Many students persistently misinterpret histograms. This calls for closer inspection of students’ strategies when interpreting histograms and case-value plots (which look similar but are diferent). Using students’ gaze data, we ask: How and how well do upper secondary pre-university school students estimate and compare arithmetic means of histograms and case-value plots? We designed four item types: two requiring mean estimation and two requiring means comparison. Analysis of gaze data of 50 students (15–19 years old) solving these items was triangulated with data from cued recall. We found five strategies. Two hypothesized most common strategies for estimating means were confirmed: a strategy associated with horizontal gazes and a strategy associated with vertical gazes. A third, new, count-and-compute strategy was found. Two more strategies emerged for comparing means that take specific features of the distribution into account. In about half of the histogram tasks, students used correct strategies. Surprisingly, when comparing two case-value plots, some students used distribution features that are only relevant for histograms, such as symmetry. As several incorrect strategies related to how and where the data and the distribution of these data are depicted in histograms, future interventions should aim at supporting students in understanding these concepts in histograms. A methodological advantage of eye-tracking data collection is that it reveals more details about students’ problem-solving processes than thinking-aloud protocols. We speculate that spatial gaze data can be re-used to substantiate ideas about the sensorimotor origin of learning mathematics.
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This paper describes the work that is done by a group of I3 students at Philips CFT in Eindhoven, Netherlands. I3 is an initiative of Fontys University of Professional Education also located in Eindhoven. The work focuses on the use of computer vision in motion control. Experiments are done with several techniques for object recognition and tracking, and with the guidance of a robot movement by means of computer vision. These experiments involve detection of coloured objects, object detection based on specific features, template matching with automatically generated templates, and interaction of a robot with a physical object that is viewed by a camera mounted on the robot.
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The combination of self-tracking and persuasive eCoaching in healthy lifestyle interventions is a promising approach. The objective of this study is to map the key components of existing healthy lifestyle interventions combining self-tracking and persuasive eCoaching using the scoping review methodology in accordance with the York methodological framework by Arksey and O’Malley. Seven studies were included in this preliminary scoping review. Components related to persuasive eCoaching applied only in effective interventions were reduction of complex behavior into small steps, providing positive motivational feedback by praise and providing reliable information to show expertise. Concerning self-tracking, it did not seem to matter if more action was required by the participant to obtain personal data. The first results of this study indicate the necessity to identify the needs and problems of the specific target group of the interventions, due to differences found between various groups of users. In addition to objective data on lifestyle and health behavior, other factors need to be taken into account, such as the context of use, daily experiences, and feelings of the users.
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In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Onze straten zijn in transitie: Verdichting door de bouw van 1 miljoen nieuwe woningen in de bestaande stad; de versnippering van nieuwe vormen van (deel)mobiliteit; vergroening; installaties en objecten voor energietransitie; de introductie van biobased en circulaire materialen; de verschraling van het winkelaanbod; de introductie van heel nieuwe typen woonmilieus. Allemaal werkt door in de straatruimte; de gedeelde publieke ruimte tussen de gebouwen die cruciaal is voor de leefkwaliteit en well-being van inwoners. Het maken van de straatruimte vindt gefragmenteerd en geleidelijk plaats. Met de bouw van 1 miljoen nieuwe woningen de komende tien jaar is de impact echter nauwelijks te overschatten. Gemeentelijke overheden bepalen de kaders en stellen de regels, maar de daadwerkelijke keuzes en uitwerkingen worden door ontwerpbureaus gemaakt. Deze MKB-ers twijfelen of de gangbare opwerpoplossingen inderdaad de well-being versterken. Zij hebben urgente behoefte aan meer evidence based kennis hierover, vernieuwde ontwerpoplossingen en kennisdeling. Met deze mkb-vraag gaat dit onderzoek aan de slag. Dit onderzoeksvoorstel richt zich op de straatruimte op ooghoogte, de nieuwe verdichtingslocaties, drie gebruikersgroepen (bewoners, passanten, bezoekers) en de impact op well-being van de huidige ontwerpoplossingen, mede in relatie tot nieuwe vereisten vanuit personenmobiliteit en vergroening. Hiertoe hebben we een consortium samengesteld van architectuur, stedenbouw, landschapsarchitectuurbureaus, brancheorganisaties en een reflectiegroep van ruimtelijk opdrachtgevers en interdisciplinaire internationale academici. We bouwen voort op ons exploratieve onderzoek Sensing Streetscapes en de daarin geteste nieuwe technologieën (artificial intelligence en eye-tracking-technologie uit de neurologie) en zetten die in om de impact van ontwerpoplossingen op de well-being van gebruikers van de straatruimte te meten – en tussentijdse resultaten in te zetten om een cultuur van reflectie en innovatie in de praktijk van de ruimtelijke ordening aan te jagen.
Over the last couple of years there is a growing interest in the role of the bicycle in Western urban transport systems as an alternative to car use. Cycling not only has positive environmental impacts, but also positive health effects through increased physical activity. From the observation of the Urban Intelligence team that cycling data and information was limited, we have started the development of cycleprint. Cycleprint stands for Cycle Policy Renewal and INnovation by means of tracking Technology with the objective to enable more customer friendly cycle policy.The initial objective of Cycleprint was to translate GPS data into policy relevant insights to enable customer friendly cycle policy. The online toolkit what Cycleprint has become, answers the questions about:-route choice-speeds-delays at intersections -intensities Because of the success of Cycleprint in the Netherlands the range of features is still under development. As a result of the development of Cycleprint the Dutch organized the fietstelweek. In addition to Cycleprint the Urban Intelligence team developed the cyclescan to explore the effects of cycle network enhancement. The project is developed in direct collaboration with the Provincie Noord-Brabant and Metropoolregio Eindhoven to fulfill the ambition to become cycling region of the Netherlands in 2020.
