Student engagement and perceptions of blended-learning of a clinical module in a veterinary degree program.

Blended learning has received much interest in higher education as a way to increase learning efficiency and effectiveness. By combining face-to-face teaching with technology-enhanced learning through online resources, students can manage their own learning. Blended methods are of particular interest in professional degree programs such as veterinary medicine in which students need the flexibility to undertake intra- and extramural activities to develop the range of competencies required to achieve professional qualification. Yet how veterinary students engage with blended learning activities and whether they perceive the approach as beneficial is unclear. We evaluated blended learning through review of student feedback on a 4-week clinical module in a veterinary degree program. The module combined face-to-face sessions with online resources. Feedback was collected by means of a structured online questionnaire at the end of the module and log data collected as part of a routine teaching audit. The features of blended learning that support and detract from students’ learning experience were explored using quantitative and qualitative methods. Students perceived a benefit from aspects of face-to-face teaching and technology-enhanced learning resources. Face-to-face teaching was appreciated for practical activities, whereas online resources were considered effective for facilitating module organization and allowing flexible access to learning materials. The blended approach was particularly appreciated for clinical skills in which students valued a combination of visual resources and practical activities. Although we identified several limitations with online resources that need to be addressed when constructing blended courses, blended learning shows potential to enhance student-led learning in clinical courses

7th Drug hypersensitivity meeting: part two

No abstract availabl

Residential electricity demand: A modelling analysis of the dynamics of household activity and energy consumption patterns

Understanding the diversity of energy requirements and energy-related behaviours in the residential sector is key to assessing the potential of this sector to contribute to the overall flexibility of future low-carbon power systems. Models offer the opportunity to explore the relationships between household activities and the associated electricity demand loads. However, if models are to assist in the research that aims to inform the design of effective interventions, understanding the role users play must be at the core of the modelling efforts. Conventional approaches to residential electricity demand modelling have been developed with a view to inform conventional power systems. The simplifying assumptions that rule these models mask the complexity of the links between user activities and demand for electricity. Therefore, assessing the potential of the implementation of energy efficiency measures targeting the residential sector calls for the development of enhanced modelling approaches. In this thesis the key shortcomings of conventional modelling approaches have been identified. In particular, the analysis has revealed that conventional models consistently fail to represent the diversity of residential users. Thus, the need to re-assess the adequacy of the simplifying assumptions used in the development of conventional modelling approaches has been highlighted. The diversity of residential energy requirements has been further investigated, and novel methods to characterise the socio-demographic heterogeneity of households have been presented. Furthermore, the thesis describes novel approaches that attempt to bridge the gap between energy research through social science lenses and the development of technical modelling tools. The findings of the validation analysis show that these approaches could indeed help improve our understanding of the current role of the residential sector and assess its potential to provide additional system flexibility

The price is not right! Energy demand, Time of Use tariffs, values and social practices

Several governments are opting to move from flat electricity tariffs to Time of Use pricing in an effort to curb peak electricity demand. However, despite the fact that numerous trial studies looking to quantify the effectiveness of pricing schemes have been carried out, these have produced mixed results, and in most cases, the observed temporal shifts in demand in response to the introduction of time-varying pricing are marginal at best. If changes in the timing of energy demand should be of substantial magnitude, marginal behavioural shifts in electricity consumption will not be sufficient. This prompts conceptual efforts to research what constitutes an (in)effective price-driven demand management intervention, and what their implementation may mean for energy demand. Most failures in price-driven interventions have been interpreted by energy economists in terms of setting the wrong price, which for time-varying tariffs translates into inadequate price ratios between peak and off-peak periods. This view is rooted in principles of economic rational choice theories that assume people will always respond to changes in the price of goods or services in a rational, predictable manner. However, this fails to consider the fact that price is only one of many factors at play when it comes to making decisions that will result in demand for energy. This paper suggests that more radical reductions in demand for energy and associated carbon emissions can be achieved through approaches that aim to find a better alignment of time-varying pricing and the (value of) social practices which constitute everyday life. The paper concludes by suggesting ways to integrate concepts explaining ToU pricing effects and the timing of electricity demand with methodologies which disaggregate price elasticity, and offer alternatives to the estimation of market and non-market values of practices and time

Linking intra-day variations in residential electricity demand loads to consumers' activities: What's missing?

An increasing interest in the representation of the intra-day variability observed in domestic electricity consumption patterns has driven the development of various modelling frameworks that incorporate consumer behavioural patterns as a key element for the simulation of electricity consumption. Some of the existing models produce reasonable representations of the broader characteristics of user activity patterns, typically rendered as dwelling occupancy patterns. However, when these activity patterns are used to produce estimates of the electricity demand loads associated with such activities, little attention is paid to the links between activities and the actual use of the electric equipment responsible for the production of the actual demand loads. Instead, the simulation of demand loads from activity patterns is ruled by simplifying assumptions that mask the reality behind those links. This paper therefore seeks to unpack the relationship between activity and electricity demand profiles by focussing on the underlying activity patterns in more detail, and how these relate to the usage patterns of the associated appliances. These relationships are studied based on currently available datasets. The analysis of the activities associated with the use of more than one appliance revealed the differences between the likelihood of each appliance being activated throughout the day relative to user engagement in the activity the appliance is associated with. In practice, what this shows is how each appliance's share of the demand load associated with the activity varies throughout the day. As a result, the power consumption associated with a particular activity is subject to the same kind of variability; activity-related demand. The results of this analysis can be used in conjunction with current or new modelling approaches with a view to linking the user activity patterns with the simulation more of realistic electricity demand loads

From capabilities to capacity: Examining core power capacity requirements in the UK residential sector under the capabilities framework

The ongoing decarbonisation of electricity generation prompts questions around ways to reduce expensive demand peaks and increasing flexibility. Some of those questions are in relation to the development of more cost-effective tariff structures that enable an equitable recovery of costs. Reforming the current tariff structure, however, involves resolving issues around how much should be paid for both variable and fixed components of the bill. As regards to the latter, the concept of core capacity refers to the amount of power capacity that enables consumers to realise basic capabilities and therefore cannot be readily flexed. Setting a capacity core (or cores) links into issues around defining adequate levels of service provision, as well as the timing of energy services and sufficiency under different circumstances. Identifying the set of core capacities across the residential consumer base is key to assessing the potential of this sector to provide additional system flexibility. In this paper, we set out to investigate how the capacity required to meet the demand associated with the attainment of valued capabilities varies across the different segments of the residential consumer population. We explore the diversity of power capacity requirements with a view to identifying the bounds that define the core levels of access to power provision. Our empirical analysis shows that these vary widely across the residential consumer base, ranging from about 2 kW for low-income households, to 7 kW for those largely relying on conventional electric heating systems to maintain adequate levels of thermal comfort during winter