How teachers think about the role of digital technologies in student assessment in mathematics

This study concerns teachers’ use of digital technologies in student assessment, and how the learning that is developed through the use of technology in mathematics can be evaluated. Nowadays math teachers use digital technologies in their teaching, but not in student assessment. The activities carried out with technology are seen as ‘extra-curricular’ (by both teachers and students), thus students do not learn what they can do in mathematics with digital technologies. I was interested in knowing the reasons teachers do not use digital technology to assess students’ competencies, and what they would need to be able to design innovative and appropriate tasks to assess students’ learning through digital technology. This dissertation is built on two main components: teachers and task design. I analyze teachers’ practices involving digital technologies with Ruthven’s Structuring Features of Classroom Practice, and what relation these practices have to the types of assessment they use. I study the kinds of assessment tasks teachers design with a DGE (Dynamic Geometry Environment), using Laborde’s categorization of DGE tasks. I consider the competencies teachers aim to assess with these tasks, and how their goals relate to the learning outcomes of the curriculum. This study also develops new directions in finding how to design suitable tasks for student mathematical assessment in a DGE, and it is driven by the desire to know what kinds of questions teachers might be more interested in using. I investigate the kinds of technology-based assessment tasks teachers value, and the type of feedback they give to students. Finally, I point out that the curriculum should include a range of mathematical and technological competencies that involve the use of digital technologies in mathematics, and I evaluate the possibility to take advantage of technology feedback to allow students to continue learning while they are taking a test.

Development of quantitative methods for sustainability assessment in process industry

The increasing aversion to technological risks of the society requires the development of inherently safer and environmentally friendlier processes, besides assuring the economic competitiveness of the industrial activities. The different forms of impact (e.g. environmental, economic and societal) are frequently characterized by conflicting reduction strategies and must be holistically taken into account in order to identify the optimal solutions in process design. Though the literature reports an extensive discussion of strategies and specific principles, quantitative assessment tools are required to identify the marginal improvements in alternative design options, to allow the trade-off among contradictory aspects and to prevent the “risk shift”. In the present work a set of integrated quantitative tools for design assessment (i.e. design support system) was developed. The tools were specifically dedicated to the implementation of sustainability and inherent safety in process and plant design activities, with respect to chemical and industrial processes in which substances dangerous for humans and environment are used or stored. The tools were mainly devoted to the application in the stages of “conceptual” and “basic design”, when the project is still open to changes (due to the large number of degrees of freedom) which may comprise of strategies to improve sustainability and inherent safety. The set of developed tools includes different phases of the design activities, all through the lifecycle of a project (inventories, process flow diagrams, preliminary plant lay-out plans). The development of such tools gives a substantial contribution to fill the present gap in the availability of sound supports for implementing safety and sustainability in early phases of process design. The proposed decision support system was based on the development of a set of leading key performance indicators (KPIs), which ensure the assessment of economic, societal and environmental impacts of a process (i.e. sustainability profile). The KPIs were based on impact models (also complex), but are easy and swift in the practical application. Their full evaluation is possible also starting from the limited data available during early process design. Innovative reference criteria were developed to compare and aggregate the KPIs on the basis of the actual sitespecific impact burden and the sustainability policy. Particular attention was devoted to the development of reliable criteria and tools for the assessment of inherent safety in different stages of the project lifecycle. The assessment follows an innovative approach in the analysis of inherent safety, based on both the calculation of the expected consequences of potential accidents and the evaluation of the hazards related to equipment. The methodology overrides several problems present in the previous methods proposed for quantitative inherent safety assessment (use of arbitrary indexes, subjective judgement, build-in assumptions, etc.). A specific procedure was defined for the assessment of the hazards related to the formations of undesired substances in chemical systems undergoing “out of control” conditions. In the assessment of layout plans, “ad hoc” tools were developed to account for the hazard of domino escalations and the safety economics. The effectiveness and value of the tools were demonstrated by the application to a large number of case studies concerning different kinds of design activities (choice of materials, design of the process, of the plant, of the layout) and different types of processes/plants (chemical industry, storage facilities, waste disposal). An experimental survey (analysis of the thermal stability of isomers of nitrobenzaldehyde) provided the input data necessary to demonstrate the method for inherent safety assessment of materials.

New functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb

In case of severe osteoarthritis at the knee causing pain, deformity, and loss of stability and mobility, the clinicians consider that the substitution of these surfaces by means of joint prostheses. The objectives to be pursued by this surgery are: complete pain elimination, restoration of the normal physiological mobility and joint stability, correction of all deformities and, thus, of limping. The knee surgical navigation systems have bee developed in computer-aided surgery in order to improve the surgical final outcome in total knee arthroplasty. These systems provide the surgeon with quantitative and real-time information about each surgical action, like bone cut executions and prosthesis component alignment, by mean of tracking tools rigidly fixed onto the femur and the tibia. Nevertheless, there is still a margin of error due to the incorrect surgical procedures and to the still limited number of kinematic information provided by the current systems. Particularly, patello-femoral joint kinematics is not considered in knee surgical navigation. It is also unclear and, thus, a source of misunderstanding, what the most appropriate methodology is to study the patellar motion. In addition, also the knee ligamentous apparatus is superficially considered in navigated total knee arthroplasty, without taking into account how their physiological behavior is altered by this surgery. The aim of the present research work was to provide new functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb. This was mainly realized by means of the identification and development of new techniques that allow a thorough comprehension of the functioning of the knee joint, with particular attention to the patello-femoral joint and to the main knee soft tissues. A knee surgical navigation system with active markers was used in all research activities presented in this research work. Particularly, preliminary test were performed in order to assess the system accuracy and the robustness of a number of navigation procedures. Four studies were performed in-vivo on patients requiring total knee arthroplasty and randomly implanted by means of traditional and navigated procedures in order to check for the real efficacy of the latter with respect to the former. In order to cope with assessment of patello-femoral joint kinematics in the intact and replaced knees, twenty in-vitro tests were performed by using a prototypal tracking tool also for the patella. In addition to standard anatomical and articular recommendations, original proposals for defining the patellar anatomical-based reference frame and for studying the patello-femoral joint kinematics were reported and used in these tests. These definitions were applied to two further in-vitro tests in which, for the first time, also the implant of patellar component insert was fully navigated. In addition, an original technique to analyze the main knee soft tissues by means of anatomical-based fiber mappings was also reported and used in the same tests. The preliminary instrumental tests revealed a system accuracy within the millimeter and a good inter- and intra-observer repeatability in defining all anatomical reference frames. In in-vivo studies, the general alignments of femoral and tibial prosthesis components and of the lower limb mechanical axis, as measured on radiographs, was more satisfactory, i.e. within ±3°, in those patient in which total knee arthroplasty was performed by navigated procedures. As for in-vitro tests, consistent patello-femoral joint kinematic patterns were observed over specimens throughout the knee flexion arc. Generally, the physiological intact knee patellar motion was not restored after the implant. This restoration was successfully achieved in the two further tests where all component implants, included the patellar insert, were fully navigated, i.e. by means of intra-operative assessment of also patellar component positioning and general tibio-femoral and patello-femoral joint assessment. The tests for assessing the behavior of the main knee ligaments revealed the complexity of the latter and the different functional roles played by the several sub-bundles compounding each ligament. Also in this case, total knee arthroplasty altered the physiological behavior of these knee soft tissues. These results reveal in-vitro the relevance and the feasibility of the applications of new techniques for accurate knee soft tissues monitoring, patellar tracking assessment and navigated patellar resurfacing intra-operatively in the contest of the most modern operative techniques. This present research work gives a contribution to the much controversial knowledge on the normal and replaced of knee kinematics by testing the reported new methodologies. The consistence of these results provides fundamental information for the comprehension and improvements of knee orthopedic treatments. In the future, the reported new techniques can be safely applied in-vivo and also adopted in other joint replacements.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.