledge on environmental health”. This work is published from Portugal.

Children using electronic sensors to create and use knowledge on environmental health
by Maria João Silva.
First Monday, Volume 25, Number 3 - 2 March 2020
https://journals.uic.edu/ojs/index.php/fm/article/download/9646/9401
doi: http://dx.doi.org/10.5210/fm.v25i3.9646