Chapter 13 Reflecting on Maker Education as a Potential Context for the Development of Spatial Ability

In: Maker Education Meets Technology Education
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Jeffrey Buckley
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Abstract

Based on significant evidence of the benefit of increasing learners’ levels of spatial ability, its development has become a focal agenda for many educators, educational researchers, and educational policy makers. While to date spatial ability has received little attention in research surrounding maker environments, maker education has the potential to be a particularly auspicious context for its development within learners. In this chapter, the seven case studies of maker education in this edited volume from Kenya, Mexico, China, the Netherlands (×2), Denmark, and South Korea are reflected upon through this specific lens. Each case study provoked a different dimension to this reflection, with questions of how spatial ability relates to “making”, how it’s development should be prioritised against other already noted aims of maker education, and what could be the implications of making spatial ability development an explicit goal of maker education inductively arising. These questions are unpacked, and it is envisioned that this reflection will underpin ensuing advances on if and how spatial ability development should be further examined or integrated into maker education environments.

1 Introduction

Over the last decade, the “maker” label has become attached to a broad range of educational activities associated with craft and construction (Godhe et al., 2019). These range from formal to informal activities, include “make” elements that are both physical (e.g., kit assembly) and virtual (e.g., 3-dimensional modelling), and involve the use of a spectrum of tools from basic hand-tools through to rapid prototyping and automation. Maker education as a concept has to a degree grown in ambiguity, and consideration of this is an important preface to the statement that a direct relationship between maker education and spatial ability has not been the subject of much, if any, empirical investigation to date. To illustrate this, a search on Google Scholar for “maker education” AND “spatial ability” at the time of writing this chapter (19th of February, 2022) returned only 23 unique manuscripts. Unfortunately, of these, two were book chapters which I could not get access to, and two were articles published in Korean and one was an edited book published in Italian which are languages I cannot read. Of the remaining 18 published works,1 only 4 described an empirical link between spatial ability and maker related activities, of which 3 were qualitative observations (Bhaduri et al., 2021; Boyle, 2019; Simpson & Kastberg, 2022) and 1 was a quantitative post-test only boxplot from an undescribed instrument purporting to measure “spatial thinking skills” (Akshay et al., 2018).

Investigating this potential relationship could be particularly fruitful given the significant evidence underpinning the relationship between spatial ability and Science, Technology, Engineering, and Mathematics (STEM) in general (Wai et al., 2009) and the growing evidence of its specific importance in technology education (Buckley et al., 2022), a subject area with much commonality with maker education. While a direct association between maker education as a concept and spatial ability has been speculated, theorised, qualitatively observed, and identified as desirable, it has not yet been the focal subject of any formal investigation. That said, there is much empirical evidence associating spatial ability and signature activities of maker education such as craft (Bailey & Sims, 2014) and design (Lin, 2016) in non-maker specific contexts, a notable distinction given the importance of context and environment both in and for learning. Before delving into a reflection on the maker education case studies in this volume through the lens of spatial ability development, as spatial ability has not been extensively studied in this context it is worth framing what spatial ability is as an intelligence construct so as its potential place in maker environments can be better considered.

2 Framing Spatial Ability

Schneider and McGrew (2018), who together for the last decade have been leading the development of the Cattell-Horn-Carroll (CHC) model of intelligence – the current most comprehensive framework of cognitive abilities – lay out that among other criteria the qualification of a cognitive ability requires that it is both plausibly linked to functions that evolve to help humans survive and reproduce and that it should have practical use or validity. From an educational perspective the core focus has been on defining spatial ability as a psychometric construct and investigating its predictability and explanatory power for desirable outcomes such as performance and retention. It is here where this chapter will centre and how the practical use and validity of spatial ability will be discussed. However, it is worth acknowledging the evolutionary lens offered by Geary (2022) who comments that “from an evolutionary perspective, spatial abilities are an aspect of folk physics that is supported by brain and cognitive systems that enable organisms to engage in the physical world”. In discussing the evolutionary functions of spatial ability, Geary (2022) predominantly focuses on navigation and wayfinding, movement detection, and closure, which relate closely to Schneider and McGrew’s criterion that spatial abilities can be linked to helping humans survive and reproduce. Geary’s (2022) comments on multiple facets of spatial ability also offers a nice introduction to how spatial ability is understood today. It is a broad cognitive domain constituting of several narrow and discrete cognitive factors associated with the processing of spatial information.

The construct of spatial ability as an intellectual factor was first described by Sir Francis Galton lein in the late 1800s. Specifically, Galton referred to a “visualising faculty” and even at this early stage Galton’s observations were that spatial ability was multidimensional (Galton, 1880). For example, Galton described his visualising faculty as encompassing capacities such as being able to recall a clear and complete mental image of any recently examined object – a skill which today relates to the spatial factor of imagery – and to being able to mentally visualise that object freely from any perspective – a skill which, depending on whether egocentric or allocentric reasoning is involved and whether the object is simple or complex, would today relate to either the visualisation, mental rotation, or spatial orientation spatial factors. Since Galton’s pioneering work, the construct of spatial ability was evolved during the 1900s through a series of seminal empirical psychometric studies, with each adding to or refining its dimensions. Three central research questions guided this period of inquiry (Eliot & Smith, 1983). Initial focus was placed on examining whether spatial ability had incremental validity beyond a general intelligence (g) factor, i.e., was there a cognitive ability associated with the processing of spatial information that was independent from and practically useful beyond general intelligence. Next, after this was established, emphasis shifted to determining the sub-components of spatial ability. Finally, following the identification of a series of these sub-components, known as “spatial factors”, efforts were invested into determining the extent to which these related to each other and to other cognitive factors not associated with spatial ability. Significant contributions in this time, for example and chronologically, came from Thurstone (1936), Holzinger and Harman (1938), Guilford and Lacey (1947), French (1951), Guilford, Fruchter and Zimmerman (1952), Zimmerman (1953), Lohman (1979), Lohman, Pellegrino, Alderton, and Regian (1987), Horn (1988), and Carroll (1993). These works illustrate how the language associated with spatial ability changed over time and how, depending on the nature of the testing instruments used, different spatial factors were observable.

Today, within the CHC theory, spatial ability is formally termed “visual-processing” and is described as “the ability to make use of simulated mental imagery to solve problems — perceiving, discriminating, manipulating, and recalling nonlinguistic images in the ‘mind’s eye’” (Schneider & McGrew, 2018, p. 125). Others have described spatial ability as “the ability to generate, retain, and manipulate abstract visual images” (Lohman, 1979, p. 126), the “innate ability to visualise that a person has before any formal training has occurred” (Sorby, 1999, p. 21), and as “the ability to visualise, manipulate and interrelate real or imaginary configurations in space” (Gaughran, 2002, p. 3). In contrast to a broad descriptor, Sutton and Allen (2011, p. 5) describe spatial ability relative to specific task performance in saying that it is “the performance on tasks that require: (a) the mental rotation of objects; (b) the ability to understand how objects appear in different positions; and (c) the ability to conceptualise how objects relate to each other in space”. Additionally, Wai et al. (2009, p. 827) define spatial ability through a predictability lens, referring to it as “a salient psychological characteristic among adolescents who subsequently go on to achieve advanced educational and occupational credentials in (Science, Technology, Engineering, and Mathematics) STEM”.

Given these different definitions, it is important to consider Meehl’s (2006) noting of two issues in the context of intelligence constructs in that verbal definitions such as those just cited are neither sufficiently comprehensive nor do they command consensus. The previous descriptions, while not incorrect, are not complete. Instead, Meehl’s (2006) recommendation is to define such constructs empirically, with verbalisations instead being considered as descriptive. To this end, spatial ability is currently best defined through empirical frameworks such as the CHC theory. In this framework, spatial ability is defined as a second-order (broad) cognitive factor, reflective of a number of first-order (narrow) spatial factors. In the most currently iteration of the CHC theory (Schneider & McGrew, 2018, pp. 126–128), 12 narrow spatial factors are listed and described as:

  1. Visualisation: The ability to perceive complex patterns and mentally simulate how they might look when transformed (e.g., rotated, twisted, inverted, changed in size, partially obscured).

  2. Speeded rotation: The ability to solve problems quickly by using mental rotation of simple images.

  3. Imagery: The ability to voluntarily mentally produce very vivid images of objects, people, or events that are not actually present.

  4. Flexibility of closure: The ability to identify a visual figure or pattern embedded in a complex distracting or disguised visual pattern or array, when one knows in advance what the pattern is.

  5. Closure speed: The ability to quickly identify and access a familiar, meaningful visual object stored in long-term memory from incomplete or obscured (e.g., vague, partially obscured, disguised, disconnected) visual cues of the object, without knowing in advance what the object is.

  6. Visual memory: The ability to remember complex images over short periods of time (less than 30 seconds).

  7. Spatial scanning: The ability to quickly and accurately survey (visually explore) a wide or complicated spatial field or pattern with multiple obstacles, and identify a target configuration or identify a path through the field to a target endpoint.

  8. Serial perceptual integration: The ability to recognize an object after only parts of it are shown in rapid succession.

  9. Length estimation: The ability to visually estimate the length of objects (without using measuring instruments).

  10. Perceptual illusions: The ability not to be fooled by visual illusions.

  11. Perceptual alternations: Consistency in the rate of alternating between different visual perceptions.

  12. Perceptual speed: The speed and fluency with which similarities or differences in visual stimuli can be distinguished.

To operationalise this definition in empirical investigations (which is important as it is operational definitions that evidence of the importance of spatial ability directly relate to), spatial ability can be modelled as a latent variable. It is itself not directly measurable or observable. Instead, data is collected through the administration of psychometric tests to a cohort of participants which are indicative of a number (usually at least three) of first-order spatial factors (listed above). These narrow spatial factors are directly measurable and through factor analytic methods the “shared” variance is defined as spatial ability (cf., Buckley, 2020).

In practice, studies examining the relationship between what they describe as spatial ability and an educational outcome such as performance or retention often are not this comprehensive. Instead, one spatial factor is usually the subject of investigation which is often the visualisation factor when participants are adolescents or older. Other factors have also been studied, just to a lesser extent and for this chapter the visualisation factor will be a focus (cf. Buckley et al., 2018). The visualisation factor is the strongest loading first-order spatial factor on the broader second-order factor of spatial ability (Ebisch et al., 2012; Schneider & McGrew, 2018). In other words, it is the most characteristic factor for describing spatial ability more broadly. Like spatial ability itself, it is best described empirically rather than verbally. However, as this is a directly observable cognitive ability its empirical definition is not through a framework, but it is defined based on the instruments used as indicators of it. As described above, the visualisation factor involves the mental manipulation of complex geometries, where complex often means 3-dimensional, and this manipulation can involve mental rotations, mental cutting, mental folding, etc. Good practice would involve the use of a number of instruments, each of which involving a different one of these mental operations, and visualisation would be defined as a composite score across each of these. Figure 13.1 provides an example item from one common psychometric test of visualisation, the Purdue Spatial Visualisation Test: Visualisation of Rotations (PSVT:R: Guay, 1977). In the PSVT:R, participants are shown a stimulus geometry in an initial state (top left) and an end state (top right). The end state is derived by the rotation of the object by up to three 90° rotations. In Figure 13.1, one 90° rotation clockwise about the y-axis brought the stimulus geometry from its initial state to the end state. A different geometry is then provided (centre) and the task is to apply the same rotation(s) that the stimulus geometry moves through to it, in this case one 90° rotation clockwise about the y-axis. Five possible solutions are then provided (bottom) and one of these is the correct end state. The participant must indicate which they believe it to be. In Figure 13.1 the correct answer is “D”.

Figure 13.1
Figure 13.1

Example item from the instructions of the Purdue Spatial Visualisation Test: Visualisation of Rotations (PSVT:R: Guay, 1977)

While there are multiple tests which can serve as operational definitions for spatial ability, the PSVT:R is a common example and one which has been used previously in technology education (Buckley et al., 2019; Julià & Antolì, 2018; Julià & Antolí, 2016; Lane & Sorby, 2021; Šafhalter et al., 2022). It is performance on this test and other similar tests (see also Figure 13.2) that is used to indicate learners levels of spatial ability, and this cognitive ability is particularly useful to education researchers, educators and education policy makers as it (1) is predictive of STEM outcomes such as educational performance and the attainment of advanced qualifications (Wai et al., 2009), (2) can be developed through “spatialised” pedagogical approaches (Newcombe, 2017) and dedicated interventions (Uttal et al., 2013), and (3) the development of spatial ability has been found to transfer back to improved STEM education performance (Sorby et al., 2018). Interestingly and also usefully, evidence is emerging that spatial ability itself can be developed through the teaching of specific subjects such as mechanics (Munoz-Rubke et al., 2021). Now, through a series of case studies, the role of spatial ability in maker education can start to be theorised more formally, and given the lack of consideration it has been given to date in this context, spatial ability could potentially become a new and important dimension of maker education agendas.

Figure 13.2
Figure 13.2

Example of the item structure for the Visual Puzzles subtest of the 4th edition of the Wechsler Adult Intelligence Scale (WAIS-IV; adapted from Pearson Assessments, 2022)

3 Review of Maker Education Case Studies

The seven case studies on the implementation of maker education in this volume formed that basis of this reflection. These case studies come from Kenya, Mexico, China, Denmark, South Korea, and, two from The Netherlands, and provide rich first-person accounts of maker education in context. A challenge in reading these while thinking about how maker education could provide a context for the development of spatial ability was presented when I noticed that spatial ability was not directly mentioned from any perspective in any of the chapters. This, given the previously described literature search, was not surprising but it is important to note that the discussion herein is not a synthesis of the case study authors explicit commentary around spatial ability. Further, and exciting from my perspective, is that while there was overlap each case study provoked me to think about spatial ability and maker education in a new way. It is very likely that more case studies would have resulted in even more dimensions to this reflection, suggesting that a grounded theory-based inquiry to extend this reflection could have significant merit. While each case study provided a unique perspective on how spatial ability could relate to maker education, three broader themes stood out which given the nature of this reflection seem most appropriately framed as questions: (1) how does spatial ability relate to “making”? (2) how should spatial ability be prioritised within maker education? and (3) what are the implications of spatial ability development being an explicit intended goal of maker education? Each of these questions is unpacked in the next sub-sections.

3.1 How Does Spatial Ability Relate to “Making”?

Perhaps the most obvious question to ask regarding the place of spatial ability within maker education is how it relates to “making” in maker environments. Dougherty’s (2016, p. 143) definition that making is “the process of realising an idea and making it tangible” is useful to keep in mind in this regard. Making was naturally a core thread across each case study, however two in particular – those from Kenya and Mexico – framed making in ways that the place of spatial thinking became more apparent.

In their chapter (Chapter 6), Westerhof, Gielen, van Boeijen and Jowi describe a maker workshop delivered by the Sustainable Rural Initiatives (SRI) through a local community centre in Kisumu County in Kenya. Developed in collaboration with the Industrial Design Engineering school at TU Delft, the workshop centred around children making “appropriate toys” from free local materials and was designed around the three phases of exploring, building, and presenting. In their chapter, two figures are provided which show the toys in the process of being made and then being presented. One shows what appears to be a house with a bamboo internal support structure and clay walls and roof. The final artefact, at least as a hazy idea, would have needed to be visualised before the building process. It also seems reasonable to infer that the thinking about how the materials would work together, such as using clay to hold the bamboo in place and positioning the bamboo in such a way that it would support the clay, would benefit from imagining multiple possible solutions which is an inherently spatial thought process. In the second image, finished toy cars made from clay are presented. While of course trial and error could have been used in this and in the previous house example, thinking spatially about the proportions of components such as the wheels and how to assemble them seems more efficient, suggesting a benefit from spatial ability.

Núñez-Solís, Silva, Madahar, and Eskue provide a very different perspective on making in their chapter. In relation to their case study (Chapter 5), which centres around upcycling and the circular economy, they discuss how the Mexican company Recicla Electrónicos México S.A de C.V. created “EcoMakerKits” which they provide to schools as educational materials. Their “EcoMakerStore” provides a wider variety of kits – sets of components which can be assembled into a working product – but they focus on the Bluetooth speaker and ventilator kits in their chapter. I visited their website2 to see the kits on offer in more detail and was immediately reminded of Gaughran’s (2002) conference paper where he discusses a continuum of spatial factors using the analogy of a plug-top being mentally disassembled and reassembled. While scholarship around spatial factors has progressed since Gaughran’s (2002) publication, kit assembly as an activity seems very much reflective of spatial tests such involving visual puzzles – indicators, like the PSVT:R, of the visualisation spatial factor. Figure 13.2 shows what the items in these types of spatial tests look like (with actual test items being more difficult). Here, a puzzle is provided (top) and a selection of 6 “pieces” (bottom) are provided. The problem involves identifying which pieces are required to make the full puzzle, and a specific number of pieces must be selected. In Figure 13.2, for example, pieces 5 and 6 are sufficient but the task is to identify three pieces so the correct solution would be pieces 1, 2, and 6.

Assembling a kit is a similar activity where the puzzle from Figure 13.2 represents the assembled product and the pieces from Figure 13.2 represent the kit’s components. However, it is possible that spatial reasoning could be circumvented (cf. Buckley et al., 2022). Núñez-Solís, Silva, Madahar, and Eskue provided a video tutorial to accompany their kits which, depending on how it is used, could remove the need to think about how the components go together. With a video showing step-by-step how to assemble each piece, learners do not need to think about how components fit together either physically and within a system of moving parts. The use of kits could be both an aspect of maker education which elicits spatial thinking or even develops it, but pedagogical decisions need to be taken into account in terms of how they are used.

3.2 How Should Spatial Ability Be Prioritised within Maker Education?

Considering that spatial ability seems aligned with capability in terms of making or building and that also, such as through the use of kits, maker education could be an environment where spatial ability could be developed, the question of how it should be prioritised relative to other goals needs to be asked. With this in mind, I was particularly intrigued by Pols and Hut’s case study (Chapter 9) on maker education in the Netherlands. In their chapter, they describe the development of a makerspace for use by students in two mandatory courses in an applied physics programme in Delft University. As a brief note, it is worth pointing out that the learning outcomes in these courses highlight another dimension to making in maker education that spatial ability has been empirically linked with, those of “use simulation software” and “make 2D (vector) and 3D models” (Basham & Kotrlik, 2008; Dilling & Vogler, 2021; Lei et al., 2009; Shavalier, 2004; Storey Vasu, & Kennedy Tyler, 1997). What was of particular interest was that the authors stated a lot of time was “wasted” on simple “jury rigged” solutions. They provided a photograph of such a prototype, which included a lot of duct tape, cork, and string, and while it was a prototype and less polished it was reminiscent of the activity from the Kenyan case study where toys were made from clay. Maker spaces were introduced in the case study to facilitate moving beyond such prototypes in the applied physics courses by streamlining activity so that iterative prototyping and testing and the development of specific advanced technical skills could be more feasible. From a technical perspective, advanced manufacturing skills are now more likely to be developed and the students will progress through more of a design process that is contextually relevant. However, if the development of spatial ability were to be an explicit goal in this environment, I would hypothesise that it is the initial prototyping activity where solutions need to be conceived and basic materials need to be creatively imagined into a model where this development would be fostered more (although this would need to be empirically evidenced). A balance between disciplined learning and general spatial development would require considered pedagogical decisions.

Building on this idea, Gu and Yang’s chapter (Chapter 8) in which they describe a case study of maker education in China highlights another pedagogical dimension to spatial ability development. Gu and Yang, similar to Núñez-Solís, Silva, Madahar, and Eskue in Mexico, discuss maker kits, however the real emphasis was on a 5-week (10 classroom hour) design task where children had to make a desk lamp. Much like in Westerhof, Gielen, van Boeijen and Jowi’s case study from Kenya, the children were tasked with using locally available material (although could spend up to ¥15, which is approximately €2) which they had to source themselves. Gu and Yang provided a photograph of the students finished work and the 10 lamps shown were made from a variety of materials such as paper cups, a woven wooden basket, a shuttlecock, and what appear to be parts of various toys. They really are quite innovative and personalised. Interestingly, as part of the case study, the authors listed the problems the children faced with the task. To paraphrase, they included electronic components such as wires or batteries not being correctly installed and the joining of different parts not being strong enough and requiring, for example, more glue. The problems faced were not spatial, and on reflection it is not clear that the task required spatial thinking. If it did it was trivial. The main learning outcomes were associated with electronics and “creative literacy”. This highlights an important point that just because designing and making have been linked with spatial ability, it does not mean that merely including these activities within an educational task will elicit a cognitively spatial response. If an educator intends for a task to require spatial ability or in particular to develop it, the task needs to be designed accordingly. This includes, for example, “spatialising” the task, making spatial reasoning an efficient strategy for learners when responding to the task, and ensuring sufficient cognitive demand of this nature. Designing such tasks, if spatial ability development was to be a goal, would also require both consideration of the actual artefact and building procedure (such as the use of a kit, the provision of instructions, the sourcing of materials, etc.), and consideration of pedagogical strategy where learners are encouraged to visualise problem solutions.

Finally in this theme is the case study offered by Pijls, van Eijck, and Bredeweg (Chapter 4), which also comes from The Netherlands. This chapter was particularly interesting from the perspective of spatial ability development, as the authors describe a series of interviews with makerspace coaches and children who attended a makerspace with one quote being “thinking is 3D is what everybody has to learn”, and yet despite this I did not think it should be primarily part of the previous section on how spatial ability is related to making. I was instead struck by a series of comments about the importance of accessing makerspaces and their more general benefits for children which has instead made me reflect on whether spatial ability development should be a priority. For context, Pijls, van Eijck, and Bredeweg describe how the Amsterdam Public Library created a network of 10 makerspaces called Maakplaats021. Each makerspace was located in a library location and contained 3D printers, a laser cutter, a vinyl cutter, laptops, glue guns, sewing machines, and various other small pieces of stationary (e.g., pencils, paints, etc.). Library staff were recruited as makerspace coaches. From the interviews, the authors identified a series of themes which related to skills development, the variety of potential learning opportunities, developing interest in programming, community collaboration, developing confidence, and developing spatial ability (referred to as “thinking in 3D”). There were more insights in the chapter that related to the makerspace coaches, but these are not described here. Of all the chapters, this was perhaps the most pointed in the series of benefits to young people from engaging with makerspaces, and it has caused me to reflect on whether developing spatial ability should be considered as a priority. Of course, it may be a very important effect of maker related activity – and it is clear how this can be from this and the other chapters – but it is something that should be a goal? Maybe, but in my opinion not at the expense of some of the other benefits of makerspaces. The chapter is filled with quotes from children who were proud of their creations, had developed skills (like sewing) enabling them to help their parents at home, learned basic social and hygiene skills, and proclaimed interest in technology and making due to exposure they may otherwise not have received. Most impactful (for me) was the following quote in the chapter:

One week ago, we were sitting with the children, chatting a bit and I asked them ‘Who feels happy now?’ Many raised their hands.

In my opinion, spatial ability development can be a priority of makerspaces, but perhaps not the priority.

3.3 What Are the Implications of Spatial Ability Development Being an Explicit Intended Goal of Maker Education?

Across the previous case studies this reflection inductively provoked thinking around when, where, and how spatial ability manifests in maker environments and if it was to be a more explicit agenda how would this be balanced with disciplinary learning outcomes. On reading Holm Kanstrup, Iversen, Van Mechelen, Dindler, and Wagner’s chapter, a potential value of the development of spatial ability being an explicit agenda of maker education became apparent. The authors present a framework for the establishment of sustainable makerspaces. They derived this from their experiences of 11 cases across Denmark and “sustainable” in this chapter relates primarily to funding sustainability for makerspaces. The problem, as the authors put it, is that makerspaces receive a form of development funding to get established and to operate in their first few years, but then struggle to secure and generate fundings to continue beyond this period. In response, the authors developed a six-step framework which they provided to stakeholders through workshops as a way of supporting their long-term planning. The six steps, or six objectives for stakeholders, involved:

  1. Understanding the complexity of a makerspace initiative.

  2. Hands-on introduction to makerspace education.

  3. Establishing the grand narrative of a maker space initiative.

  4. Developing the makerspace initiative within the existing municipality landscape.

  5. Confirmation and articulation of management support for the makerspace initiative.

  6. Choosing and purchasing technologies for the maker space.

In their chapter, the authors provide more detail on each of these, but the third step in particular is critical. The authors note a general aim of these makerspaces – effectively the “grand narrative” – as being to “[increase] children’s interest in creating digital technologies and understanding how emerging technologies affects our everyday lives”. This, based on the previously described case studies, is an aim generally mediated through make-based activity. As discussed, spatial ability could be developed through maker activity with purposefully designed activities and depending on other intended learning outcomes, this could be included without much disruption. Could the addition of spatial ability development, subject to qualifying this through empirical investigation, support the acquisition of further funding? I am remined of the work of Uttal et al. (2013) who through a meta-analysis of spatial training studies identify g = .40 as the “most conservative effect size” from their work for the effect of spatial training on improving spatial ability. To give context to this, they note that if spatial ability were to be improved by this much in a population of people, the number of people in that population who have the level of spatial ability associated with receiving a bachelor’s degree in engineering would approximately double.3 To have such a significant and tangible impact, in addition to the currently noted aims of maker education, would certainly aid efforts in securing funding through the explication of additional societal benefit.

4 Consolidation and Conclusion

A seventh case study relating to maker education in South Korea provided by Kwon provoked similar reflection to those previously discussed. An emphasis was placed on fun, making was contextualised in terms of 3D printing and programming, and the alignment of maker education and formal secondary education was discussed. Many considerations have been raised relating to the place of spatial ability in maker environments both empirically (e.g., how does it relate to building and craft?) and epistemologically (e.g., should spatial development be an explicit agenda?). What Kwon’s chapter uniquely presents is how this conversation can, and perhaps should, now be continued. Kwon describes MAKERS (a pseudonym), a professional learning community (PLC) responsible for a technology teachers’ association in Seoul. Through interviews with four technology teachers who are members of MAKERS, rich insight is gained into their thoughts about both maker and technology education in South Korea and the relationship between them. One specific comment from a teacher (Daehan, also a pseudonym) encapsulates my concluding thoughts. Daehan said

There are many misconceptions about technology and technology education, including in schools. I was worried and upset about that. However, when technology teachers get together to share their concerns and discuss their own solutions, it miraculously leads to better practice.

Shared discourse from maker education stakeholders can lead to improved practice, and the nature of this improvement is defined by those stakeholders. Educators who are involved in maker education are perfectly placed to collaboratively consider intended outcomes. In terms of the development of spatial ability being one of these goals, existing research supports the view that it is possible and could have significant societal and individual learner impact. Dialogue between educators and researchers (and other relevant stakeholders) could advance this agenda in a meaningful and contextually appropriate way.

Notes

1

These included 11 articles published in academic journals, 4 articles published in conference proceedings, 2 Doctoral theses, and 1 conference proceeding published between 2015 and 2022, with most publications coming from 2019 (n = 3), 2020 (n = 3), and 2021 (n = 7).

3

Based on data from Wai et al. (2009, 2010).

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