Vocation, motivation and approaches to learning: a comparative study

Purpose – The individual characteristics of students can have a strong influence on the success of the adopted innovations in terms of their transferability and sustainability. The purpose of this paper is to compare the motivations and approaches to learning on degrees with differing vocational components. Design/methodology/approach – Self-Determination Theory (SDT) and approaches to learning framework were used as theoretical background. Questionnaires were used to generate data. The sample was composed by 270 students enroled on differing degrees in term of motivation (accounting and nursing). Findings – The results reveal differences in the approaches to learning and motivation between nursing and accounting students. Nursing degree seem to attract more internally motivated students, presenting significantly higher scores in terms of deep approach and lower scores on surface approach. Significant relationships where found between motivation and approaches. Research limitations/implications – Data are obtained from students studying at a specific university in two degrees. Practical implications – The result suggest that different degrees could attract students with different motivations and approaches to learning. Educators must be aware of which type of students are being attracted to their classrooms, because the inconsistencies between the students’ motives and approaches, the way the contents are presented, the pedagogy and the assessment system could result in poorer learning and failure to transfer or sustain innovations. Originality/value – This paper adds to the very scarce literature linking motivation and approaches. The implications for curriculum design and delivery and specifically for assessment design are of interest for educators.Junta de Andalucía – FEDER (Proyectos de Excelencia: SEJ-02670

Breakthroughs in Shared Measurement and Social Impact

A surprising new breakthrough is emerging in the social sector: A handful of innovative organizations have developed web-based systems for reporting the performance, measuring the outcomes, and coordinating the efforts of hundreds or even thousands of social enterprises within a field. These nascent efforts carry implications well beyond performance measurement, foreshadowing the possibility of profound changes in the vision and effectiveness of the entire nonprofit sector. This paper, based on six months of interviews and research by FSG Social Impact Advisors, examines twenty efforts to develop shared approaches to performance, outcome, or impact measurement across multiple organizations. The accompanying appendices include a short description of each system and four more in-depth case studies

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs

A Review of Atrial Fibrillation Detection Methods as a Service

Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals

Empowering audiences to measure quality

This paper addresses four indicators of the audience experience in the performing arts: knowledge, risk, authenticity and collective engagement, and argues that these provide a measure of the audience\u27s experience of the quality of a performance. Qualitative interviews with four performing arts companiesdemonstrated a range of strategies for gathering audience feedback. In particular, the paper addresses systems for gathering &quot;deep feedback&quot; by audiences, and argues that these are a means of collecting information about the quality of the audience experience. &quot;Deep feedback&quot; is a critical mechanism by which performing arts organisations can engage in audience development and audiences are empowered to measure quality.<br /

Navigating global-local tensions in accountability/autonomy policies: Comparative case studies in 'Asian' universities

The twin policy domains of accountability and autonomy have featured in recent education reforms in many countries, signalling new relationships between governments and educational institutions. Despite different national and localised contexts, a number of common 'global' trends have been identified. However, simultaneously context-specific differences are also evident. For us, the concept of 'globalisation', when it implies policy homogenisation, is too blunt an instrument to critically analyse these major reforms. We would argue that there are still too few studies on globalisation processes grounded in detailed examinations of particular historical times and geographical spaces. Our research is located within the tensions between global commonalities and localised differences. This paper reports research on changing accountability and autonomy in higher education in three 'Asian' countries. Empirical data has been collected in the People's Republic of China, Hong Kong and Singapore in an attempt to begin to redress a 'Western' hegemony in such research. Within each national context two different types of universities became case study sites for the analysis of both commonalities and differences in accountability and autonomy policies and practices. The current paper focuses in particular on the conceptual and methodological framings of the research and presents some preliminary findings

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version