Problem-based learning approaches in meteorology

Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a current field course module, this project describes the implementation of two test Problem-Based Learning activities and testing and improvement using several different and complementary means of evaluation. By the end of a 2-year program of design, implementation, testing, and reflection and re-evaluation, two robust, engaging activities have been developed that provide an enhanced and diverse learning environment in the field course. The results suggest that Problem-Based Learning techniques would be a useful addition to the meteorology curriculum and suggestions for courses and activities that may benefit from this approach are included in the conclusions.

Urban retrofitting: identifying disruptive and sustaining technologies using performative and foresight techniques

Cities, which are now inhabited by a majority of the world's population, are not only an important source of global environmental and resource depletion problems, but can also act as important centres of technological innovation and social learning in the continuing quest for a low carbon future. Planning and managing large-scale transitions in cities to deal with these pressures require an understanding of urban retrofitting at city scale. In this context performative techniques (such as backcasting and roadmapping) can provide valuable tools for helping cities develop a strategic view of the future. However, it is also important to identify ‘disruptive’ and ‘sustaining’ technologies which may contribute to city-based sustainability transitions. This paper presents research findings from the EPSRC Retrofit 2050 project, and explores the relationship between technology roadmaps and transition theory literature, highlighting the research gaps at urban/city level. The paper develops a research methodology to describe the development of three guiding visions for city-regional retrofit futures, and identifies key sustaining and disruptive technologies at city scale within these visions using foresight (horizon scanning) techniques. The implications of the research for city-based transition studies and related methodologies are discussed.

A comparison of GOCE and drifter-based estimates of the North Atlantic steady-state surface circulation

Over the last decade, due to the Gravity Recovery And Climate Experiment (GRACE) mission and, more recently, the Gravity and steady state Ocean Circulation Explorer (GOCE) mission, our ability to measure the ocean’s mean dynamic topography (MDT) from space has improved dramatically. Here we use GOCE to measure surface current speeds in the North Atlantic and compare our results with a range of independent estimates that use drifter data to improve small scales. We find that, with filtering, GOCE can recover 70% of the Gulf Steam strength relative to the best drifter-based estimates. In the subpolar gyre the boundary currents obtained from GOCE are close to the drifter-based estimates. Crucial to this result is careful filtering which is required to remove small-scale errors, or noise, in the computed surface. We show that our heuristic noise metric, used to determine the degree of filtering, compares well with the quadratic sum of mean sea surface and formal geoid errors obtained from the error variance–covariance matrix associated with the GOCE gravity model. At a resolution of 100 km the North Atlantic mean GOCE MDT error before filtering is 5 cm with almost all of this coming from the GOCE gravity model.

Enterprise Architecture adoption method for Higher Education Institutions

During the last few years Enterprise Architecture has received increasing attention among industry and academia. Enterprise Architecture (EA) can be defined as (i) a formal description of the current and future state(s) of an organisation, and (ii) a managed change between these states to meet organisation’s stakeholders’ goals and to create value to the organisation. By adopting EA, organisations may gain a number of benefits such as better decision making, increased revenues and cost reductions, and alignment of business and IT. To increase the performance of public sector operations, and to improve public services and their availability, the Finnish Parliament has ratified the Act on Information Management Governance in Public Administration in 2011. The Act mandates public sector organisations to start adopting EA by 2014, including Higher Education Institutions (HEIs). Despite the benefits of EA and the Act, EA adoption level and maturity in Finnish HEIs are low. This is partly caused by the fact that EA adoption has been found to be difficult. Thus there is a need for a solution to help organisations to adopt EA successfully. This thesis follows Design Science (DS) approach to improve traditional EA adoption method in order to increase the likelihood of successful adoption. First a model is developed to explain the change resistance during EA adoption. To find out problems associated with EA adoption, an EA-pilot conducted in 2010 among 12 Finnish HEIs was analysed using the model. It was found that most of the problems were caused by misunderstood EA concepts, attitudes, and lack of skills. The traditional EA adoption method does not pay attention to these. To overcome the limitations of the traditional EA adoption method, an improved EA Adoption Method (EAAM) is introduced. By following EAAM, organisations may increase the likelihood of successful EA adoption. EAAM helps in acquiring the mandate for EA adoption from top-management, which has been found to be crucial to success. It also helps in supporting individual and organisational learning, which has also found to be essential in successful adoption.

Care, disability and HIV in Africa: diverging or interconnected concepts and practices?

Recent research and policy have recognised the central role of unpaid care-givers (often women and girls) in the global South. Disability rights perspectives, however, challenge the language of ‘care’ and ‘dependence’. Drawing on qualitative research with women living with HIV and children caring for them in Tanzania, and on learning from the National Community of Women Living with HIV and AIDS in Uganda (NACWOLA), this paper explores the divergences and interconnections between the concepts and practices of care, disability and HIV in the context of East Africa. Despite the development of interdependent caring relations, both care-givers and people living with HIV in Tanzania experience ‘diminished autonomy’. The participation of people living with HIV, including disabled people, in home-based care and in peer support groups, however, can enhance ‘relational autonomy’ for both care-givers and care-recipients. We reflect on opportunities and challenges for mutual learning and cross-movement advocacy by disabled people, people living with HIV and care-givers.

How students view the boundaries between their science and religious education concerning the origins of life and the universe

Internationally in secondary schools, lessons are typically taught by subject specialists, raising the question of how to accommodate teaching which bridges the sciences and humanities. This is the first study to look at how students make sense of the teaching they receive in two subjects (science and religious education) when one subject’s curriculum explicitly refers to cross-disciplinary study and the other does not. Interviews with 61 students in seven schools in England suggested that students perceive a permeable boundary between science and their learning in science lessons and also a permeable boundary between religion and their learning in RE lessons, yet perceive a firm boundary between science lessons and RE lessons. We concluded that it is unreasonable to expect students to transfer instruction about cross-disciplinary perspectives across such impermeable subject boundaries. Finally we consider the implications of these findings for the successful management of cross-disciplinary education.

Individual differences in early language learning: a study of English learners of French

The present longitudinal study examines the interaction of learner variables (gender, motivation, self-efficacy and first language literacy) and their influence on second language learning outcomes. The study follows English learners of French from Year 5 in primary school (aged 9-10) to the first year in secondary school (Year 7 aged 11-12). Language outcomes were measured by two oral production tasks; a sentence repetition task and a photo description task both of which were administered at three time points. Longitudinal data on learner attitudes and motivation were collected via questionnaires. Teacher assessment data for general first language literacy attainment were also provided. The results show a great deal of variation in learner attitudes and outcomes and that there is a complex relationship between first language literacy, self-efficacy, gender and attainment. For example, in general, girls held more positive attitudes to boys and were more successful. However, the inclusion of first language ability, which explained 30-40% of variation, shows that gender differences in attitudes and outcomes are likely mediated by first language literacy and prior learning experience.

Rapid evolution of the cerebellum in humans and other great apes

Humans’ unique cognitive abilities are usually attributed to a greatly expanded neocortex, which has been described as “the crowning achievement of evolution and the biological substrate of human mental prowess” [1]. The human cerebellum, however, contains four times more neurons than the neocortex [2] and is attracting increasing attention for its wide range of cognitive functions. Using a method for detecting evolutionary rate changes along the branches of phylogenetic trees, we show that the cerebellum underwent rapid size increase throughout the evolution of apes, including humans, expanding significantly faster than predicted by the change in neocortex size. As a result, humans and other apes deviated significantly from the general evolutionary trend for neocortex and cerebellum to change in tandem, having significantly larger cerebella relative to neocortex size than other anthropoid primates. These results suggest that cerebellar specialization was a far more important component of human brain evolution than hitherto recognized and that technical intelligence was likely to have been at least as important as social intelligence in human cognitive evolution. Given the role of the cerebellum in sensory-motor control and in learning complex action sequences, cerebellar specialization is likely to have underpinned the evolution of humans’ advanced technological capacities, which in turn may have been a preadaptation for language.

Terminology matters! Why difference is not incompleteness and how early child bilinguals are heritage speakers

This paper integrates research on child simultaneous bilingual (2L1) acquisition more directly into the heritage language (HL) acquisition literature. The 2L1 literature mostly focuses on development in childhood, whereas heritage speakers (HSs) are often tested at an endstate in adulthood. However, insights from child 2L1 acquisition must be considered in HL acquisition theorizing precisely because many HSs are the adult outcomes of child 2L1 acquisition. Data from 2L1 acquisition raises serious questions for the construct of incomplete acquisition, a term broadly used in HL acquisition studies to describe almost any difference HSs display from baseline controls (usually monolinguals). We offer an epistemological discussion related to incomplete acquisition, highlighting the descriptive and theoretical inaccuracy of the term. We focus our discussion on two of several possible causal factors that contribute to variable competence outcomes in adult HSs, input (e.g., Sorace, 2004; Rothman, 2007; Pascual y Cabo & Rothman, 2012) and formal instruction (e.g., Kupisch, 2013; Kupisch et al., 2014) in the HL. We conclude by offering alternative terminology for HS outcomes.

Reducing defects through organizational learning within a Housing Association environment

Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.