1. Introduction
The concept of sustainability has emerged as a pivotal concern in today’s society (Intergovernmental Panel on Climate Change, 2023). While sustainability is based on the three pillars of social, economic and ecological sustainability, recent years have seen a notable shift in focus towards the ecological aspects. The actions taken today by individuals and companies will have an impact on the world in years to come, thereby underscoring the necessity of a more profound comprehension of sustainable practices among the general population (Reference Waas, Hugé, Verbruggen and WrightWaas et al., 2011). While tools and methods to quantify the sustainability of a given product, such as Life Cycle Assessment (LCA) or Product Carbon Footprint (PCF) calculation, have gained popularity and are being adopted by industry, the impacts of products are, if published at all, often presented as a mere number without context, which is often beyond the comprehension of the public (Čuček et al., Reference Čuček, Klemeš and Kravanja2012; Finkbeiner et al., Reference Finkbeiner, Schau, Lehmann and Traverso2010; Gutwald et al., Reference Gutwald, Baumann, Funk, Reichenstein, Albayrak and Franke2024; Hauschild et al., Reference Hauschild, Rosenbaum and Olsen2018). Nevertheless, a fundamental comprehension of the consequences of the products we utilize daily is imperative to facilitate the changes to enable a more sustainable world. Since the actions of the present will have ramifications in the future, it is of particular importance that young people possess a more profound understanding of sustainability and its assessment to enable them to make sustainable decisions, to balance sustainability-related trade-offs and to minimize rebound-effects.
Gamification has been demonstrated to be an effective method for facilitating comprehension of complex topics, enhancing motivation and engagement in learning, and communicating the subject of sustainability in an accessible manner (Reference KappKapp, 2012).
Motivated by this, this paper describes the design of a demonstrator having the objective of visualizing the connections between various product parameters, design decisions, and the resulting environmental impact. The demonstrator is aimed at children between the ages of 8 and 12, presenting additional challenges in terms of the suitability of the topic and content for this age group.
The objective of the learning process was to convey that decisions about our own actions have consequences with regard to environmental aspects. However, it was also emphasized that we, as actors, have the opportunity to contribute to a more sustainable world through our own actions.
This paper begins by outlining the theoretical foundation of the methods employed. It then identifies the requirements and boundary conditions and defines the scope of the developed app. The structure and development of the demonstrator is then presented. Finally, the developed work is subjected to critical reflection, and potential avenues for future expansion are discussed.
2. State of the art
The challenge of limiting global warming is one of the most important issues of our time, with implications for future generations. A key objective is to reduce the emission of greenhouse gases (GHG), that contribute to global warming (Intergovernmental Panel on Climate Change [IPCC], 2023). Research is therefore focused on quantifying the environmental impact of products and deriving strategies to reduce it. The environmental impact of a product can be significantly influenced at the product development stage. This is because, among other factors, decisions are made about materials and manufacturing processes, which have a considerable impact on the subsequent characteristics of the product (Reference He, Wang, Huang and WangHe et al., 2015). In this context, the Product Carbon Footprint (PCF) plays an instrumental role, as it can map the climate impact of a product based on its entire life cycle (International Organization for Standardization [ISO], 2006a).
In addition to the aforementioned applications, this approach can be employed to conduct a hotspot analysis, which can be utilised to identify the principal drivers of the product’s climate impact. This can then be employed to reduce the climate impact in the most targeted manner possible (Reference Hetherington, Borrion, Griffiths and McManusHetherington et al., 2014). However, such assessments are inherently complex, as they necessitate the formulation of numerous assumptions, the application of specific calculation methods, the contextualisation of results within the framework of previously established boundary conditions, and the communication of findings in the form of CO2 equivalents (CO2e), which is often perceived as abstract and challenging for non-experts, let alone for children, to comprehend or interpret (Reference Hauschild, Rosenbaum and OlsenHauschild et al., 2018).
Gamification has become a well-established method for communicating complex processes and fostering comprehension of them. The term “gamification” is used to describe the incorporation of elements typically associated with games into a context that is not inherently game-like. This approach has the potential to motivate users to engage with complex topics, particularly in the case of children, who may be encouraged to take on additional initiative as a result of the increased interaction with a given topic (Reference KappKapp, 2012).
The combination of gamification and life cycle assessment using the PCF offers a promising avenue for instilling in children the understanding that they can significantly influence the environmental impact of their actions by making informed decisions. Consequently, the current state of the art in both topics is highlighted in the following.
2.1. Life cycle assessment and product carbon footprint
Life Cycle Assessment (LCA) is a method that enables users to assess and evaluate the environmental impacts of a product, process or service. The ISO 14040 standard (ISO, 2006a) describes the principles and procedures of LCA while the ISO 14044 standard (ISO, 2006b) provides detailed requirements and guidelines for conducting LCAs. To perform an LCA, it is first necessary to identify and quantify the energy and resource use of the subject of the assessment. Once this is done, it is then possible to assess and quantify the different environmental impacts caused. The life cycle stages of a product typically include the extraction of raw material, manufacturing and processing, the distribution and transportation, the utilisation and their end of life. Users will have to perform a goal and scope definition first, during which the objectives, boundaries and assumptions are set, followed by an Inventory Analysis, where data on in- and outputs of the assessed subject are collected. Following these first two steps a Life Cycle Impact Assessment (LCIA) can then be conducted, which evaluates potential environmental impacts like carbon emissions, pollution or ground use. As a final step, the results of the study are then interpreted (ISO, 2006a).
While LCA encompasses a multitude of environmental impacts, the calculation of the PCF only refers to the emissions of GHG that are quantified as a singular value in the form of Carbon Dioxide Equivalents (CO2e). Consequently, the calculation of the PCF represents an LCIA and not a comprehensive LCA. The process of conducting an LCIA largely mirrors that of an LCA (ISO, 2006b). Nevertheless, given the established link between GHG emissions and global warming (IPCC, 2023), the PCF provides a valuable means of gauging the climate impact of a given subject.
2.2. Gamification
Gamification is the usage of game elements and mechanics in a non-game context to increase motivation and engagement of the users. This is achieved by creating a more attractive and interesting environment for activities, tasks or processes. It can also trigger behavioural changes. Kapp (Reference Kapp2012) describes it as follows:
““Gamification” is using game-based mechanics, aesthetics, and game-thinking to engage people, motivate action, promote learning, and solve problems.”
Heininger et al. (Reference Heininger, Prifti, Seifert, Utesch and Krcmar2017) conducted a literature review and identified a number of success factors. The motivation and enthusiasm by the user to learn is the first identified success factor and can be addressed by gamification, which can help increase motivation to engage with complex topics. Integration and involvement are other important factors that can also be aided by gamification, as game elements can motivate users to tasks that would normally be seen as unpleasant. Another success factor of gamification is the adaption to the audience, as they are usually targeted towards a specific audience and complexity and mechanics are adapted to the target group of users. The fourth success factor is interaction and feedback, which describes the fact that the user usually receives near to instant feedback regarding his actions and inputs. Finally, the integration of educational content into the gamified experience is important, as this determines whether or not the user is actually able to learn something by interacting with the application.
Brewer et al. (Reference Brewer, Anthony, Brown, Irwin, Nias, Tate, Hourcade, Sawhney and Reardon2013) find that gamification can be beneficial when conducting empirical studies with children. The authors advise to use gamification elements, personalize motivational elements, avoiding sessions with children that already know each other and to allow some albeit balanced and purposeful distractions, adding that the gamified elements helped motivate the children.
2.3. Gamification in the context of sustainability and the product carbon footprint
Prijardashini et al. (Reference Priyadarshini, Nishane, Pokle, Khwaja and Dasgupta2021) developed a game designed to assist students in evaluating their daily routines in terms of CO2e emissions. This is achieved through the completion of a list of questions. Subsequently, the responses are then contextualised by displaying the resulting emissions and by comparing them to the other options that the user did not select. Moreover, the response is rewarded with points based on its sustainability in comparison to the other potential solutions. Similarly, Md Nor and Abdul Hadi (Reference Md Nor and Abdul Hadi2016) developed a calculator with the objective of assisting children in comprehending the impact of their daily routines on on CO2e emissions. The tool is specifically designed for children in Malaysia, as daily routines and emission factors vary considerably depending on the region in which the participants reside. The authors observe that their project contributed to the creation of awareness regarding climate change among their participants. However, they identify a limitation in the platform’s provision of information regarding the explanation and meaning of the results.
Beside this, Arnemann et al. (Reference Arnemann, Galera, Winter and Schleich2024) developed a framework that receives live production data from the corresponding machines, calculates the PCF and incorporates gamification elements to contextualise sustainability aspects of production for both professional and non-professional users.
However, in synthesis, though gamification has already been used in the context of design for sustainability and related teaching, there is a lack of a suitable gamification approaches for children. Motivated by this lack, the following sections highlight the conceptualization and development of a design for sustainability demonstrator for younger kids.
3. Conceptualization and development of the demonstrator
Considering the state of the art, the development of the demonstrator can now be initiated. In the initial phase, fundamental requirements were identified, followed by a theoretical conceptualisation and the formulation of an information model. Subsequently, the actual demonstrator is then developed.
3.1. Requirements and limitations
The demonstrator was developed for an open, which was aimed at children. In this context, the following limitations and requirements were derived:
1. It is anticipated that 200 children would attend the event in four 90-minute time slots
2. The event is designed for children between the ages of 6 and 12
3. The demonstrator will utilise a rocket, that can be configured and launched into space. The rocket will be approximately the size of a person.
4. One large smartboard is available for use during the open day
Based on these limitations, requirements and findings of the literature review presented in section 2, it is possible to derive and detail further requirements:
5. In order to provide each child with the opportunity to complete the experiment at least once, the duration of the challenge should be limited to approximately 90 seconds.
6. Given the limited time frame and the relatively complex subject matter, the interface must be designed with simplicity as a core principle
7. A counselor will be present to provide additional explanations or information as required
8. The children will be arranged in a queue to participate in the experiment. They will be able to observe and learn from the child in front of them as they demonstrate the basic principles of the experiment
9. The results of the experiment must be readily comprehensible and contextualised
10. Given the age gap, it is imperative to consider the varying degrees of comprehension among the participants. It is essential that all children are able to successfully complete their assigned experiment, even with a limited grasp of the sustainability concepts
11. Given the age of the children, it cannot be assumed that all the participants are able to read
12. It is essential that the interface allows for the interaction of different parameters, which can be selected by the users
13. It is necessary to provide an accompanying experiment that can be completed by the children during the waiting perios, as only one child can use the smart board at any given time
This list of requirements and limitations will subsequently be used to conceptualise the demonstrator.
3.2. Theoretical concepts
As mentioned in requirement 3, the demonstrator should utilise a rocket that is launched into space. This scenario is used to frame the learning experience in an exciting story that captures the children’s attention. In consideration of the rocket example, it is determined that the parameters selected by the user should include the material of a specified number of parts, the type of fuel utilised for the rocket launch, and the site of the launch, as these factors interact with one another. The selection of materials will consequently determine the weight of the empty rocket and thus the quantity of fuel required for the rocket launch. Furthermore, the energy density of the fuel will also influence the total system weight of the rocket. The total system weight will in turn influence the amount of CO2e emissions during the transport to the selected launch site. This interaction creates a level of complexity that can create an additional challenge for the more advanced, older users while it is not necessary to fully master this concept in order to successfully complete the experiment presented by the demonstrator.
As a physical experiment is to be conducted in conjunction with the digital experiment, it is essential that the rocket can be disassembled into individual parts, which must be straightforward for users to assemble but can also be readily varied. In order to maintain simplicity in the digital interface and keep completion times of the digital experiment fast, it is reasonable to allow the user to choose four different parameters of the rocket, with each parameter displayed on one of the four sides of the rocket. One parameter is the type of fuel used for the launch, therefore a maximum of three individual rocket parts whose material can be changed by the user remains. The material and fuel choices shall be represented in graphical form to create an engaging user experience and enable all users to create their own rocket, regardless of their ability to read.
Once the materials and fuel type have been selected, the user is then presented with a list of potential sites for the rocket launch. The locations should differ in terms of their latitude, resulting in significant differences regarding the fuel required. The Earth’s ground speed is higher near the equator, which means that the rocket requires less energy and therefore less fuel to launch than at locations with lower ground speeds. Furthermore, the launch sites will necessitate the transportation of the rocket to the selected location by different means of transport (MOT), introducing an additional layer of complexity to the problem.
The PCF calculation will be divided into three stages. The first will consider the CO2e emissions resulting from the material choices for the rocket parts, the second will examine the CO2e emissions associated with the necessary fuel, and the third will evaluate the CO2e emissions caused by the transportation of the rocket including the fuel, to the selected launch site. The specific emission factors (SEF) required for the calculation of the PCF from the mass of material, fuel or length and weight of transport will be sourced from an eco-database, whereas other parameters like material density, fuel (energy-)density or the latitude of the selected potential launch sites will be sourced from literature.
Figure 1 details how user choices interact with each other and how the PCF of the rocket launch including the rocket itself, the required fuel and transport to the launch site can be calculated.
Concept of the information flow for the digital demonstrator
Subsequently, the results will then be presented to the user in a manner that is readily comprehensible and interpretable by children.
3.3. Practical implementation
This section describes the implementation of the presented concept. As previously outlined in section 3.1, it is both feasible and beneficial to supplement the digital demonstrator with a physical experiment. This approach has the potential to reduce the waiting time for the experiment and provide children with initial insights into the consequences of the material selection, particularly in terms of product weight, before they start their attempt at the experiment. To this end, a hybrid demonstrator, combining digital and physical elements, is developed.
3.3.1. Physical demonstrator
As previously outlined, the rocket will be constructed in three sections, which dimensions sufficient to prevent injury to the children while allowing for straightforward assembly and disassembly. The three derived parts are the main skeleton, the hull and the tip of the rocket, as they can be readily varied and assembled. The main skeleton of the rocket comprises the tail, the stabilisers and the internal supporting structure. The hull is tube with a specified inner diameter, which allows for the straightforward realisation of different materials and be stacking on the main skeleton. Finally, the rocket tip can be threaded onto the skeleton, keeping the hull from moving around. Thereby, the assembly of the full rocket is enabled in only two steps. Based on considerations, a design is created in CAD software. The main skeleton and the tip are 3D-printed in both polymer and stainless-steel variants while the hull is 3D-printed in a polymer variant and cut from tubes out of stainless steel, aluminium and carbon fibre-reinforced plastic. This allows for a variety of materials with differing densities to be employed, thereby demonstrating to users how the impact of material selection on the overall weight of the finished product. The developed physical demonstrator is illustrated in Figure 2, depicting both the CAD modell and physical variants.
Left: CAD model displaying the main skeleton, the tip and the hull of the rocket; Right: Physical parts, different coloured 3D-printed rocket parts from polymer and stainless steel and tubes cut to length from stainless steel, aluminium and carbon fibre
3.3.2. Digital demonstrator
The development of the digital part of the demonstrator will entail the completion of two principal tasks. Initially, the theoretical concept will be translated into a fundamental user workflow, encompassing both the mathematical functions and data aggregation for the PCF calculation. Subsequently, a frontend will be created, enabling the user to make the envisaged selections and communicate them to the backend, which is based on the aforementioned workflow.
To develop the digital demonstrator the collection of the data for the specified parts, potential material and fuel type choices and launch sites is necessary. A total of four datasets are then created, comprising one for the rocket parts, another for the material choices, a third for fuel type choices and a fourth for the launch site options. The four datasets, together with their respective contents, are displayed in table 1.
Overview of the datasets established for the practical implementation
In order to determine the volume of the predefined rocket parts the CAD model of the physical demonstrator is scaled to a height of two metres, based on the requirement of the rocket being the size of a person. The volume of the parts is then measured in the CAD Software and saved.
The geometry of the individual components is not adapted according to the material, the corresponding load-bearing capacity or possible manufacturing processes, which represents a significant simplification but it maintains a manageable complexity, which is particularly relevant in the context of short throughput times. This approach eliminates the need for further explanations regarding manufacturing and ensures that users can readily comprehend the interface.
The selected materials are consistent with those presented in the physical demonstrator, comprising various types of metal, carbon fibre-reinforced plastics, an engineering-grade polymer and wood as an additional option. Although these materials are not typically used for the selected rocket parts, they create a direct link between the physical and digital parts of the demonstrators. Moreover, the explanation of advanced materials, such as highly temperature-resistant ceramics, would be challenging to convey within the limited time available for children to complete their experiment. The CO2e emissions of the three rocket parts made from the respective materials are then calculated by multiplying their volume, density and the SEF as detailed in the concept section. All SEF are taken from the ecoinvent database as described by Wernet et al. (Reference Wernet, Bauer, Steubing, Reinhard, Moreno-Ruiz and Weidema2016).
Following the material selection, the user is presented with the option of selecting a fuel type for the rocket. The user can choose the solid rocket propellant HTPB, methane, hydrogen and electricity provided by lithium-ion-batteries. These options, however, only partially reflect the current state of the art in spacecraft engineering. Nevertheless, we consider it important to include popular fuel types in the automotive sector, as children are already familiar with these options.
The subsequent step is the selection of the launch site. Here, the user is presented with three options. The first one is the City of Darmstadt where the open day is hosted. It is assumed that this is also the location where the rocket is built, eliminating the need for further transportation of the rocket. The second location is the spaceport in Kourou, French-Guyana. This necessitates transportation from Darmstadt, Germany to Rotterdam, Netherlands by train and then subsequently by ship to the destination in southern America. The third option was the cosmodrome in Baikonur, Kazakhstan, which requires transportation by train. The distances traveled by train were estimated using the BRouter online tool, whereas the distance traveled by ship was estimated using Google Maps.
The Russian Soyuz V rocket was launched from both spaceports in French-Guyana and Kazakhstan in the past and can therefore be used to estimate the amount of energy needed that would be required to launch the rocket configured by the user. The possible payloads per location and the weight of the Soyuz V rocket to Geostationary transfer orbit for both spaceports where then used to estimate the required energy per kg of mass for both locations. This estimation was subsequently extrapolated to the latitude of the third launch site of Darmstadt. A Latitude Correction Factor (LCF) was then calculated comparing the possible payload at all three locations to simplify calculations in the demonstrator. This constitutes a further simplification of the estimation process but is necessary to regulate complexity and keep calculation times as low as possible. With this data and the energy density of the selected fuel type, the mass and the CO2e emissions of the chosen fuel required can then be calculated.
The mass of the rocket consisting of the mass of the rocket parts and the fuel is then added together and multiplied with the distance travelled by each means of transport and their corresponding SEF to calculate CO2e emissions caused by transportation.
The total CO2e emissions resulting from the user’s selected options can then be calculated and displayed. To provide further context for the user, in this case children, the amount of CO2e emitted by the rocket launch is converted into the number of trees that would be necessary to remove the equivalent amount of CO2 from the atmosphere. These approaches are the subject of ongoing debate, as they represent further simplification and do not necessarily facilitate improved understanding (Reference Mohanty, Filipowicz, Bravo, Carter, Shamma, Schmidt, Väänänen, Goyal, Kristensson, Peters, Mueller, Williamson and WilsonMohanty et al., 2023; Reference Vizzoto, Testa and IraldoVizzoto et al., 2021). Furthermore they can be employed for the purpose of greenwashing (Reference Michael, Stacy and RomanaMichael Jay Polonsky et al., 2010). However, these approaches also represent a simplified solution and basis for interpretation for non-experts and can facilitate individual action, like planting trees to compensate ones one emissions (Reference Mora Rollo, Rollo and MoraMora Rollo et al., 2020). In addition to the number of trees, which is also visually represented in the app the calculated value of CO2e emissions, and their contributors are displayed as a numeric value, enabling further analysis of the results.
To maintain simplicity and intuitiveness regarding user interaction, a touch interface is employed for all input operations. As the demonstrator is intended to be accessible on a range of devices, a webpage format has been selected. The structure of the webpage is defined by HTML, while CSS is used for styling and layout. JavaScript is employed as the backend programming language. Figure 3 illustrates the combination of HTML, CSS and JavaScript. The HTML and CSS code determines the visual appearance of the webpage, while JavaScript executes the functions for calculating the PCF and sends out instructions on visual changes, such as the update of the rocket graphic. JavaScript thus serves as the brain of the demonstrator. The .containers{} functions used in CSS mainly contain information of the placement, size, color and style of the assigned HTML item. Upon opening the webpage, the user is presented with a visual representation of the defined items, accompanied by instructions and images of the preselected materials for the rocket parts and fuel types. The selection of construction materials for specific rocket components and fuel type is facilitated by a drag-and-drop operation, whereby the corresponding image is placed onto the central container. The central container, which initially displays the rocket outline, is subsequently populated with textures indicative of the chosen material or fuel type.
Left side showing the CSS functions for styling and visualization, right side JavaScript functions used to define all the actions
The code comprises five functions, defined with the objective of achieving the desired functionality and maintaining the desired level of robustness. Figure 3 illustrates that the functions dragStart(e) and dragEnd(e) appear to replicate the function performed indirectly by touchStart(e) and touchEnd(e). This is done to enable both touch-based and computer mouse input. The touchStart(e) function initiates the calculation of the coordinates of the dragged image as soon as any touch point on the screen is activated. The touchMove(e) function performs several key functions, including maintaining the size of the texture item and updating the coordinate position of the item. The touchEnd(e) function reports the coordinates of the point at which the touch ended. This information is then fed into the function getClosestSnapPoint(x, y) to determine the position of the image on the central rocket container. The function touchEnd(e) extracts the data attributes of the moved item and assigns the corresponding material to the given rocket part. To facilitate the selection of the optimal launch location, the three potential launch sites and their associated data attributes are presented in the form of buttons, accompanied by a visual representation of the transportation route to the selected launch site. Upon selecting a specific launch site by means of a button, the data attributes of that site are automatically selected for the calculation of CO2e emissions.
The launch button triggers the calculation of the PCF, resulting in the display of the numerical value of CO2e emissions and the corresponding number of trees. The launch button is displayed prominently to add an additional element of gamification, enabling the user to launch the rocket they configured into space. The completed app is displayed in Figure 4.
Completed app; Left: Choice of materials and fuel type; Centre: Choice of launch site; Right: Results including the rendered number of trees required to offset the CO2e emissions
4. Use Case, evaluation and critical discussion
At the open day, the developed demonstrators were subjected to testing by around 200 children. As anticipated, a queue formed, and the hypothesis that children could learn the fundamental principles of the demonstrator was validated. It was, however, imperative to maintain constant supervision of both demonstrators, with a particular emphasis on providing supplementary information. While younger children were primarily engaged in creating a visually appealing rocket, older children attempted to develop optimal solutions and minimize CO2e emissions, sometimes queuing multiple times to refine a specific strategy. One participant attempted to maximize emissions, after he had reached the minimal amount possible, persistently seeking guidance and suggestions from the experiment supervisors.
In relation to the stated objectives and requirements, these were all achieved, although not without some limitations. The time required by individual users varied, with some requiring more than the anticipated 90 seconds and others requiring less. The objective of learning the fundamental principles of the demonstrator from the children in front was achieved. However, some children who had already completed the task encouraged others to follow their example or alter specific parameters, which may have affected the learning outcome for other participants. Furthermore, it was imperative to ensure the continuous presence of a supervisor, as the material and fuel type options were not adequately explained. This issue could be addressed by ranking the materials according to their density or other relevant parameters, or by incorporating more gamification elements into the process of selecting materials. For instance, the movement of denser materials could be slowed down, thereby enhancing the level of immersion. Additionally, it is uncertain whether the children were able to gain genuine insights into sustainability, given the difficulty in applying this example to everyday products. Furthermore, some technical issues did arise. These included cases where children were not big enough to move items to the desired location and instances where the touchscreen was accidentally triggered by bracelets touching it.
There are also number of further improvements. The chosen product for example is not ideal, as the material and fuel type choices are not really suited for a rocket given the extreme operating conditions real rockets would endure during their flight, whereas suitable materials would be hard to explain to children with no further background knowledge. Another aspect is the choice of materials in relation to the geometric model of the product, in this case the rocket. Currently, the model remains unaffected by the choice of material, i.e. the only relevant material parameter is the density, while other parameters such as the strength of the material are not considered. A similar aspect is the manufacturing of the components. Currently, only the required material is considered without production losses or costs. It seems reasonable to define one or more possible manufacturing processes for each material/geometry combination, add another level of complexity and give the user more options to choose from. In the context of the short timeframes for the challenge and the explanation effort for children, this was not possible for the current project, but it would be an option to refine the demonstrator accordingly and add such an extension as an “expert mode” for more advanced or older users. Furthermore, more gamification elements can be added, like animations for the rocket launch, the transport modes, the chosen fuel types or materials to increase immersion and engagement of the users.
5. Conclusion
Driven by the increasing relevance of design for sustainability and the need to raise awareness for sustainable design and consuming decisions, this paper describes the conceptualization and implementation of a gamification-based learning tool for children, which is intended to visualize the relations between product parameters, design decisions, and the resulting environmental impact. This demonstrator is arranged around the story of a rocket that that should be launched to space and allows children in the ages between 6 and 12 to vary different rocket materials, fuel types and launch sites for their rocket and to assess the effects of their choices on the product carbon footprint. The application of the demonstrator in the context of an open day revealed positive feedback and some ideas for further improvements. In conclusion, this demonstrator is one of very few examples and approaches to inspire children for design for sustainability in engineering and may foster the scientific discussion about adequate learning demonstrators and materials for children in this domain.
Open access
