Stargazing Live! aims to capture the imagination of learners with a combination of live and interactive planetarium lessons, real astronomical data, and lessons built around interactive knowledge representations. The lessons were created using a co-creation model and tackle concepts in the pre-university (astro)physics which students find difficult to grasp with traditional interventions. An evaluation study in 9 Dutch classrooms showed that learners are inspired and engaged by the planetarium lessons but are not always able to link the content to the classroom. Pre- and post-tests showed that the accompanying star properties activity significantly increased learners’ understanding of the causal relationships between mass and other properties (such as luminosity, gravity, and temperature) in a main sequence star.
Many students in secondary schools consider the sciences difficult and unattractive. This applies to physics in particular, a subject in which students attempt to learn and understand numerous theoretical concepts, often without much success. A case in point is the understanding of the concepts current, voltage and resistance in simple electric circuits. In response to these problems, reform initiatives in education strive for a change of the classroom culture, putting emphasis on more authentic contexts and student activities containing elements of inquiry. The challenge then becomes choosing and combining these elements in such a manner that they foster an understanding of theoretical concepts. In this article we reflect on data collected and analyzed from a series of 12 grade 9 physics lessons on simple electric circuits. Drawing from a theoretical framework based on individual (conceptual change based) and socio-cultural views on learning, instruction was designed addressing known conceptual problems and attempting to create a physics (research) culture in the classroom. As the success of the lessons was limited, the focus of the study became to understand which inherent characteristics of inquiry based instruction complicate the process of constructing conceptual understanding. From the analysis of the data collected during the enactment of the lessons three tensions emerged: the tension between open inquiry and student guidance, the tension between students developing their own ideas and getting to know accepted scientific theories, and the tension between fostering scientific interest as part of a scientific research culture and the task oriented school culture. An outlook will be given on the implications for science lessons.
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In 1996 innovative, double major teacher education programs for Physics & Mathematics and Physics & Chemistry were initiated at the University of San Carlos in Cebu, Philippines. Both programs require 4 years of study. From the outset the focus was on making a difference in the quality of Science and Mathematics Teacher Education, producing teachers with a good mastery of subject matter and able to teach the subjects in exciting and effective ways in typical Philippine crowded and resource-poor classrooms. The programs recruit top high school graduates using a promotion and scholarship scheme and then expose them to the best science lecturers at the university, and create a special learning environment for the duration of their training. Early 2011 a study was conducted to assess long term effects of the programs through a tracer study of the 300 alumni, interviews, and 22classroom visits to observe their teaching. Of the 300 alumni 245 are still teaching of whom 33 abroad (mainly USA) and 212 in the Philippines. Alumni are highly valued by principals of the top schools in Cebu and their students win many local and even national science competitions. Their teaching is competent with lots of interaction and good subject matter mastery, but they are also facing some typical Philippine education problems.
MULTIFILE
Road freight transport contributes to 75% of the global logistics CO2 emissions. Various European initiatives are calling for a drastic cut-down of CO2 emissions in this sector [1]. This requires advanced and very expensive technological innovations; i.e. re-design of vehicle units, hybridization of powertrains and autonomous vehicle technology. One particular innovation that aims to solve this problem is multi-articulated vehicles (road-trains). They have a smaller footprint and better efficiency of transport than traditional transport vehicles like trucks. In line with the missions for Energy Transition and Sustainability [2], road-trains can have zero-emission powertrains leading to clean and sustainable urban mobility of people and goods. However, multiple articulations in a vehicle pose a problem of reversing the vehicle. Since it is extremely difficult to predict the sideways movement of the vehicle combination while reversing, no driver can master this process. This is also the problem faced by the drivers of TRENS Solar Train’s vehicle, which is a multi-articulated modular electric road vehicle. It can be used for transporting cargo as well as passengers in tight environments, making it suitable for operation in urban areas. This project aims to develop a reverse assist system to help drivers reverse multi-articulated vehicles like the TRENS Solar Train, enabling them to maneuver backward when the need arises in its operations, safely and predictably. This will subsequently provide multi-articulated vehicle users with a sustainable and economically viable option for the transport of cargo and passengers with unrestricted maneuverability resulting in better application and adding to the innovation in sustainable road transport.
Granular materials (GMs) are simply a collection of individual particles, e.g., rice, coffee, iron-ore. Although straightforward in appearance, GMs are key to several processes in chemical-pharmaceutical, high-tech, agri-food and energy industry. Examples include laser sintering in additive manufacturing, tableting in pharma or just mixing of your favourite crunchy muesli mix in food industry. However, these bulk material handling processes are notorious for their inefficiency and ineffectiveness. Thereby, affecting the overall expenses and product quality. To understand and enhance the quality of a process, GMs industries utilise computer-simulations, much like how cars and aeroplanes have been designed and optimised since the 1990s. Just as how engineers utilise advanced computer-models to develop our fuel-efficient vehicle design, energy-saving granular processes are also developed utilising physics-based simulation-models, using a computer. Although physics-based models can effectively optimise large-scale processes, creating and simulating a fully representative virtual prototype of a GMs process is very iterative, computationally expensive and time intensive. On the contrary, given the available data, this is where machine learning (ML) could be of immense value. Like how ML has transformed the healthcare, energy and other top sectors, recent ML-based developments for GMs show serious promise in faster virtual prototyping and reduced computational cost. Enabling industries to rapidly design and optimise, enhancing real-time data-driven decision making. GranML aims to empower the GMs industries with ML. We will do so by (i) performing an in-depth GMs-ML literature review, (ii) developing open-access ML implementation guidelines; and (iii) an open-source proof-of-concept for an industry-relevant use case. Eventually, our follow-up mission is to build upon this vital knowledge by (i) expanding the consortium; (ii) co-developing a unified methodology for efficient computer-prototyping, unifying physics- and ML-based technologies for GMs; (iii) enhancing the existing computer-modelling infrastructure; and (iv) validating through industry focused demonstrators.
Sensoren gebaseerd op nanotechnologie worden beschouwd als een technologie die sterk kan bijdragen aan de kwaliteit van de gezondheidszorg en aan het verminderen van de zorgkosten. Door hun extreme gevoeligheid zijn dit type sensoren in staat om met kleine monstervolumes in korte tijd een nauwkeurige diagnose te kunnen stellen op basis van bijvoorbeeld bloed-, speeksel-, adem- of urinemonsters. Concreet betekent dit dat met dit type sensoren eenvoudige analyses mogelijk zijn, waardoor er extra mogelijkheden naast bestaande, vaak uitgebreide, analyselaboratoria ontstaan. Hoewel er een divers aantal sensorprincipes beschikbaar is, zijn er tot op heden nog nauwelijks praktische toepassingen gerealiseerd. De reden is dat er nog een aantal technische stappen te zetten zijn om van een laboratorium-prototype sensor tot een compleet analyse-apparaat te komen. Binnen het huidige project willen de consortiumpartners deze ontwikkeling uitvoeren voor een optische nanosensor, waarbij wordt voortgebouwd op de kennis en ervaring die binnen het lectoraat NanoPhysics Interface is opgedaan in de afgelopen twee jaren. Specifiek zal worden gekeken naar twee belangrijke aspecten: het aanbrengen van de gevoelige laag en de elektronische interface. Belangrijke aspecten hierbij zijn dat de gevoelige laag (die een interactie heeft met de op te sporen stoffen) lokaal op de juiste plek op de sensor wordt aangebracht en een goede hechting vertoont. Voor sommige toepassingen kan het tevens nodig zijn dat er verschillende gevoelige lagen op een chip (met meerdere sensoren) gecombineerd kunnen worden. Voor de uitlees-elektronica zal met name gekeken worden naar de optische aansluiting op de chip (die eenvoudig te vervangen moet zijn), naar mogelijkheden tot miniaturisatie (om de meting zo flexibel mogelijk te kunnen inzetten) en naar de eisen aan de gebruikersinterface (afhankelijk van de toepassing en de doelgroep). Uiteindelijk is het de bedoeling dat het geheel samengevoegd wordt in een demonstrator-opstelling. Vanwege de huidige kennis binnen het lectoraat op het gebied van metingen aan het menselijk metabolisme via biomarkers op de huid, is ervoor gekozen om deze toepassing voor de demonstrator te gebruiken.