9.2.1 Fostering an Intuitive Understanding of Statics
Can apprentices develop an intuitive understanding of statics without going into the math- ematical formalisms? In other learning contexts, previous works have shown that this goal could be reached (described in Chapter 2). Hence, we believe that the answer to this question is still positive. The aim of this dissertation has been to explore how to fulfil our purposes within the vocational education context.
In our last study, the improvements observed in some apprentices indicated that our aug- mented reality environment can help in developing statics reasoning abilities, although it was not possible to show a significant learning gain. One might wonder whether there was any improvement compared to the performance achieved by apprentices in study presented in chapter 5. When looking at Figure 9.1 it is possible to notice that the relative learning gains were not statistically different in the four experimental conditions. Ironically, the highest median was found when apprentices worked with non-interactive structures and received the simple feedback “correct/incorrect” from the experimenters. Besides the concerns about the validity of the pre-test and post-test (see below), the two studies were not meant to prove the existence of one best solution. The first study has highlighted that activities meant to foster a conceptual understanding of statics did not necessarily benefit from hands-on exploration. The result was not novel and gave support to previous claims that the manipulation of physical tools does not guarantee learning (McNeil and Jarvin, 2007; Han et al., 2009; Alfieri et al., 2011). Our contribution has been to show the reason why this happened by comparing the gaze behaviors of apprentices and experts. The spring mechanisms that we designed to make the models interactive and to provide a visual feedback of the axial forces acting on them, absorbed participants’ attention at the expense of other parts of the models that experts took into account. These parts were relevant to understand how forces balanced each other and reached the equilibrium. On the contrary, the gaze behavior of apprentices who worked in the non-exploratory condition was closer to the experts’ one. Based on these results, we proposed the augmentation through StaticAR as a way to overcome the observed limitations. The presence of small-scale wooden models remained a crucial aspect of our AR environment, but we chose not to pursue the idea of augmenting interactive structures after weighting up the findings and other factors, like the time to manufacture them and its cost, following the suggestion in (Klahr et al., 2007). Nevertheless, adopting StaticAR in combination with
9.2. Contributions
interactive models definitely deserves future explorations and it is likely that apprentices would benefit from a hybrid approach of augmented reality and manipulative tools.
The visualizations available in StaticAR “reveal the invisible” and go obviously beyond what physical models can show. The tool allows apprentices and teachers to quickly run simulations. The many parameters usually required to setup the structural analysis scenarios (like Young’s modulus, moment of inertia, etc.) emerge from the interface in the form of wood species, timber strength class and size of rafters, something that have a concrete meaning in carpentry. As we could only study a part of the several functions and visualizations available, we chose those related to the analysis of the axial forces which is relevant to the study of roof structures. We decided to keep the springs in the digital augmentation because they show the nature of such forces (compressive and tensile) in an intuitive way, but we combined them with a slightly more formal representation, namely arrows. The arrows would convey the way forces interact and reach the static equilibrium which were the aspects that the spring mechanisms of chapter 5 did not express to apprentices. To investigate whether this combination would work, we created an activity in which pairs of apprentices used the two representations to collaboratively solve statics problems. The outcome of the collaboration was not constant, but in several occasions apprentices’ explanations reflected the intuition of statics principles. The study has also the merit of identifying part of the difficulties and misconception encountered by apprentices. To our knowledge, this has been rarely investigated in the vocational domain. Taxonomies of the typical errors made by students who start approaching statics, and more generally classical physics, are only available for high school and undergraduate students (Steif and Dantzler, 2005). In this sense, we have provided additional information to better shape the instructional materials available to apprentices and vocational teachers.
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Tangible Feedback Verbal Feedback Arrows Representation Springs Representation
Experimental Condition
Relativ
e Lear
ning Gain
Study Chapter 5 Chapter 8
Chapter 9. General Discussion
9.2.2 The role of physical objects in AR systems
We have been able to provide empirical support for the positive impacts that tangible interac- tion could have on users’ experience as described by other authors (Marshall, 2007; Antle and Wise, 2013). The contribution came mainly from the application of the eye-tracking methods that has recently become more common in research areas of tangible interaction and TUIs (Schneider et al., 2015, 2016). In particular, the claims that attribute to tangibles the advantage of promoting a more readily comprehension of 3D shapes compared to digital visualizations found confirmation in our third study too (the one about the shifts of visual attention). Even though in that setup the manipulation of the physical structures did not have any effect on the AR experience, one of the findings was that the aid associated to the perception of complex geometries was reflected in a higher number of fixations in the participants’ gaze when they were looking at challenging structures.
In both the studies of chapters 4 and 7, the participants worked within mixed-reality environ- ments where they needed to link the virtual and the real-world spaces. The study of chapter 7 confirmed that this connection could be facilitated by the physical entities since they exist in both spaces and act as anchors and spatial cues. Gaze-shifts were due to participants’ change of position and it is very likely that the same motivation brought participants in the study of chapter 4 to look at the physical shape. In that case, the anchoring function was even more precious because in the experimental setup the physical space (the workspace printed on paper) and the digital space (the screen) were not overlapping. The issue of sustaining users’ spatial perception is well known in mixed-reality research, especially for what concerns the design of immersive environments where the user cannot rely on natural multi-sensory during locomotion (Darken and Peterson, 2001). In outdoor environment it has been shown that looking at the real-world surroundings and introducing artificial spatial cues in the AR appli- cations help users to keep the spatial orientation. (Veas et al., 2010; Tatzgern et al., 2015). Our findings suggested the possibility to use physical objects as spatial cues in indoor mixed-reality systems too.
Another result from the first study was that participants kept on referring to the physical interface even when its shape began to diverge from the shape of its digital counterpart, which made us reject our tokenization hypothesis. This finding should be discussed in the light of the fact that tangibles usually cannot accommodate the changes of their digital representations (few exceptions like (Follmer et al., 2013) ). As a consequence, in application where the digital entities mutate (e.g. CAD) either the digital shape changes according to the physical one or the tangibles are mere controllers (examples in (Marner and Thomas, 2010; Wendrich and Kruiper, 2017) ). We showed that tangibles can keep their representational role in this kind of applications too, in the sense that, even when the physical correspondence is partially lost, they embed the properties of the digital representations that go beyond the properties of tokens (presence, position, proximity). Furthermore, the loss of physical correspondence was, to some extent, actively avoided by the participants. Our tangible interface could not accom- modate the changes of its digital representation, so participants changed their task-solving strategy in order to preserve that part of information they probably could not reconstruct from 138