Tablet computer | EPFL Graph Search

A tablet computer, commonly shortened to tablet, is a mobile device, typically with a mobile operating system and touchscreen display processing circuitry, and a rechargeable battery in a single, thin and flat package. Tablets, being computers, have similar capabilities, but lack some input/output (I/O) abilities that others have. Modern tablets largely resemble modern smartphones, the only differences being that tablets are relatively larger than smartphones, with screens or larger, measured diagonally, and may not support access to a cellular network. Unlike laptops (which have traditionally run off operating systems usually designed for desktops), tablets usually run mobile operating systems, alongside smartphones. The touchscreen display is operated by gestures executed by finger or digital pen (stylus), instead of the mouse, touchpad, and keyboard of larger computers. Portable computers can be classified according to the presence and appearance of physical keyboards. Two spec

Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality

Thibault Lucien Christian Asselborn, Mateo Chapatte, Pierre Dillenbourg

This paper proposes new ways to assess handwriting, a critical skill in any child’s school journey. Traditionally, a pen and paper test called the BHK test (Concise Evaluation Scale for Children’s Handwriting) is used to assess children’s handwriting in French-speaking countries. Any child with a BHK score above a certain threshold is diagnosed as ‘dysgraphic’, meaning that they are then eligible for financial coverage for therapeutic support. We previously developed a version of the BHK for tablet computers which provides rich data on the dynamics of writing (acceleration, pressure, and so forth). The underlying model was trained on dysgraphic and non-dysgraphic children. In this contribution, we deviate from the original BHK for three reasons. First, in this instance, we are interested not in a binary output but rather a scale of handwriting difficulties, from the lightest cases to the most severe. Therefore, we wish to compute how far a child’s score is from the average score of children of the same age and gender. Second, our model analyses dynamic features that are not accessible on paper; hence, the BHK is useful in this instance. Using the PCA (Principal Component Analysis) reduced the set of 53 handwriting features to three dimensions that are independent of the BHK. Nonetheless, we double-checked that, when clustering our data set along any of these three axes, we accurately detected dysgraphic children. Third, dysgraphia is an umbrella concept that embraces a broad variety of handwriting difficulties. Two children with the same global score can have totally different types of handwriting difficulties. For instance, one child could apply uneven pen pressure while another one could have trouble controlling their writing speed. Our new test not only provides a global score, but it also includes four specific score for kinematics, pressure, pen tilt and static features (letter shape). Replacing a global score with a more detailed profile enables the selection of remediation games that are very specific to each profile.

2020

Augmented Reality to Facilitate a Conceptual Understanding of Statics in Vocational Education

Lorenzo Lucignano

At the core of the contribution of this dissertation there is an augmented reality (AR) environment, StaticAR, that supports the process of learning the fundamentals of statics in vocational classrooms, particularly in carpentry ones. Vocational apprentices are expected to develop an intuition of these topics rather than a formal comprehension. We have explored the potentials of the AR technology for this pedagogical challenge. Furthermore, we have investigated the role of physical objects in mixed-reality systems when they are implemented as tangible user interfaces (TUIs) or when they serve as a background for the augmentation in handheld AR. This thesis includes four studies. In the first study, we used eye-tracking methods to look for evidences of the benefits associated to TUIs in the learning context. We designed a 3D modelling task and compared users' performance when they completed it using a TUI or a GUI. The gaze measures that we analysed further confirmed the positive impact that TUIs can have on the learners' experience and enforced the empirical basis for their adoption in learning applications. The second study evaluated whether the physical interaction with models of carpentry structures could lead to a better understanding of statics principles. Apprentices engaged in a learning activity in which they could manipulate physical models that were mechanically augmented, allowing for exploring how structures react to external loads. The analysis of apprentices' performance and their gaze behaviors highlighted the absence of clear advantages in exploring statics through manipulation. This study also showed that the manipulation might prevent students from noticing aspects relevant for solving statics problems. From the second study we obtained guidelines to design StaticAR which implements the magic-lens metaphor: a tablet augments a small-scale structure with information about its structural behavior. The structure is only a background for the augmentation and its manipulation does not trigger any function, so in the third study we asked to what extent it was important to have it. We rephrased this question to whether users would look directly at the structure instead of seeing it only through a tablet. Our findings suggested that a shift of attention from the screen to the physical object (a structure in our case) might occur in order to sustain users' spatial orientation when they change positions. In addition, the properties of the gaze shift (e.g. duration) could depend on the features of the task (e.g. difficulty) and of the setup (e.g. stability of the augmentation). The focus of our last study was the digital representation of the forces that act in a loaded structure. From the second study we observed that the physical manipulation failed to help apprentices understanding the way the forces interact with each other. To overcome this issue, our solution was to combine an intuitive representation (springs) with a slightly more formal one (arrows) which would show both the nature of the forces and the interaction between them. In this study apprentices used the two representations to collaboratively solve statics problems. Even though apprentices had difficulties in interpreting the two representations, there were cases in which they gained a correct intuition of statics principles from them. In this thesis, besides describing the designed system and the studies, implications for future directions are discussed.

EPFL2018

When Children Teach a Robot to Write: An Autonomous Teachable Humanoid Which Uses Simulated Handwriting

Pierre Dillenbourg, Deanna Hood, Séverin Lemaignan

This article presents a novel robotic partner which children can teach handwriting. The system relies on the learning by teaching paradigm to build an interaction, so as to stimulate meta-cognition, empathy and increased self-esteem in the child user. We hypothesise that use of a humanoid robot in such a system could not just engage an unmotivated student, but could also present the opportunity for children to experience physically-induced benefits encountered during human-led handwriting interventions, such as motor mimicry. By leveraging simulated handwriting on a synchronised tablet display, a nao humanoid robot with limited fine motor capabilities has been configured as a suitably embodied handwriting partner. Statistical shape models derived from principal component analysis of a dataset of adult-written letter trajectories allow the robot to draw purposefully deformed letters. By incorporating feedback from user demonstrations, the system is then able to learn the optimal parameters for the appropriate shape models. Preliminary in situ studies have been conducted with primary school classes to obtain insight into children’s use of the novel system. Children aged 6-8 successfully engaged with the robot and improved its writing to a level which they were satisfied with. The validation of the interaction represents a significant step towards an innovative use for robotics which addresses a widespread and socially meaningful challenge in education.

2015