Why don't zombies like hibiscus tea? A multi-subject approach to photosynthesis through the use of Grätzel cells

Traditionally, photosynthesis has been seen as the domain of biology, with some input from chemistry when dealing with chromatography, while, apart from a passing reference to the colour of leaves, physics has tended to steer clear of the process that provides the lifeblood of human existence. This article outlines how a recent technological advance can be used as a teaching resource in all three branches of science

Developing a predictive model for the enhanced learning outcomes by the use of technology

This paper reports on the initial outcomes of a study to develop a model to identify the relationship between technological facilities such as iPad, MacBook, Apps and software etc., pedagogy (that can be defined as any conscious activity by one person designed to enhance learning in another (Watkins and Mortimore, 1999 [1])), curriculum and learning. The new model can be called CPT Model. This is a new area of study. The model will test the difference between the observed learning outcomes and the learning outcomes predicted. This model can predict the outcomes for assessing the students’ progress. Using a three-dimensional vector space in the form of 3D equations, after the integration between the ICT and the education, students’ observed and predicted progress (that was calculated using the CPT model) were compared. These rates were very close to each other. Therefore the null hypothesis, "there is not a significant difference between the observed (actual) and expected outcomes"

A content, pedagogy and technology [CPT] approach to TPACK

TPACK is a framework for the learning process in which educators combine Technological, Pedagogical and Content Knowledge to deliver the learning experience. Therefore, TPACK can be defined as a complex interaction between the technology, pedagogy and content. TPACK expresses the overlap between these factors in a two-dimensional space, placing TPACK at the centre. Educators can place their teaching episode within this space and ask, if I place my delivery at this point is it the best point in the TPACK space? Secondly educators may ask how can the best point within the space be determined? The CPT model proposes an attempt to address these questions by recasting TPACK as a three-dimensional pseudo-vector space allowing expected outcomes and observed outcomes to be analysed. For the study presented here our null hypothesis is: H0 = there is no significant difference between the observed and expected outcomes

A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)

A simple numerical solution procedure – namely the method of lines combined with an off-the-shelf ordinary differential equation (ODE) solver – was shown in previous work to provide efficient, mass-conservative solutions to the pressure-head form of Richards' equation. We implement such a solution in our model openRE. We developed a novel method to quantify the boundary fluxes that reduce water balance errors without negative impacts on model runtimes – the solver flux output method (SFOM). We compare this solution with alternatives, including the classic modified Picard iteration method and the Hydrus 1D model. We reproduce a set of benchmark solutions with all models. We find that Celia's solution has the best water balance, but it can incur significant truncation errors in the simulated boundary fluxes, depending on the time steps used. Our solution has comparable runtimes to Hydrus and better water balance performance (though both models have excellent water balance closure for all the problems we considered). Our solution can be implemented in an interpreted language, such as MATLAB or Python, making use of off-the-shelf ODE solvers. We evaluated alternative SciPy ODE solvers that are available in Python and make practical recommendations about the best way to implement them for Richards' equation. There are two advantages of our approach: (i) the code is concise, making it ideal for teaching purposes; and (ii) the method can be easily extended to represent alternative properties (e.g., novel ways to parameterize the K(ψ) relationship) and processes (e.g., it is straightforward to couple heat or solute transport), making it ideal for testing alternative hypotheses

Using the Sound Card as a Timer

Experiments in mechanics can often be timed by the sounds they produce. In such cases, digital audio recordings provide a simple way of measuring time intervals with an accuracy comparable to that of photogate timers. We illustrate this with an experiment in the physics of sports: to measure the speed of a hard-kicked soccer ball.Comment: 3 pages, 4 figures, Late

Secondary school pupils' preferences for different types of structured grouping practices

The aim of this paper is to explore pupils’ preferences for particular types of grouping practices an area neglected in earlier research focusing on the personal and social outcomes of ability grouping. The sample comprised over 5,000 year 9 pupils (aged 13-14 years) in 45 mixed secondary comprehensive schools in England. The schools represented three levels of ability grouping in the lower school (years 7 to 9). Pupils responded to a questionnaire which explored the types of grouping that they preferred and the reasons for their choices. The majority of pupils preferred setting, although this was mediated by their set placement, type of school, socio-economic status and gender. The key reason given for this preference was that it enabled work to be matched to learning needs. The paper considers whether there are other ways of achieving this avoiding the negative social and personal outcomes of setting for some pupils

Citizens observatories for effective Earth observations: the WeSenseIt approach

The WeSenseIt project defines citizen observatories as “A method, an environment and an infrastructure supporting an information ecosystem for communities and citizens, as well as emergency operators and policymakers, for discussion, monitoring and intervention on situations, places and events” . A collaborative approach has been taken to develop solutions that involve an exchange of information and expertise from all participants and where the focus is on arriving at practical solutions with a clear vision and direction. This has created a shared ownership scheme, and shifts power to the process itself rather than remaining within authorities, developers or decision-makers. The project’s emphasis is on delivering highly innovative technologies to support citizens, communities and authorities in developing a real-time situation awareness while ensuring all stakeholders play their part. Implementation has been through a combination of crowdsourcing, custom applications and dedicated web portals designed to foster collaboration, and which has created a shared knowledge base that facilitates decision-making processes and engages with communities. Data is captured via innovative sensors that are used directly by citizens, crowdsourcing from social networks (or by collective intelligence)

Active 10: Brisk walking to support regular physical activity

We describe a methodology and a technology supporting an intervention carried out by Public Health England (PHE) to encourage physically inactive people (doing less than 30 minutes' physical activity per week) to initiate regular physical activity via 10 minutes of daily brisk walking. The intervention is designed to encourage the inclusion of short bouts of continuous brisk walking in everyday activities such as shopping or commuting. To this extent a behaviour change mobile application, Active 10, was developed and distributed freely for Android and iOS. The app was downloaded over 620,000 times and our server infrastructure has collected nearly a billion data points between March 2017 and January 2019. The paper describes the rationale for Active 10, the application supporting the intervention, the data architecture and the data collection approach. Then we discuss the complexity of developing a health tracking technology with such large number of users, producing a significant volume of data. Finally, we describe a preliminary data analysis, focussing on a cohort of 129,010 users who used the app for over 8 weeks: 73% of these users achieved less than ten minutes of brisk walking per day during the first week; by the end of the 8th week this subset of users showed, on average, a 10-fold increase in brisk walking. The most inactive section of the cohort, the 54% of users who showed virtually no brisk walking activity during week 1, seems to achieve the greatest proportional increase, and by the end of week 8 they appear to meet, on average, 10 minutes of continuous brisk walking per day. The increase is more evident within the 15% of the cohort who kept the app for over six months: on average a 12% increase in average activity was observed in this group with no sign of decline