Abstract
A smart bracelet that reacts to a person's heartbeat. A smart bench that invites passers-by to sit close. These and others are smart things, part of the Internet of Things (IoT) and people's lives. However, people are mainly IoT consumers and rarely given the possibility of becoming IoT creators. This paper presents a case study concerning the design of smart things for outdoor environments, with end users as the main creators. Ideas of smart things were collaboratively conceptualised by child end-users with a card-based board game. Their ideas were taken up in the form of inspiration cards within a bachelor's first-year course, by students coming from different high schools. Students started from children's ideas as inspiration triggers and collaboratively evolved some of them into interactive smart-thing prototypes. The paper concludes by reflecting on its results and drawing lessons for future editions of cross-generational workshops related to IoT design with end users.
| Original language | English |
|---|---|
| Pages (from-to) | 3281-3300 |
| Number of pages | 20 |
| Journal | Behaviour and Information Technology |
| Volume | 41 |
| Issue number | 15 |
| Early online date | 2 Oct 2021 |
| DOIs | |
| Publication status | Published - 18 Nov 2022 |
Keywords
- design thinking
- design toolkit
- end user development
- Internet of things
- IoT
- smart thing
ASJC Scopus subject areas
- Developmental and Educational Psychology
- Arts and Humanities (miscellaneous)
- General Social Sciences
- Human-Computer Interaction
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In: Behaviour and Information Technology, Vol. 41, No. 15, 18.11.2022, p. 3281-3300.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - From children's ideas to prototypes for the internet of things
T2 - a case study of cross-generational end-user design
AU - Gennari, Rosella
AU - Melonio, Alessandra
AU - Rizvi, Mehdi
N1 - Funding Information: The results of the reported design process are positive but with limitations. In particular, the design process reported in this paper is designed as a case study. However, in order to draw general conclusions concerning the effectiveness of the design approach and toolkits, it would take an experiment with a controlled group. Nevertheless, the reported work gives indications about the effectiveness of the design approach and toolkits, which can be evaluated in future experiments. Another limitation is related to the design toolkit used by children. The programming and prototyping part was missing in that toolkit: having it in the toolkit might have enabled children to prototype their own ideas and to carry the resulting prototypes into the design process with university students. Recent design workshops with SNaP and children indeed included programming and prototyping tools within the design toolkits for children (Gennari et al. 2021). Future work will try bringing children's prototypes into the design process with university students and study how these are appropriated and may evolve. Moreover, future editions of the course will try investigating with questionnaires the sense of empowerment that students expressed and was documented in a qualitative manner in the work reported in this paper. The paper reported a case study, concerning a design process of smart things with end users–school-age children, university freshers. The process started with children and continued with students. None of them had any prior experience of design and the majority had no experience of programmable microelectronics. The process adopted a design-thinking approach with different workshops, for moving the design of smart things from exploration, ideation into programming and prototyping. The design toolkits for children and students had tools shared between generations, but they had also different tools per generation. Toolkits are reported in the paper and compared across generations. In particular, shared tools were cards for representing things of the common environment to make smart, input and output devices for making things smart, and mission cards for design goals. Students had also further cards, to account for the complexity of the things they could design, and for developing some of children's imagined inputs and outputs. Both children and university students had a conceptualisation framework at their disposal, where they placed cards related to their idea of smart things and described them. However, the framework was different in complexity for children and university students, adapted to their different needs. The major contribution of the paper is thus the case study itself. Its results indicate that the design approach and toolkits enabled the sharing of smart-thing design across generations: students appropriated ideas of smart things by children, and evolved them in terms of complexity, unless they had already their own idea of a thing to make smart. Moreover, the reported results show that the experiences of children and university students were both positive. Although the results of the reported work are limited by their contextual nature, lessons were drawn from the case-study results for other researchers or practitioners willing to design with end users. Limitations of the work are reflected over in the remainder of this section. The results of the reported design process are positive but with limitations. In particular, the design process reported in this paper is designed as a case study. However, in order to draw general conclusions concerning the effectiveness of the design approach and toolkits, it would take an experiment with a controlled group. Nevertheless, the reported work gives indications about the effectiveness of the design approach and toolkits, which can be evaluated in future experiments. Another limitation is related to the design toolkit used by children. The programming and prototyping part was missing in that toolkit: having it in the toolkit might have enabled children to prototype their own ideas and to carry the resulting prototypes into the design process with university students. Recent design workshops with SNaP and children indeed included programming and prototyping tools within the design toolkits for children (Gennari et al. 2021). Future work will try bringing children's prototypes into the design process with university students and study how these are appropriated and may evolve. Moreover, future editions of the course will try investigating with questionnaires the sense of empowerment that students expressed and was documented in a qualitative manner in the work reported in this paper. Different generations or age-groups of end users have different levels of familiarisation with technology. Thus the exploration of IoT may use differently the design tools. For instance, in the work reported in this paper, during the exploration and familiarisation workshop with school-age children, cards were used to explain input and output devices. Children were invited to pick up random input and output cards, and they were asked to reflect on them by themselves; in case needed, they were helped by the moderator with examples. In the case of university students, cards were used to make them familiar with physical computing and cloud computing in order to program and prototype smart things, and possibly evolve children's ideas. During the ideation and conceptualisation, tools could be partly differentiated according to the generations. In the case study reported in this paper, all end users used SNaP cards for their ideation and conceptualisation. However students had also cloud-computing cards which helped them realise what imagined by children, e.g. a barcode-scanner and a database of barcodes for the ‘garbage input’. Moreover, in order to conceptualise ideas of smart things, children and students used similar and yet different tools. Children used a board of SNaP, which asked them to use cards for physical devices, real or imagined, and mission cards; moreover, it asked children to narrate their smart things, possibly using when-sentences. Students, instead, had an adapted version of the Tiles framework for conceptualising ideas. With respect to the SNaP board for children, the adapted Tiles framework required students to create a linear storyline, detailing the interaction with their smart things via cards, and it also asked them to deeply reflect on smart things, from the usability viewpoint. Students' and children's design toolkits shared SNaP cards for missions, things of the same environment to make smart, physical input and output devices. These probably helped create a common language across generations to design smart things. In fact, input and output cards, in both toolkits, serve to represent the essential components of smart things. In the work reported in this paper, when students appropriated children's ideas of smart things and prototyped them, students maintained several input and output devices which children had chosen via SNaP cards. Moreover, missions of SNaP gave children and students common design goals. All students maintained the original missions chosen by children, and continued thus designing with the same design goal in mind. Sharing such cards, thus, seem to have enabled to share a common language for describing smart things and their goals across two different generations. Students' and children's design toolkits shared SNaP cards for missions, things of the same environment to make smart, physical input and output devices. These probably helped create a common language across generations to design smart things. In fact, input and output cards, in both toolkits, serve to represent the essential components of smart things. In the work reported in this paper, when students appropriated children's ideas of smart things and prototyped them, students maintained several input and output devices which children had chosen via SNaP cards. Moreover, missions of SNaP gave children and students common design goals. All students maintained the original missions chosen by children, and continued thus designing with the same design goal in mind. Sharing such cards, thus, seem to have enabled to share a common language for describing smart things and their goals across two different generations. Different generations or age-groups of end users have different levels of familiarisation with technology. Thus the exploration of IoT may use differently the design tools. For instance, in the work reported in this paper, during the exploration and familiarisation workshop with school-age children, cards were used to explain input and output devices. Children were invited to pick up random input and output cards, and they were asked to reflect on them by themselves; in case needed, they were helped by the moderator with examples. In the case of university students, cards were used to make them familiar with physical computing and cloud computing in order to program and prototype smart things, and possibly evolve children's ideas. During the ideation and conceptualisation, tools could be partly differentiated according to the generations. In the case study reported in this paper, all end users used SNaP cards for their ideation and conceptualisation. However students had also cloud-computing cards which helped them realise what imagined by children, e.g. a barcode-scanner and a database of barcodes for the ‘garbage input’. Moreover, in order to conceptualise ideas of smart things, children and students used similar and yet different tools. Children used a board of SNaP, which asked them to use cards for physical devices, real or imagined, and mission cards; moreover, it asked children to narrate their smart things, possibly using when-sentences. Students, instead, had an adapted version of the Tiles framework for conceptualising ideas. With respect to the SNaP board for children, the adapted Tiles framework required students to create a linear storyline, detailing the interaction with their smart things via cards, and it also asked them to deeply reflect on smart things, from the usability viewpoint. While supporting IoT design across generations, researchers should find ways of transferring ideas from one generation to the other. In the case study reported in this paper, this was done by converting the ideas generated by children into inspiration cards. Such inspiration cards, as the name indicates, served as inspiration during the workshops with university students. Each idea came with a brief description of the smart thing ideated by children, the mission, input and output devices, besides the intended interaction. Taking children's ideas as starting point for the ideation process has several advantages. The main reason is that children's ideas are often less-constrained, more imaginative and more creative than those of adults, as reported in the literature (Kuzmickaja et al. 2015). Therefore, such a strategy of starting with school-age children for ideas and then transferring such ideas to older end users, i.e. university students, can help in designing novel IoT. The results of this paper related to the evolution of smart things, reflected over above, also indicate that students, without a predefined thing to make smart in mind, tend to exploit the possibility of evolving others' ideas and make them more complex or feasible to implement. According to the reported results, students had a positive experience, and they enjoyed to engage in different stages of design across generations. This paper reported on the experience of school-age children and university students with design workshops which were similarly structured. Children's experience was investigated with survey instruments adequate for them, besides through observations. Students' experience was investigated with a standardised survey instrument related to students' satisfaction with courses, besides through interviews. Results concerning their experience are positive, and discussed below. All children reported high level of engagement with SNaP for designing smart things, to the point that they were not willing to give away their cards and wanted to keep as many cards as possible for creating their ideas, albeit they collaborated in other manners on reflecting on others' ideas through the game. Also quantitative results from the survey concerning students' experience are very positive, in general. Qualitative data from the interviews seem to confirm this interpretation. Specifically, the large majority of students reported high levels of satisfaction with the course material, structure and facilities, which indicate that the organisation of the course in different design workshops, with a design-thinking approach, was well received by students. Students enjoyed the structure of the course as well as its ‘physical approach’. Another positive aspect of the design experience with university students, emerging from interviews, was the engagement of students with an entire design journey, which led to the creation of quasi-finished products and their sharing. According to the available data, it seems that the design thinking approach to the course made students feel empowered. As stated by one student from past editions of the course, acting as course facilitator in the design experience reported in the paper, the approach enabled students ‘to participate in the activities in a very proactive way’ and they ‘felt responsible for […] the final product’. The design process reported in this paper started with children's ideas of smart things, designed with SNaP in 2018. The process continued with university students in the first-year of their Bachelor's in Computer Science, developing prototypes of smart things. The complexity of their design was assessed as follows. The complexity of ideas by children and prototypes by students was uniformly measured by considering inputs, outputs and events in the form of when-sentences in their descriptions. Results are discussed in the remainder. The complexity of children's ideas varied considerably, whereas that of students was less varied. On average students' prototypes turned out to be more complex than children's ideas, in terms of inputs and outputs they employed to program and develop prototypes of smart things. In relation to the evolution of smart things from one generation to the other, 4 groups of students out of 6 appropriated children's ideas, and brought them to the programming and prototyping stage. The remaining 2 groups opted for different things to make smart, which were not part of children's ideas. The evolution of children's ideas retained the original missions by children and, in general, the things they aimed at making smart. Only in one case, a group of students picked up an idea as inspiration and departed from it also in term of the thing to make smart: in the end, students created a game, Boppy, out of sensors and output devices retained from the original idea by children. All other prototypes, instead, maintained also the thing that children had decided to make smart (bins, bench). Last but not least, most of the students' prototypes (3 out of 4) evolved children's ideas in terms of complexity, by adding or removing specific inputs and outputs, so as to make their development more feasible. For example, in the case of the Garbage Collector students improved the children's idea they took inspiration from and replaced the sensor chosen by children with another which correctly rendered the interaction described by children. In the case of the Heartbeat Bench prototype, students removed an input chosen by children and changed the output, making the idea easier to implement but at the cost of reducing its overall complexity. Interestingly, all students maintained the original missions chosen by children for their ideas, which set the design goals which children had chosen, and maintained some of the inputs or outputs chosen by children. The design process reported in this paper started with children's ideas of smart things, designed with SNaP in 2018. The process continued with university students in the first-year of their Bachelor's in Computer Science, developing prototypes of smart things. The complexity of their design was assessed as follows. The complexity of ideas by children and prototypes by students was uniformly measured by considering inputs, outputs and events in the form of when-sentences in their descriptions. Results are discussed in the remainder. The complexity of children's ideas varied considerably, whereas that of students was less varied. On average students' prototypes turned out to be more complex than children's ideas, in terms of inputs and outputs they employed to program and develop prototypes of smart things. In relation to the evolution of smart things from one generation to the other, 4 groups of students out of 6 appropriated children's ideas, and brought them to the programming and prototyping stage. The remaining 2 groups opted for different things to make smart, which were not part of children's ideas. The evolution of children's ideas retained the original missions by children and, in general, the things they aimed at making smart. Only in one case, a group of students picked up an idea as inspiration and departed from it also in term of the thing to make smart: in the end, students created a game, Boppy, out of sensors and output devices retained from the original idea by children. All other prototypes, instead, maintained also the thing that children had decided to make smart (bins, bench). Last but not least, most of the students' prototypes (3 out of 4) evolved children's ideas in terms of complexity, by adding or removing specific inputs and outputs, so as to make their development more feasible. For example, in the case of the Garbage Collector students improved the children's idea they took inspiration from and replaced the sensor chosen by children with another which correctly rendered the interaction described by children. In the case of the Heartbeat Bench prototype, students removed an input chosen by children and changed the output, making the idea easier to implement but at the cost of reducing its overall complexity. Interestingly, all students maintained the original missions chosen by children for their ideas, which set the design goals which children had chosen, and maintained some of the inputs or outputs chosen by children. This paper reported on the experience of school-age children and university students with design workshops which were similarly structured. Children's experience was investigated with survey instruments adequate for them, besides through observations. Students' experience was investigated with a standardised survey instrument related to students' satisfaction with courses, besides through interviews. Results concerning their experience are positive, and discussed below. All children reported high level of engagement with SNaP for designing smart things, to the point that they were not willing to give away their cards and wanted to keep as many cards as possible for creating their ideas, albeit they collaborated in other manners on reflecting on others' ideas through the game. Also quantitative results from the survey concerning students' experience are very positive, in general. Qualitative data from the interviews seem to confirm this interpretation. Specifically, the large majority of students reported high levels of satisfaction with the course material, structure and facilities, which indicate that the organisation of the course in different design workshops, with a design-thinking approach, was well received by students. Students enjoyed the structure of the course as well as its ‘physical approach’. Another positive aspect of the design experience with university students, emerging from interviews, was the engagement of students with an entire design journey, which led to the creation of quasi-finished products and their sharing. According to the available data, it seems that the design thinking approach to the course made students feel empowered. As stated by one student from past editions of the course, acting as course facilitator in the design experience reported in the paper, the approach enabled students ‘to participate in the activities in a very proactive way’ and they ‘felt responsible for […] the final product’. The paper reported on a design process, started with school-age children and ended with university freshers. Design was organised with a design-thinking approach along workshops, with design toolkits shared across generations. The design process started with children's ideas, and it continued with university students who developed prototypes of smart things. The reported results are related to two research questions: (1) what smart things would children and students design; (2) their experience with design. This section starts discussing such results. It continues with preliminary lessons learnt for cross-generation design toolkits, grounded on the reported results. The design process reported in this paper started with children's ideas of smart things, designed with SNaP in 2018. The process continued with university students in the first-year of their Bachelor's in Computer Science, developing prototypes of smart things. The complexity of their design was assessed as follows. The complexity of ideas by children and prototypes by students was uniformly measured by considering inputs, outputs and events in the form of when-sentences in their descriptions. Results are discussed in the remainder. The complexity of children's ideas varied considerably, whereas that of students was less varied. On average students' prototypes turned out to be more complex than children's ideas, in terms of inputs and outputs they employed to program and develop prototypes of smart things. In relation to the evolution of smart things from one generation to the other, 4 groups of students out of 6 appropriated children's ideas, and brought them to the programming and prototyping stage. The remaining 2 groups opted for different things to make smart, which were not part of children's ideas. The evolution of children's ideas retained the original missions by children and, in general, the things they aimed at making smart. Only in one case, a group of students picked up an idea as inspiration and departed from it also in term of the thing to make smart: in the end, students created a game, Boppy, out of sensors and output devices retained from the original idea by children. All other prototypes, instead, maintained also the thing that children had decided to make smart (bins, bench). Last but not least, most of the students' prototypes (3 out of 4) evolved children's ideas in terms of complexity, by adding or removing specific inputs and outputs, so as to make their development more feasible. For example, in the case of the Garbage Collector students improved the children's idea they took inspiration from and replaced the sensor chosen by children with another which correctly rendered the interaction described by children. In the case of the Heartbeat Bench prototype, students removed an input chosen by children and changed the output, making the idea easier to implement but at the cost of reducing its overall complexity. Interestingly, all students maintained the original missions chosen by children for their ideas, which set the design goals which children had chosen, and maintained some of the inputs or outputs chosen by children. This paper reported on the experience of school-age children and university students with design workshops which were similarly structured. Children's experience was investigated with survey instruments adequate for them, besides through observations. Students' experience was investigated with a standardised survey instrument related to students' satisfaction with courses, besides through interviews. Results concerning their experience are positive, and discussed below. All children reported high level of engagement with SNaP for designing smart things, to the point that they were not willing to give away their cards and wanted to keep as many cards as possible for creating their ideas, albeit they collaborated in other manners on reflecting on others' ideas through the game. Also quantitative results from the survey concerning students' experience are very positive, in general. Qualitative data from the interviews seem to confirm this interpretation. Specifically, the large majority of students reported high levels of satisfaction with the course material, structure and facilities, which indicate that the organisation of the course in different design workshops, with a design-thinking approach, was well received by students. Students enjoyed the structure of the course as well as its ‘physical approach’. Another positive aspect of the design experience with university students, emerging from interviews, was the engagement of students with an entire design journey, which led to the creation of quasi-finished products and their sharing. According to the available data, it seems that the design thinking approach to the course made students feel empowered. As stated by one student from past editions of the course, acting as course facilitator in the design experience reported in the paper, the approach enabled students ‘to participate in the activities in a very proactive way’ and they ‘felt responsible for […] the final product’. Students' and children's design toolkits shared SNaP cards for missions, things of the same environment to make smart, physical input and output devices. These probably helped create a common language across generations to design smart things. In fact, input and output cards, in both toolkits, serve to represent the essential components of smart things. In the work reported in this paper, when students appropriated children's ideas of smart things and prototyped them, students maintained several input and output devices which children had chosen via SNaP cards. Moreover, missions of SNaP gave children and students common design goals. All students maintained the original missions chosen by children, and continued thus designing with the same design goal in mind. Sharing such cards, thus, seem to have enabled to share a common language for describing smart things and their goals across two different generations. Different generations or age-groups of end users have different levels of familiarisation with technology. Thus the exploration of IoT may use differently the design tools. For instance, in the work reported in this paper, during the exploration and familiarisation workshop with school-age children, cards were used to explain input and output devices. Children were invited to pick up random input and output cards, and they were asked to reflect on them by themselves; in case needed, they were helped by the moderator with examples. In the case of university students, cards were used to make them familiar with physical computing and cloud computing in order to program and prototype smart things, and possibly evolve children's ideas. During the ideation and conceptualisation, tools could be partly differentiated according to the generations. In the case study reported in this paper, all end users used SNaP cards for their ideation and conceptualisation. However students had also cloud-computing cards which helped them realise what imagined by children, e.g. a barcode-scanner and a database of barcodes for the ‘garbage input’. Moreover, in order to conceptualise ideas of smart things, children and students used similar and yet different tools. Children used a board of SNaP, which asked them to use cards for physical devices, real or imagined, and mission cards; moreover, it asked children to narrate their smart things, possibly using when-sentences. Students, instead, had an adapted version of the Tiles framework for conceptualising ideas. With respect to the SNaP board for children, the adapted Tiles framework required students to create a linear storyline, detailing the interaction with their smart things via cards, and it also asked them to deeply reflect on smart things, from the usability viewpoint. While supporting IoT design across generations, researchers should find ways of transferring ideas from one generation to the other. In the case study reported in this paper, this was done by converting the ideas generated by children into inspiration cards. Such inspiration cards, as the name indicates, served as inspiration during the workshops with university students. Each idea came with a brief description of the smart thing ideated by children, the mission, input and output devices, besides the intended interaction. Taking children's ideas as starting point for the ideation process has several advantages. The main reason is that children's ideas are often less-constrained, more imaginative and more creative than those of adults, as reported in the literature (Kuzmickaja et al. 2015). Therefore, such a strategy of starting with school-age children for ideas and then transferring such ideas to older end users, i.e. university students, can help in designing novel IoT. The results of this paper related to the evolution of smart things, reflected over above, also indicate that students, without a predefined thing to make smart in mind, tend to exploit the possibility of evolving others' ideas and make them more complex or feasible to implement. According to the reported results, students had a positive experience, and they enjoyed to engage in different stages of design across generations. In the middle of the course, teachers organised an ideation and conceptualisation workshop with students. It lasted circa 6 h. Students worked in groups as follows (see Figure 7). Figure 7. Groups of students during the ideation and conceptualisation workshop. Groups of students during the ideation and conceptualisation workshop. University students were invited to read and, if they wished so, to use inspiration cards of the toolkit, reporting ideas of smart things by children. In case so, they were also asked to continue elaborating on ideas by children so as to bring them to the final programming and prototyping stage. Once cards were reflected over, students were introduced to the following Design-Sprint techniques: (1) Crazy 8's; (2) Sharing and Voting; (3) Dot Vote (Crazy 8 2016). By adopting the Crazy 8's technique, each student sketched up to eight ideas on an A4 paper, folded into eight sections for the group's selected mission. In case feasible, students correlated them to inspiration, mission and persona cards of their choice. By adopting the Sharing and Voting technique, students presented their ideas to their group, one by one. Then group members discussed and negotiated so as to merge and converge on at most eight ideas per group. Ideas were shortlisted if the group members considered them feasible to prototype, useful for personas, relevant for the mission, reinventing and innovating–that is, ideas were evaluated against reflection cards of SNaP for students, examples of which are in Figure 5. This way, at the end of Sharing and Voting, each group ended up with a selection of eight crazy ideas per group. Groups then plastered a corridor with the sketches of their final ideas, eight per group, along with their persona and mission cards, inspiration cards if used, so as to share them with everyone else in the class. In turn, each group pitched their ideas (see Figure 8). In line with the Dot Vote technique, students were given each ten stickers to vote other groups' ideas. Students went around the ideas of all the groups, and pasted one or more stickers on the ideas which they liked best. See the left-more part of Figure 8. Students were invited to use again reflection cards to evaluate ideas–feasible to prototype, useful for personas, relevant for the mission, reinventing and innovating. At the end of this step, each group ranked ideas according to the number or coloured stickers. They either chose an idea among those with the highest number of stickers, or in some cases, they merged ideas with the highest numbers of stickers. Figure 8. The result of voting with stickers during the ideation workshop and the framework for conceptualising the most voted idea. The result of voting with stickers during the ideation workshop and the framework for conceptualising the most voted idea. Finally, each group was given the adapted Tiles framework to conceptualise their winning ideas with. At the end, one student per group gave a short presentation by using the framework in a so-called elevator pitch format. Reflections again followed so as to improve on the ideas conceptualised in frameworks. See the left-more part of Figure 8 for an example of the resulting framework. Workshops were organised along the aforementioned design stages: (1) exploration and familiarisation; (2) ideation and conceptualisation; (3) programming and prototyping. Specifically, the first workshops enabled students to explore and get familiar with the design toolkits and learn the basics of IoT for designing smart things. Then university students moved on to a single ideation and conceptualisation workshop, during which they elaborated on ideas starting from children's ideas. Finally, students took part in a series of programming and prototyping workshops, with a conclusive sharing part. The following part describes each type of workshops in details. The exploration and familiarisation workshops took c. half of the course. Their purpose was to familiarise all students with the basic IoT concepts (e.g. inputs and outputs) and make them familiar with toolkits for designing their smart things. At the start of these workshops, teachers presented the main environment, shared with children–enriching nature outdoor parks with IoT. Teachers also showed the smart-things of the previous academic year; albeit related to a different environment, they served to motivate students and to make tangible the outcomes of the design workshops. In order to further enter into the mind-set of the course, students were invited to immediately work in groups. Working in groups, students started programming. They tackled Python programming exercises prepared by teachers, for physical and cloud computing with the microelectronics of the design toolkit. Then they explored decks of cards of their design toolkit related to inputs and outputs (see Figure 5) and were invited to connect them to what explored through exercises. In the middle of the course, teachers organised an ideation and conceptualisation workshop with students. It lasted circa 6 h. Students worked in groups as follows (see Figure 7). Figure 7. Groups of students during the ideation and conceptualisation workshop. University students were invited to read and, if they wished so, to use inspiration cards of the toolkit, reporting ideas of smart things by children. In case so, they were also asked to continue elaborating on ideas by children so as to bring them to the final programming and prototyping stage. Once cards were reflected over, students were introduced to the following Design-Sprint techniques: (1) Crazy 8's; (2) Sharing and Voting; (3) Dot Vote (Crazy 8 2016). By adopting the Crazy 8's technique, each student sketched up to eight ideas on an A4 paper, folded into eight sections for the group's selected mission. In case feasible, students correlated them to inspiration, mission and persona cards of their choice. By adopting the Sharing and Voting technique, students presented their ideas to their group, one by one. Then group members discussed and negotiated so as to merge and converge on at most eight ideas per group. Ideas were shortlisted if the group members considered them feasible to prototype, useful for personas, relevant for the mission, reinventing and innovating–that is, ideas were evaluated against reflection cards of SNaP for students, examples of which are in Figure 5. This way, at the end of Sharing and Voting, each group ended up with a selection of eight crazy ideas per group. Groups then plastered a corridor with the sketches of their final ideas, eight per group, along with their persona and mission cards, inspiration cards if used, so as to share them with everyone else in the class. In turn, each group pitched their ideas (see Figure 8). In line with the Dot Vote technique, students were given each ten stickers to vote other groups' ideas. Students went around the ideas of all the groups, and pasted one or more stickers on the ideas which they liked best. See the left-more part of Figure 8. Students were invited to use again reflection cards to evaluate ideas–feasible to prototype, useful for personas, relevant for the mission, reinventing and innovating. At the end of this step, each group ranked ideas according to the number or coloured stickers. They either chose an idea among those with the highest number of stickers, or in some cases, they merged ideas with the highest numbers of stickers. Figure 8. The result of voting with stickers during the ideation workshop and the framework for conceptualising the most voted idea. Finally, each group was given the adapted Tiles framework to conceptualise their winning ideas with. At the end, one student per group gave a short presentation by using the framework in a so-called elevator pitch format. Reflections again followed so as to improve on the ideas conceptualised in frameworks. See the left-more part of Figure 8 for an example of the resulting framework. The course continued with 6 programming and prototyping workshops, each of circa 4 h. During these workshops students programmed and prototyped ideas, starting from the idea conceptualised in frameworks, and at the end shared them. During the first programming and prototyping workshops, teachers stirred students through the relevant programming material they had explored during the exploration and familiarisation workshops, and recapped for them in a dedicated portfolio. When needed, further input and output devices were chosen with teachers according to the ideas of groups besides those explored in the exploration and familiarisation workshops. From the fourth programming and prototyping workshop onward, students assembled their components and, whenever needed, they used laser cutters and 3D printers available in the university's makerspace. They extensively tested and reflected on their prototypes and adjusted them according to the detected issues related to programming and prototyping. The final part of the course consisted of a sharing workshop in the form of a public exhibition (see Figure 9). Along with this exhibition space, each group had 10 min to present their prototype verbally as well as to enact the interaction with their prototype in front of the audience. After the presentations, the audience freely interacted with the students and their prototypes. Therefore, this served as a chance for the students not only to share and show-case their prototypes but also to get feedback from an audience of Free University of Bozen-Bolzano researchers and peers, besides interested citizens. Figure 9. Exhibition space with smart thing prototypes in the last workshop. Exhibition space with smart thing prototypes in the last workshop. In 2018–2019, the Maker Lab course of Free University of Bozen-Bolzano was held with first-year Bachelors' students from the Faculty of Computer Science, coming from different high schools. The course took a total of 60 h. The Maker Lab course was organised with design workshops, for enriching nature outdoor park environments with IoT. The remainder of this section discusses the participants and setting, the research questions, and the organisation of design workshops with students. A total of 28 students enrolled in the course. Most of students had no electronics background, and none of them had any prior design experience. They worked in groups of 3 to 5. Two teachers acted as workshop organisers and prepared all the material for workshops. Along the course they acted as facilitators as in collaborative learning settings (Johnson and Johnson 2005). Furthermore, a student from a past edition of the course also participated as technical facilitator for students. The leading research questions of design with university students were as follows: R1. what smart things students would design;R2. what the students' overall experience with design would be. what smart things students would design; what the students' overall experience with design would be. Different sorts of mainly qualitative data were collected and later analysed in relation to the two aforementioned research questions. For answering (R1), researchers considered the programmed prototypes. Data concerning (R2), that is, participants' experience, were collected via a standard post-course survey managed and processed by the university in anonymous format, with open-format and closed-format questions, besides interviews tracked in notes by teachers. The students were made aware that the interviews and the anonymous survey had no effect on the grading of the course whatsoever. They were in any case familiar with these types of surveys to be filled at the end of each course they attend. Workshops were organised along the aforementioned design stages: (1) exploration and familiarisation; (2) ideation and conceptualisation; (3) programming and prototyping. Specifically, the first workshops enabled students to explore and get familiar with the design toolkits and learn the basics of IoT for designing smart things. Then university students moved on to a single ideation and conceptualisation workshop, during which they elaborated on ideas starting from children's ideas. Finally, students took part in a series of programming and prototyping workshops, with a conclusive sharing part. The following part describes each type of workshops in details. The exploration and familiarisation workshops took c. half of the course. Their purpose was to familiarise all students with the basic IoT concepts (e.g. inputs and outputs) and make them familiar with toolkits for designing their smart things. At the start of these workshops, teachers presented the main environment, shared with children–enriching nature outdoor parks with IoT. Teachers also showed the smart-things of the previous academic year; albeit related to a different environment, they served to motivate students and to make tangible the outcomes of the design workshops. In order to further enter into the mind-set of the course, students were invited to immediately work in groups. Working in groups, students started programming. They tackled Python programming exercises prepared by teachers, for physical and cloud computing with the microelectronics of the design toolkit. Then they explored decks of cards of their design toolkit related to inputs and outputs (see Figure 5) and were invited to connect them to what explored through exercises. In the middle of the course, teachers organised an ideation and conceptualisation workshop with students. It lasted circa 6 h. Students worked in groups as follows (see Figure 7). Figure 7. Groups of students during the ideation and conceptualisation workshop. University students were invited to read and, if they wished so, to use inspiration cards of the toolkit, reporting ideas of smart things by children. In case so, they were also asked to continue elaborating on ideas by children so as to bring them to the final programming and prototyping stage. Once cards were reflected over, students were introduced to the following Design-Sprint techniques: (1) Crazy 8's; (2) Sharing and Voting; (3) Dot Vote (Crazy 8 2016). By adopting the Crazy 8's technique, each student sketched up to eight ideas on an A4 paper, folded into eight sections for the group's selected mission. In case feasible, students correlated them to inspiration, mission and persona cards of their choice. By adopting the Sharing and Voting technique, students presented their ideas to their group, one by one. Then group members discussed and negotiated so as to merge and converge on at most eight ideas per group. Ideas were shortlisted if the group members considered them feasible to prototype, useful for personas, relevant for the mission, reinventing and innovating–that is, ideas were evaluated against reflection cards of SNaP for students, examples of which are in Figure 5. This way, at the end of Sharing and Voting, each group ended up with a selection of eight crazy ideas per group. Groups then plastered a corridor with the sketches of their final ideas, eight per group, along with their persona and mission cards, inspiration cards if used, so as to share them with everyone else in the class. In turn, each group pitched their ideas (see Figure 8). In line with the Dot Vote technique, students were given each ten stickers to vote other groups' ideas. Students went around the ideas of all the groups, and pasted one or more stickers on the ideas which they liked best. See the left-more part of Figure 8. Students were invited to use again reflection cards to evaluate ideas–feasible to prototype, useful for personas, relevant for the mission, reinventing and innovating. At the end of this step, each group ranked ideas according to the number or coloured stickers. They either chose an idea among those with the highest number of stickers, or in some cases, they merged ideas with the highest numbers of stickers. Figure 8. The result of voting with stickers during the ideation workshop and the framework for conceptualising the most voted idea. Finally, each group was given the adapted Tiles framework to conceptualise their winning ideas with. At the end, one student per group gave a short presentation by using the framework in a so-called elevator pitch format. Reflections again followed so as to improve on the ideas conceptualised in frameworks. See the left-more part of Figure 8 for an example of the resulting framework. The course continued with 6 programming and prototyping workshops, each of circa 4 h. During these workshops students programmed and prototyped ideas, starting from the idea conceptualised in frameworks, and at the end shared them. During the first programming and prototyping workshops, teachers stirred students through the relevant programming material they had explored during the exploration and familiarisation workshops, and recapped for them in a dedicated portfolio. When needed, further input and output devices were chosen with teachers according to the ideas of groups besides those explored in the exploration and familiarisation workshops. From the fourth programming and prototyping workshop onward, students assembled their components and, whenever needed, they used laser cutters and 3D printers available in the university's makerspace. They extensively tested and reflected on their prototypes and adjusted them according to the detected issues related to programming and prototyping. The final part of the course consisted of a sharing workshop in the form of a public exhibition (see Figure 9). Along with this exhibition space, each group had 10 min to present their prototype verbally as well as to enact the interaction with their prototype in front of the audience. After the presentations, the audience freely interacted with the students and their prototypes. Therefore, this served as a chance for the students not only to share and show-case their prototypes but also to get feedback from an audience of Free University of Bozen-Bolzano researchers and peers, besides interested citizens. Figure 9. Exhibition space with smart thing prototypes in the last workshop. For answering R1, data were collected in the form of ideas conceptualised with SNaP. The outcome children's ideas are reported in Table 2. This gives the mission of each idea besides its description by children. The description in Table 2 reports in uppercase the input and output physical devices or imagined services by children. It also assigns a number to each idea, copied into an inspiration card for students. Table 2. Ideas by children designed with SNaP in 2018, and numbers identifying the inspiration cards with children's ideas.IdeaInspirationMission: help visitors learn about the park.Description: STREET SIGNS point to hidden parts of the parks with LEDs. LEDs are switched on WHEN the DISTANCE input detects that somebody approaches the STREET SIGNS.1Mission: make sure that visitors respect nature.Description: WHEN a person throws garbage on the ground, a CAMERA, which is always switched on, intercepts this situation (GARBAGE INPUT). Thus, a red light (LED) is switched on and an alarm (SPEAKER) is produced. A policeman, alerted by the alarm, goes there using a bicycle, and brings the person to the closest trash bin.2Mission: make sure that the park is accessible.Description: There are rocks and swings with MOTION sensors and SPEAKERS, to alert blind people WHEN they meet obstacles. Moreover, there is also a bridge with a MOTION sensor and a DISPLAY; WHEN a person in a wheelchair is near the bridge, the DISPLAY alerts other people to pay attention.3Mission: add playful and interactive attractions to the park.Description: There are MOTION and LUMINOSITY sensors on a bridge over water, and lights (LED) to enlighten water under the bridge. The MOTION sensor detects WHEN people pass on the bridge, water has brilliant light colours (LED) that depend on the detected LUMINOSITY level.4Mission: help visitors learn about the park.Description: A MOTION sensor detects WHEN a bicycle gets close to streets lights. The LUMINOSITY sensor then switches on lights (LED), the MOTOR makes street lights rotate to indicate the path to an hidden point that is worth being visited.5Mission: make sure that visitors respect nature.Description: A PRESSURE sensor detects WHEN somebody throws something into a trash can, thus this makes asound (SPEAKER) and lights up (LED) so as to create a joyful effect (as award).6Mission: make sure the park is accessible to anybody.Description: I would define a path that facilitates walking for disabled people. Along this path, benches are augmented so that WHEN a person feels sick she or he can sit on it, and the HEART-RATE and TEMPERATURE sensors are activated. The person can call for help by pressing the PRESSURE sensor; WHEN the person presses it, a LOCATION sensor [detects and the bench] communicates the precise position of the person (CALL-FOR-HELP OUTPUT).7Mission: add playful and interactive attractions to the park.Description: There is a path, with bicycles and benches, that is enlightened (LED). Along the path, there is a tree augmented with a BUTTON. WHEN the BUTTON is pressed, the tree takes a picture (via a CAMERA) of the beautiful nature landscape. The picture is shown on a DISPLAY installed on the tree, and also on the WEB SITE of the park.8 Ideas by children designed with SNaP in 2018, and numbers identifying the inspiration cards with children's ideas. The complexity of a smart-thing idea is the sum of the following numbers, in line with (Fronza, Corral, and Pahl 2020): the number of its physical inputs and outputs (e.g. the number of buttons and the number of speakers),the number of other inputs and outputs the smart thing has (e.g. the number of imagined services for getting data or posting data),the number of events, in the form of when-sentences. the number of its physical inputs and outputs (e.g. the number of buttons and the number of speakers), the number of other inputs and outputs the smart thing has (e.g. the number of imagined services for getting data or posting data), the number of events, in the form of when-sentences. Three researchers worked independently for assessing the complexity of smart things, then they met again for comparing their results. Results were discussed and were revised accordingly together in case of disagreements. See Table 3 for the resulting complexity. Table 3. The complexity of ideas of smart things by children.InspirationPhysicalOtherEventsComplexityInputsOutputsInputsOutputs1111321211531113421145221561214731127822116 The complexity of ideas of smart things by children. Children's ideas included at least one physical input and one physical output. Other relevant statistics related to the complexity of smart things are as follows. The mean complexity of children's ideas of smart things is 4.63 with standard deviation 1.41. The maximum is 7, the minimum is 3. The results of the workshops with children are briefly reported in relation to the two aforementioned research questions: (R1) ideas of smart things children generated, then carried over by university students; (R2) children's experience of the game-based workshops. For answering R1, data were collected in the form of ideas conceptualised with SNaP. The outcome children's ideas are reported in Table 2. This gives the mission of each idea besides its description by children. The description in Table 2 reports in uppercase the input and output physical devices or imagined services by children. It also assigns a number to each idea, copied into an inspiration card for students. Table 2. Ideas by children designed with SNaP in 2018, and numbers identifying the inspiration cards with children's ideas.IdeaInspirationMission: help visitors learn about the park.Description: STREET SIGNS point to hidden parts of the parks with LEDs. LEDs are switched on WHEN the DISTANCE input detects that somebody approaches the STREET SIGNS.1Mission: make sure that visitors respect nature.Description: WHEN a person throws garbage on the ground, a CAMERA, which is always switched on, intercepts this situation (GARBAGE INPUT). Thus, a red light (LED) is switched on and an alarm (SPEAKER) is produced. A policeman, alerted by the alarm, goes there using a bicycle, and brings the person to the closest trash bin.2Mission: make sure that the park is accessible.Description: There are rocks and swings with MOTION sensors and SPEAKERS, to alert blind people WHEN they meet obstacles. Moreover, there is also a bridge with a MOTION sensor and a DISPLAY; WHEN a person in a wheelchair is near the bridge, the DISPLAY alerts other people to pay attention.3Mission: add playful and interactive attractions to the park.Description: There are MOTION and LUMINOSITY sensors on a bridge over water, and lights (LED) to enlighten water under the bridge. The MOTION sensor detects WHEN people pass on the bridge, water has brilliant light colours (LED) that depend on the detected LUMINOSITY level.4Mission: help visitors learn about the park.Description: A MOTION sensor detects WHEN a bicycle gets close to streets lights. The LUMINOSITY sensor then switches on lights (LED), the MOTOR makes street lights rotate to indicate the path to an hidden point that is worth being visited.5Mission: make sure that visitors respect nature.Description: A PRESSURE sensor detects WHEN somebody throws something into a trash can, thus this makes asound (SPEAKER) and lights up (LED) so as to create a joyful effect (as award).6Mission: make sure the park is accessible to anybody.Description: I would define a path that facilitates walking for disabled people. Along this path, benches are augmented so that WHEN a person feels sick she or he can sit on it, and the HEART-RATE and TEMPERATURE sensors are activated. The person can call for help by pressing the PRESSURE sensor; WHEN the person presses it, a LOCATION sensor [detects and the bench] communicates the precise position of the person (CALL-FOR-HELP OUTPUT).7Mission: add playful and interactive attractions to the park.Description: There is a path, with bicycles and benches, that is enlightened (LED). Along the path, there is a tree augmented with a BUTTON. WHEN the BUTTON is pressed, the tree takes a picture (via a CAMERA) of the beautiful nature landscape. The picture is shown on a DISPLAY installed on the tree, and also on the WEB SITE of the park.8 The complexity of a smart-thing idea is the sum of the following numbers, in line with (Fronza, Corral, and Pahl 2020): the number of its physical inputs and outputs (e.g. the number of buttons and the number of speakers),the number of other inputs and outputs the smart thing has (e.g. the number of imagined services for getting data or posting data),the number of events, in the form of when-sentences. Three researchers worked independently for assessing the complexity of smart things, then they met again for comparing their results. Results were discussed and were revised accordingly together in case of disagreements. See Table 3 for the resulting complexity. Table 3. The complexity of ideas of smart things by children.InspirationPhysicalOtherEventsComplexityInputsOutputsInputsOutputs1111321211531113421145221561214731127822116 Children's ideas included at least one physical input and one physical output. Other relevant statistics related to the complexity of smart things are as follows. The mean complexity of children's ideas of smart things is 4.63 with standard deviation 1.41. The maximum is 7, the minimum is 3. Experience data, collected through the questionnaire, gave a very positive answer to the R2 research question: all children said that they liked playing very much and that they would definitely like to play again. Qualitative data were explored by researchers as in exploratory design in order to understand and assess children's answers to the questionnaire. During the game all children seemed to be very committed in identifying how each card could be exploited in combination with the others. Nobody wanted to exchange cards with the other children at start, as in fear they might need all their cards later. However, generally, children seemed to be most willing to collaborate and help each other, without feeling the need to compete with each other. For instance, when one child was in trouble in generating an idea (‘what can I make?’), all the others tried to give reflection opportunities. Then the ideation started and so did the game-play with SNaP boards. Each child randomly picked up one card per deck, and started thinking of a possible smart thing with it, with the help of others, according to the game mechanics (Gennari et al. 2019a). All children shared their smart thing ideas. The game stirred them to reflect with others so as to improve on their ideas and select the ideas that they thought best. The SNaP conceptualisation board served to describe children's ideas with cards and textual descriptions (see Figure 4). A brief oral presentation was delivered, introducing smart things, by using SNaP cards and examples, drawing from children's experience. Initially, each child was asked to choose a random card and try to think of what it represented, e.g. input cards for devices such as buttons or motion sensors, output cards for devices such as screens or speakers. In case of difficulty in understanding it (e.g. the motion sensor input card), the moderator suggested to re-read the description under the title or gave examples (see Figure 3). Design started with an exploration and familiarisation workshop, and continued with an ideation and conceptualisation workshop, explained next. A brief oral presentation was delivered, introducing smart things, by using SNaP cards and examples, drawing from children's experience. Initially, each child was asked to choose a random card and try to think of what it represented, e.g. input cards for devices such as buttons or motion sensors, output cards for devices such as screens or speakers. In case of difficulty in understanding it (e.g. the motion sensor input card), the moderator suggested to re-read the description under the title or gave examples (see Figure 3). Then the ideation started and so did the game-play with SNaP boards. Each child randomly picked up one card per deck, and started thinking of a possible smart thing with it, with the help of others, according to the game mechanics (Gennari et al. 2019a). All children shared their smart thing ideas. The game stirred them to reflect with others so as to improve on their ideas and select the ideas that they thought best. The SNaP conceptualisation board served to describe children's ideas with cards and textual descriptions (see Figure 4). The main exploratory research questions were related to (R1) children's ideas, that is, what smart things they would ideate by playing SNaP, (R2) and children's experience, whether they liked it and would do it again. As for (R1), data related to children's ideas were collected via the SNaP board illustrated in Figure 4. As for (R2), data were collected via a self-report questionnaire with two instruments from the standardised Fun Toolkit for children: the Smiley-o-meter and the Again-and-Again survey (Read and MacFarlane 2006). The questionnaire asked children what follows: how much they liked playing with SNaP, using the Smiley-o-meter 5-point Likert scale, ranging from ‘not at all’ (1) to ‘very much’ (5); whether they ‘would do it again’, using the Again-and-Again-Likert scale with answers ‘definitely yes’, ‘maybe’, ‘absolutely no’. Data related to children's experience were also collected and integrated with observations and interviews, tracked in written notes and videos. The 2018 version of SNaP was used in workshops with 8 children, aged 11–14 years old: 4 females and 4 males. They were run in a facility of Politecnico di Milano. Children were asked about their experience of creating interactive solutions such as smart things. None had any prior related experience. All children participated on a voluntary basis and their parents were administered a consent form, clarifying their rights concerning data processing. Children played the role of designers in SNaP. Two adults also participated, both design experts, one acting as moderator and the other as data recorder. In 2018, children participated in smart-thing design workshops. The goal was to make children explore what smart things are and to help them ideate their own for an outdoor park environment. The workshops revolved around the 2018 version of the SNaP design toolkit, described above (Gennari et al. 2019a). This section outlines the participants and the setting of the workshops. Then it gives essential information on the research questions and organisation of the workshops themselves. It concludes with the results of the workshops with children, that is, the outcome smart-things ideas, which were then taken up by the follow-up workshops with university students, and children's experience. The 2018 version of SNaP was used in workshops with 8 children, aged 11–14 years old: 4 females and 4 males. They were run in a facility of Politecnico di Milano. Children were asked about their experience of creating interactive solutions such as smart things. None had any prior related experience. All children participated on a voluntary basis and their parents were administered a consent form, clarifying their rights concerning data processing. Children played the role of designers in SNaP. Two adults also participated, both design experts, one acting as moderator and the other as data recorder. The main exploratory research questions were related to (R1) children's ideas, that is, what smart things they would ideate by playing SNaP, (R2) and children's experience, whether they liked it and would do it again. As for (R1), data related to children's ideas were collected via the SNaP board illustrated in Figure 4. As for (R2), data were collected via a self-report questionnaire with two instruments from the standardised Fun Toolkit for children: the Smiley-o-meter and the Again-and-Again survey (Read and MacFarlane 2006). The questionnaire asked children what follows: how much they liked playing with SNaP, using the Smiley-o-meter 5-point Likert scale, ranging from ‘not at all’ (1) to ‘very much’ (5); whether they ‘would do it again’, using the Again-and-Again-Likert scale with answers ‘definitely yes’, ‘maybe’, ‘absolutely no’. Data related to children's experience were also collected and integrated with observations and interviews, tracked in written notes and videos. Design started with an exploration and familiarisation workshop, and continued with an ideation and conceptualisation workshop, explained next. A brief oral presentation was delivered, introducing smart things, by using SNaP cards and examples, drawing from children's experience. Initially, each child was asked to choose a random card and try to think of what it represented, e.g. input cards for devices such as buttons or motion sensors, output cards for devices such as screens or speakers. In case of difficulty in understanding it (e.g. the motion sensor input card), the moderator suggested to re-read the description under the title or gave examples (see Figure 3). Then the ideation started and so did the game-play with SNaP boards. Each child randomly picked up one card per deck, and started thinking of a possible smart thing with it, with the help of others, according to the game mechanics (Gennari et al. 2019a). All children shared their smart thing ideas. The game stirred them to reflect with others so as to improve on their ideas and select the ideas that they thought best. The SNaP conceptualisation board served to describe children's ideas with cards and textual descriptions (see Figure 4). The results of the workshops with children are briefly reported in relation to the two aforementioned research questions: (R1) ideas of smart things children generated, then carried over by university students; (R2) children's experience of the game-based workshops. For answering R1, data were collected in the form of ideas conceptualised with SNaP. The outcome children's ideas are reported in Table 2. This gives the mission of each idea besides its description by children. The description in Table 2 reports in uppercase the input and output physical devices or imagined services by children. It also assigns a number to each idea, copied into an inspiration card for students. Table 2. Ideas by children designed with SNaP in 2018, and numbers identifying the inspiration cards with children's ideas.IdeaInspirationMission: help visitors learn about the park.Description: STREET SIGNS point to hidden parts of the parks with LEDs. LEDs are switched on WHEN the DISTANCE input detects that somebody approaches the STREET SIGNS.1Mission: make sure that visitors respect nature.Description: WHEN a person throws garbage on the ground, a CAMERA, which is always switched on, intercepts this situation (GARBAGE INPUT). Thus, a red light (LED) is switched on and an alarm (SPEAKER) is produced. A policeman, alerted by the alarm, goes there using a bicycle, and brings the person to the closest trash bin.2Mission: make sure that the park is accessible.Description: There are rocks and swings with MOTION sensors and SPEAKERS, to alert blind people WHEN they meet obstacles. Moreover, there is also a bridge with a MOTION sensor and a DISPLAY; WHEN a person in a wheelchair is near the bridge, the DISPLAY alerts other people to pay attention.3Mission: add playful and interactive attractions to the park.Description: There are MOTION and LUMINOSITY sensors on a bridge over water, and lights (LED) to enlighten water under the bridge. The MOTION sensor detects WHEN people pass on the bridge, water has brilliant light colours (LED) that depend on the detected LUMINOSITY level.4Mission: help visitors learn about the park.Description: A MOTION sensor detects WHEN a bicycle gets close to streets lights. The LUMINOSITY sensor then switches on lights (LED), the MOTOR makes street lights rotate to indicate the path to an hidden point that is worth being visited.5Mission: make sure that visitors respect nature.Description: A PRESSURE sensor detects WHEN somebody throws something into a trash can, thus this makes asound (SPEAKER) and lights up (LED) so as to create a joyful effect (as award).6Mission: make sure the park is accessible to anybody.Description: I would define a path that facilitates walking for disabled people. Along this path, benches are augmented so that WHEN a person feels sick she or he can sit on it, and the HEART-RATE and TEMPERATURE sensors are activated. The person can call for help by pressing the PRESSURE sensor; WHEN the person presses it, a LOCATION sensor [detects and the bench] communicates the precise position of the person (CALL-FOR-HELP OUTPUT).7Mission: add playful and interactive attractions to the park.Description: There is a path, with bicycles and benches, that is enlightened (LED). Along the path, there is a tree augmented with a BUTTON. WHEN the BUTTON is pressed, the tree takes a picture (via a CAMERA) of the beautiful nature landscape. The picture is shown on a DISPLAY installed on the tree, and also on the WEB SITE of the park.8 The complexity of a smart-thing idea is the sum of the following numbers, in line with (Fronza, Corral, and Pahl 2020): the number of its physical inputs and outputs (e.g. the number of buttons and the number of speakers),the number of other inputs and outputs the smart thing has (e.g. the number of imagined services for getting data or posting data),the number of events, in the form of when-sentences. Three researchers worked independently for assessing the complexity of smart things, then they met again for comparing their results. Results were discussed and were revised accordingly together in case of disagreements. See Table 3 for the resulting complexity. Table 3. The complexity of ideas of smart things by children.InspirationPhysicalOtherEventsComplexityInputsOutputsInputsOutputs1111321211531113421145221561214731127822116 Children's ideas included at least one physical input and one physical output. Other relevant statistics related to the complexity of smart things are as follows. The mean complexity of children's ideas of smart things is 4.63 with standard deviation 1.41. The maximum is 7, the minimum is 3. Experience data, collected through the questionnaire, gave a very positive answer to the R2 research question: all children said that they liked playing very much and that they would definitely like to play again. Qualitative data were explored by researchers as in exploratory design in order to understand and assess children's answers to the questionnaire. During the game all children seemed to be very committed in identifying how each card could be exploited in combination with the others. Nobody wanted to exchange cards with the other children at start, as in fear they might need all their cards later. However, generally, children seemed to be most willing to collaborate and help each other, without feeling the need to compete with each other. For instance, when one child was in trouble in generating an idea (‘what can I make?’), all the others tried to give reflection opportunities. In the exploration and familiarisation stage, students had SNaP cards plus others decks of cards at their disposal. Specifically, the SNaP thing cards for students were the same as for children. SNaP input and output cards for physical devices (e.g. buttons and speakers) were also shared across generations. In addition, students had at disposal other input and output cards related to cloud-computing services, e.g. for getting the current weather conditions (input) or posting a tweet (output). During their exploration and familiarisation, students also used programmable microelectronics kits. These kits came with Raspberry Pi 3 boards. Raspberry Pi has pins for interfacing with external input and output devices, which were explored and explained with the aid of SNaP input and output cards for physical devices. Moreover, the programmable microelectronics kits had stackable HATs. These HATs or “Hardware Attached on Top” are printed circuit boards with sensors and actuators to stack on top a Raspberry Pi, simplifying their usage by those without microelectronics experience (HATs 2014). In order to start the ideation process, students had at their disposal so-called inspiration cards. These transposed ideas by children, ideated with SNaP cards and conceptualised with the SNaP board (see Figure 2). Each inspiration card came with a brief description of an IoT idea by children, clarifying their envisioned mission, the thing to make smart and the input and output devices children had adopted or imagined. Students were also given the SNaP mission cards of children so as to share the same design goals. Moreover, students had also persona cards from the Tiles cards, besides reflection cards with probes for reflecting on their ideas in terms of usability. Figure 5 shows examples of all cards given to students, divided into decks of cards related to missions, inspirations, reflections, personas, things of the outdoor environment, input (physical, cloud), output (physical, cloud). Figure 5. Examples of decks of cards of the design toolkit for university students. Examples of decks of cards of the design toolkit for university students. For conceptualising their ideas, students were given a different framework than the SNaP board used by children: students used an adapted version of the Tiles framework (Mora, Gianni, and Divitini 2017). This asked students to also reflect on personas for their missions via the related cards, and to acknowledge what inspired their smart things. The adapted Tiles framework asked students to narrate the interaction of their smart thing by means of a linear storyboard. Specifically, the storyboard explicitly asked students to narrate the intended interaction of their persona(s) for reaching their mission by means of the smart-thing conceptualised with input, output and environment cards, see Figure 6. The story-board was on-purpose minimal and constrained to make sure that the ideas would be implementable, given the design inexperience of students. Figure 6. The adapted Tiles framework for university students. The adapted Tiles framework for university students. In order to program and prototype their smart things, students had at their disposal Raspberry Pi 3 and hats, besides a portfolio with a recap of relevant programming snippets explored during the exploration and familiarisation steps. Digital fabrication of smart-thing prototypes was enabled through the laser cutters and 3D printers of the Bitz makerspace of Free University of Bozen-Bolzano. Table 1 recaps what was common across design toolkits, what was for children only and students only. Table 1. Recap of common elements across design toolkits, what is for children only or students only.CommonFor childrenFor studentsSNaP missionSNaP environment thingSNaP physical inputSNaP free inputcloud inputSNaP physical outputSNaP free outputcloud outputinspirationreflectionCardsTiles personaFrameworkSNaP boardadapted from TilesMicroelectronicsRaspberry Pi Recap of common elements across design toolkits, what is for children only or students only. SNaP is a board-game with cards, split into decks, which guides children through the design of novel smart things for a specific environment. The 2018 version of SNaP has a deck of environment cards which represent things typical of outdoor park environments, such as a tree or a swing. Two deck of cards represent physical input and output devices of smart things, such as a temperature sensor or a motion sensor (input cards), and a servo motor or a speaker for sound (output cards) (Gennari et al. 2019b) (see Figure 3). Therefore environment, input and output cards serve as concrete representations of what children need in order to design smart things, feasible to implement. However, children could choose to imagine and add further input and output cards, should their idea need them in the game-play. SNaP has also a deck of mission cards giving design goals in relation to the environment, such as “help visitors learn about the park” or “help nature thrive”. In SNaP children play and act as designers: they win the game if each ideates (at least) a smart thing for the chosen environment. By throwing dice and moving their tokens on the SNaP boards, children collect, exchange and try to combine their cards. They also share their ideas, reflect on them with others and conceptualise ideas in an ad-hoc framework for children, that is, one of the SNaP boards (see Figure 4). The SNaP design toolkit was used in two main stages of the design process. Firstly, cards were used to explore and make children familiar with the basic components of smart things, namely, the things themselves represented on environment cards, the input and output devices for making things smart. Secondly, the toolkit was used for enabling children to ideate and conceptualise ideas of smart things, and frame them with cards in the conceptualisation board of SNaP (see Figure 2). As the needs and expertise of each generation are different (i.e. those of school-age children and university students), different design toolkits are often employed in the design process. However, in order to successfully move the design process across generations, the toolkits need to share elements across generations. The following part reports common aspects and differences in the design toolkits of this paper. SNaP is a board-game with cards, split into decks, which guides children through the design of novel smart things for a specific environment. The 2018 version of SNaP has a deck of environment cards which represent things typical of outdoor park environments, such as a tree or a swing. Two deck of cards represent physical input and output devices of smart things, such as a temperature sensor or a motion sensor (input cards), and a servo motor or a speaker for sound (output cards) (Gennari et al. 2019b) (see Figure 3). Therefore environment, input and output cards serve as concrete representations of what children need in order to design smart things, feasible to implement. However, children could choose to imagine and add further input and output cards, should their idea need them in the game-play. SNaP has also a deck of mission cards giving design goals in relation to the environment, such as “help visitors learn about the park” or “help nature thrive”. In SNaP children play and act as designers: they win the game if each ideates (at least) a smart thing for the chosen environment. By throwing dice and moving their tokens on the SNaP boards, children collect, exchange and try to combine their cards. They also share their ideas, reflect on them with others and conceptualise ideas in an ad-hoc framework for children, that is, one of the SNaP boards (see Figure 4). The SNaP design toolkit was used in two main stages of the design process. Firstly, cards were used to explore and make children familiar with the basic components of smart things, namely, the things themselves represented on environment cards, the input and output devices for making things smart. Secondly, the toolkit was used for enabling children to ideate and conceptualise ideas of smart things, and frame them with cards in the conceptualisation board of SNaP (see Figure 2). In the exploration and familiarisation stage, students had SNaP cards plus others decks of cards at their disposal. Specifically, the SNaP thing cards for students were the same as for children. SNaP input and output cards for physical devices (e.g. buttons and speakers) were also shared across generations. In addition, students had at disposal other input and output cards related to cloud-computing services, e.g. for getting the current weather conditions (input) or posting a tweet (output). During their exploration and familiarisation, students also used programmable microelectronics kits. These kits came with Raspberry Pi 3 boards. Raspberry Pi has pins for interfacing with external input and output devices, which were explored and explained with the aid of SNaP input and output cards for physical devices. Moreover, the programmable microelectronics kits had stackable HATs. These HATs or “Hardware Attached on Top” are printed circuit boards with sensors and actuators to stack on top a Raspberry Pi, simplifying their usage by those without microelectronics experience (HATs 2014). In order to start the ideation process, students had at their disposal so-called inspiration cards. These transposed ideas by children, ideated with SNaP cards and conceptualised with the SNaP board (see Figure 2). Each inspiration card came with a brief description of an IoT idea by children, clarifying their envisioned mission, the thing to make smart and the input and output devices children had adopted or imagined. Students were also given the SNaP mission cards of children so as to share the same design goals. Moreover, students had also persona cards from the Tiles cards, besides reflection cards with probes for reflecting on their ideas in terms of usability. Figure 5 shows examples of all cards given to students, divided into decks of cards related to missions, inspirations, reflections, personas, things of the outdoor environment, input (physical, cloud), output (physical, cloud). Figure 5. Examples of decks of cards of the design toolkit for university students. For conceptualising their ideas, students were given a different framework than the SNaP board used by children: students used an adapted version of the Tiles framework (Mora, Gianni, and Divitini 2017). This asked students to also reflect on personas for their missions via the related cards, and to acknowledge what inspired their smart things. The adapted Tiles framework asked students to narrate the interaction of their smart thing by means of a linear storyboard. Specifically, the storyboard explicitly asked students to narrate the intended interaction of their persona(s) for reaching their mission by means of the smart-thing conceptualised with input, output and environment cards, see Figure 6. The story-board was on-purpose minimal and constrained to make sure that the ideas would be implementable, given the design inexperience of students. Figure 6. The adapted Tiles framework for university students. In order to program and prototype their smart things, students had at their disposal Raspberry Pi 3 and hats, besides a portfolio with a recap of relevant programming snippets explored during the exploration and familiarisation steps. Digital fabrication of smart-thing prototypes was enabled through the laser cutters and 3D printers of the Bitz makerspace of Free University of Bozen-Bolzano. Table 1 recaps what was common across design toolkits, what was for children only and students only. Table 1. Recap of common elements across design toolkits, what is for children only or students only.CommonFor childrenFor studentsSNaP missionSNaP environment thingSNaP physical inputSNaP free inputcloud inputSNaP physical outputSNaP free outputcloud outputinspirationreflectionCardsTiles personaFrameworkSNaP boardadapted from TilesMicroelectronicsRaspberry Pi Different design toolkits tend to be used along the design process. Specific card-based toolkits are employed for ideating new solutions or exploring their contexts. According to Angelini et al., they are useful for supporting the ideation and collaboration among different stakeholders in workshops (Angelini et al., ‘Internet of Tangible Things,’ 2018). Sets or decks of cards, such as the IoTT Card Set, the IoT Design Deck and the Tiles Cards, are employed to aid in ideating smart things with diverse users (Mora, Gianni, and Divitini 2017; Angelini et al., “Designing the Interaction,” 2018; Dibitonto et al. 2018). Similarly, the IoT Service Kit uses different elements, such as maps, 3D printed tokens and cards, with the aim to imagine contextualised user journeys that integrate IoT services with both physical and digital touch-points (IoT Service Kit 2019). Some card-based toolkits, such as IoT Un-Kit, focus on in-situ ideation workshops with end users, with prototyping done by designers in multiple iterations until an outcome acceptable by the end users is achieved (Ambe et al. 2019). Other toolkits are specifically meant for the prototyping stage, and they are used in maker settings (Gianni, Mora, and Divitini 2019; Knowcards 2019). Making activities come with a host of toolkits in the form of Do-It-Yourself sets of microelectronics components for different prototyping boards, e.g. Blikstein (2013). In particular, Raspberry Pi is often the reference choice for IoT high-level solutions, and it has been adopted in the work reported in this paper as well (Gay 2014). There are other tools that span across multiple design stages and for diverse end users (Vitali and Arquilla 2018; De Roeck et al. 2019; Knowcards 2019). They are flexible and hence can be applied for different purposes throughout a design process, where the technology plays an important role as the backbone of Internet-connected products. Most relevant for this paper are SNaP and the Tiles cards for Smart Cities (Gianni and Divitini 2017; Mora, Gianni, and Divitini 2017; Gennari et al. 2020, 2021). SNaP contains cards designed for engaging children and teens in the design of their smart things. It has decks of cards concerning design missions and for things of the design environment (e.g. a tree if the environment is a park), besides decks of cards for inputs and outputs related to programmable IoT devices. See Figure 3, courtesy of Eftychia Roumelioti. Cards are played by children on SNaP game boards, one of which serves to conceptualise children's ideas with cards and a textual description. See Figure 4, courtesy of Eftychia Roumelioti. Tiles comes with different decks of cards, mainly for adults, such as personas. Moreover, Tiles has also a so-called generator framework for conceptualising smart thing ideas. Cards are placed on the left-more area, whereas a storyboard on the right-more area serves to narrate the intended interaction of the persona with the smart things under design. Figure 3. SNaP cards.Figure 4. The SNaP board for children to conceptualise their smart-thing ideas. SNaP cards. The SNaP board for children to conceptualise their smart-thing ideas. Besides toolkits spanning different design stages with diverse end users, IoT design can also employ techniques for cross-functional teams. One commonly used set of techniques is Google's Design Sprint Kit for collaborative sketching and decision making during ideation (Crazy 8 2016). Participants can generate a number of ideas individually via Crazy 8's and share them within their team so as to reflect and converge on fewer ideas via Sharing and Voting. Dot Vote is similar to Sharing and Voting but participants vote on each other's ideas across teams, instead of voting within teams. In the work reported in this paper, Raspberry Pi with programmable microelectronics, adapted versions of SNaP and Tiles toolkits, and the aforementioned Design Sprint techniques were all combined together and helped design across generations. Recent research concerning design for smart cities has highlighted the need of further initiatives of design with end users for their own environment (Ben 2020). Involvement of end users helps empower them and democratise the design process, resulting in technologies which are socially relevant as well as ethically justifiable (Pettersen and Boks 2008). Design initiatives with end users of IoT solutions were organised with design-thinking approaches, e.g. Melles, Howard, and Thompson-Whiteside (2012). Design thinking stemmed from the practices of working designers, for tackling ill-defined or unknown problems. It requires to be open to opportunities that emerge along the design process, which can arise during the exploration, ideation, experimentation with prototype solutions or during their evolution. The integration of exploration and development of prototype solutions makes it particularly useful in contexts involving learners, and in general, in contexts with multi-faceted and trans-disciplinary topics (Design Thinking for Educators Toolkit2019). Design workshops with end users, in particular, tend to involve them in the early ideation stage of design (Fu and Lin 2014; Fauquex et al. 2015; Klecha and Gianni 2017; weber 2017). Such workshops adopt specific toolkits for IoT design with end users. As purported in the work by Ardito et al., who designed methodologies and software for experts of a domain without experience in software development, it is fundamental to have toolkits adequate to the target users (Ardito et al. 2020). End users, with no experience of design, often require inspiration for such ideation stage, as they lack the expertise to independently ideate. One way of providing such inspiration is to include the presentation of already existing ideas during brainstorming sessions (weber 2017). Another way to enrich such ideation is to create interdisciplinary teams (Fu and Lin 2014). Fu et al., for instance, involved people with different backgrounds in interdisciplinary design teams. Involving maker communities and organising so-called make-a-thons can also help achieve such aim. The work reported in this paper takes inspiration from the reported work for designing with end users. In particular, it follows the work by Fu et al. in that it organises workshops with people from different sorts of background and across generations, albeit in a different manner: the design process across generations adopts a design-thinking approach for organising its workshops with young end users and the related design toolkits for them. The remainder of this section overviews the relevant related work concerning, respectively IoT design with young generations, and relevant IoT design toolkits. As per the UN Convention on the Rights of the Child, Article 12, children have the right to express their views on issues which affect them (Reiersølmoen, Gianni, and Divitini 2017). This includes the planning of IoT solutions for cities they live in. In 2016, the United Nations General Assembly unanimously adopted the Resolution 70/1 titled ‘Transforming our World: the 2030 Agenda for Sustainable Development’ (Desa et al. 2016). In this agenda, children and young people are considered not only as vulnerable part of the society who need to be empowered but also as the ‘critical agents of change’. They should be provided with platforms to ‘channel their infinite capacities for activism into the creation of a better world’. Therefore, in the work presented in this paper, the focus is on the youth for smart thing design for outdoor environments in urban settings. In line with this call, design initiatives have been organised with children with the goal of enabling them to take part in design and contribute with their ideas. Noticeable examples are the work reported in Scandinavian countries and also in Italy (Smith, Iversen, and Hjorth 2015). To the best of our knowledge, there are very few initiatives with children designing technology and university-age people or older people continuing their design. A relevant example for this paper is a game design process dating back to 2015 (Corral et al. 2015). Then children expressed their own game design ideas in ad-hoc game design workshops with them, and conceptualised them in game design documents (Gennari, Melonio, and Torello 2016). Their game design documents were then picked up by second-year university students who made children's ideas evolve into interactive game prototypes. This paper moves along similar lines, however, differently than in that paper, the focus of this paper is on smart things and their design. Moreover, differently than in the 2015 work, in the work reported in this paper, children's and students' design is organised around design thinking and with specific toolkits for smart things. However, there are initiatives in the area of city-planning and architecture which include ideas by school-age children taken up by university students (Lozanovska and Xu 2013; Derr 2015). For example, the work by Derr et al. reports an year long initiative integrating the ideas of children into an undergraduate university course. Such an experience by the university students was reported by the author to be of a transformative nature, making university students realise that children can actually be credible and competent contributors of ideas (Derr 2015). Similarly, in the paper by Lozanovska et al., primary school children and university students of architecture worked together; the expectation was that university students would be inspired by the creativity and imagination of children (Lozanovska and Xu 2013). Work in the area of IoT for computer-science or engineering education suggests it is feasible to bring smart-thing design into university courses, albeit such initiatives tend to be few and exploratory in nature (Burd et al. 2017; Khanafer and El-Abd 2019). Teaching IoT in this manner offers the possibility to touch upon different issues not only of computer science but also human and societal issues, all within a coherent framework. In general, in order to be considered an authentic experience, more than one layer, spanning across ideation, programming and prototyping with microelectronics should be included in smart-thing design with university students (Levy 2017). This is the approach taken in this paper, which makes university students experience all such difference stages of the design process with specific toolkits. Different design toolkits tend to be used along the design process. Specific card-based toolkits are employed for ideating new solutions or exploring their contexts. According to Angelini et al., they are useful for supporting the ideation and collaboration among different stakeholders in workshops (Angelini et al., ‘Internet of Tangible Things,’ 2018). Sets or decks of cards, such as the IoTT Card Set, the IoT Design Deck and the Tiles Cards, are employed to aid in ideating smart things with diverse users (Mora, Gianni, and Divitini 2017; Angelini et al., “Designing the Interaction,” 2018; Dibitonto et al. 2018). Similarly, the IoT Service Kit uses different elements, such as maps, 3D printed tokens and cards, with the aim to imagine contextualised user journeys that integrate IoT services with both physical and digital touch-points (IoT Service Kit 2019). Some card-based toolkits, such as IoT Un-Kit, focus on in-situ ideation workshops with end users, with prototyping done by designers in multiple iterations until an outcome acceptable by the end users is achieved (Ambe et al. 2019). Other toolkits are specifically meant for the prototyping stage, and they are used in maker settings (Gianni, Mora, and Divitini 2019; Knowcards 2019). Making activities come with a host of toolkits in the form of Do-It-Yourself sets of microelectronics components for different prototyping boards, e.g. Blikstein (2013). In particular, Raspberry Pi is often the reference choice for IoT high-level solutions, and it has been adopted in the work reported in this paper as well (Gay 2014). There are other tools that span across multiple design stages and for diverse end users (Vitali and Arquilla 2018; De Roeck et al. 2019; Knowcards 2019). They are flexible and hence can be applied for different purposes throughout a design process, where the technology plays an important role as the backbone of Internet-connected products. Most relevant for this paper are SNaP and the Tiles cards for Smart Cities (Gianni and Divitini 2017; Mora, Gianni, and Divitini 2017; Gennari et al. 2020, 2021). SNaP contains cards designed for engaging children and teens in the design of their smart things. It has decks of cards concerning design missions and for things of the design environment (e.g. a tree if the environment is a park), besides decks of cards for inputs and outputs related to programmable IoT devices. See Figure 3, courtesy of Eftychia Roumelioti. Cards are played by children on SNaP game boards, one of which serves to conceptualise children's ideas with cards and a textual description. See Figure 4, courtesy of Eftychia Roumelioti. Tiles comes with different decks of cards, mainly for adults, such as personas. Moreover, Tiles has also a so-called generator framework for conceptualising smart thing ideas. Cards are placed on the left-more area, whereas a storyboard on the right-more area serves to narrate the intended interaction of the persona with the smart things under design. Figure 3. SNaP cards.Figure 4. The SNaP board for children to conceptualise their smart-thing ideas. Besides toolkits spanning different design stages with diverse end users, IoT design can also employ techniques for cross-functional teams. One commonly used set of techniques is Google's Design Sprint Kit for collaborative sketching and decision making during ideation (Crazy 8 2016). Participants can generate a number of ideas individually via Crazy 8's and share them within their team so as to reflect and converge on fewer ideas via Sharing and Voting. Dot Vote is similar to Sharing and Voting but participants vote on each other's ideas across teams, instead of voting within teams. In the work reported in this paper, Raspberry Pi with programmable microelectronics, adapted versions of SNaP and Tiles toolkits, and the aforementioned Design Sprint techniques were all combined together and helped design across generations. Publisher Copyright: © 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022/11/18
Y1 - 2022/11/18
N2 - A smart bracelet that reacts to a person's heartbeat. A smart bench that invites passers-by to sit close. These and others are smart things, part of the Internet of Things (IoT) and people's lives. However, people are mainly IoT consumers and rarely given the possibility of becoming IoT creators. This paper presents a case study concerning the design of smart things for outdoor environments, with end users as the main creators. Ideas of smart things were collaboratively conceptualised by child end-users with a card-based board game. Their ideas were taken up in the form of inspiration cards within a bachelor's first-year course, by students coming from different high schools. Students started from children's ideas as inspiration triggers and collaboratively evolved some of them into interactive smart-thing prototypes. The paper concludes by reflecting on its results and drawing lessons for future editions of cross-generational workshops related to IoT design with end users.
AB - A smart bracelet that reacts to a person's heartbeat. A smart bench that invites passers-by to sit close. These and others are smart things, part of the Internet of Things (IoT) and people's lives. However, people are mainly IoT consumers and rarely given the possibility of becoming IoT creators. This paper presents a case study concerning the design of smart things for outdoor environments, with end users as the main creators. Ideas of smart things were collaboratively conceptualised by child end-users with a card-based board game. Their ideas were taken up in the form of inspiration cards within a bachelor's first-year course, by students coming from different high schools. Students started from children's ideas as inspiration triggers and collaboratively evolved some of them into interactive smart-thing prototypes. The paper concludes by reflecting on its results and drawing lessons for future editions of cross-generational workshops related to IoT design with end users.
KW - design thinking
KW - design toolkit
KW - end user development
KW - Internet of things
KW - IoT
KW - smart thing
UR - http://www.scopus.com/inward/record.url?scp=85129484058&partnerID=8YFLogxK
U2 - 10.1080/0144929X.2021.1979654
DO - 10.1080/0144929X.2021.1979654
M3 - Article
AN - SCOPUS:85129484058
SN - 0144-929X
VL - 41
SP - 3281
EP - 3300
JO - Behaviour and Information Technology
JF - Behaviour and Information Technology
IS - 15
ER -