A (digital) finger on the pulse

Complex Event Processing (CEP) is a computer-based technique used to track, analyse and process data in real-time (as an event happens). It establishes correlations between streams of information and matches to defined behaviour

Support dementia: using wearable assistive technology and analysing real-time data

Within healthcare, Complex Event Processing (CEP) engines can analyse events and related data which come from various sources (wearable sensors, environment sensors etc.) in real-time and provide insights for a better healthcare. A major strength of CEP is the automated matching of patterns and triggering of immediate actions. Dementia is becoming increasingly common in the elderly population. Currently, care provided by the NHS is in the form of personal attendants such as nurses and social workers. Reducing the amount of personal care devoted to early Dementia sufferers by means of remotely monitoring their condition will reduce the pressure on NHS resources and will promote good quality independent living. The use of sensory devices to monitor the activities of daily living of early Dementia suffers, and then analyse the sensory output to identify deviations from normal behavioural patterns can indicate deterioration in the Dementia condition such as restlessness and wandering, and subsequently seek intervention from the caregivers or the health clinicians. Controlling healthcare demand through prevention or delay is essential and technologies together with data analytics will play an increasing role. The main focus of this paper is to provide a broad overview of how people with special needs such as dementia patients, will benefit from assisted technologies to overcome barriers in achieving their daily activities and to present how CEP engines for real-time analytics can support this. This work will feed into fulfilling research work which is to provide a suitable framework to accurately analyse real-time data from assistive technology and wearable devices for remote healthcare, particularly dementia

Support dementia: using wearable assistive technology and analysing real-time data

Support provided to sufferers of Dementia by the National Health Service (NHS) is mainly in the form of personal attendants such as nurses and social workers. The main focus of this paper is to present how the use of assistive technologies can help early sufferers of Dementia patients to overcome barriers in achieving their daily activities and to illustrate how data analytics, such as Complex Event Processing (CEP) in real-time can allow better monitoring of these patients. This activity will contribute to research work which is to provide a suitable framework to accurately analyse real-time data from assistive technology and wearable devices for remote healthcare, particularly monitoring early sufferers of dementia in order to promote good quality independent living

A study to evaluate students’ performance, engagement, and progression in higher education based on feedforward teaching approach

Learners who enter higher education (HE) at foundation entry level are susceptible to many chal-lenges that have an impact on their performance, engagement, and progression. Not all students who enter HE at foundation level will progress and attain their course qualification. In addition to this, many university lecturers are struggling to give the effective support to their students. The study in this paper focuses on feedforward teaching approaches which defines ways to enhance learning by using advanced organised strategies to offer relevant supporting concepts and mean-ingful verbal material. To date there are insufficient literature reviews on the feedforward ap-proaches to facilitate students' subsequent learning. To provide better academic support for students and a strong foundation to become independent in their study is something this paper focuses on. Therefore, the main contribution of this paper is the: identification of the key feedforward features and suggestion of effective feedforward approaches. A study was undertaken to rigorously im-plement feedforward approaches that would support groups of students on modules at foundation entry level. At the end of module delivery, different students’ data sets were analysed related to the progression rates, standard deviation, and mean. In addition, the students’ satisfaction question-naire (module evaluation survey) and their feedback survey were also considered for engagement, and retention purposes. The outcomes from this exercise suggested that feedforward approaches allowed students to increase their overall effort at attempting the summative assessment and thus, improving their performance, engagement, and retention

Application of Complex Event Processing techniques to Big Data related to healthcare: a systematic literature review of case studies

Healthcare is a growth area for event processing applications. Computers and information systems have been used for collecting patient data in health care for over fifty years. However, progress towards a unified health care delivery system in the UK has been slow. Big Data, the Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with treatment areas of healthcare domain but also to redefine healthcare services. This study is intended to provide a broad overview of where in the health sector, the application of CEP is most used, the data sources that contribute to it and the types of event processing languages and techniques implemented. By systematic review of existing literature on the application of CEP techniques in Healthcare, a number of use cases have been identified to provide a detailed analysis of the most common used case(s), common data sources in use and highlight CEP query language types and techniques that have been considered

Learning through the pandemic: first year students’ perceptions

The outbreak of COVID-19 pandemic and the resultant access restrictions to university site have led to a significant change in the students’ learning experiences. The new Level 3 entrants starting their undergraduate degrees with a foundation year had a first-hand experience of online learning at the onset of their educational experience in lieu of the face-to face learning. The students at the School of Computing & Engineering at University of West London were introduced to the ‘UWL Flex’ as an online learning platform. This study aimed to quantify student perceptions and experiences for those new entrants on the Built Environment and Computing courses. An anonymous survey was administered to all students towards the end of the modules. Some open-ended responses were sought from the students and their perceptions on online delivery mode of study were recorded. Students were encouraged to comment on digital competence, socioeconomic circumstances, access to technological tools, one to one tutorial support and prior knowledge. The findings showed that the overall strengths of online learning outweighed the limitations

Use of “Feed-Forward” to improve students’ engagement and achievement

The presentation reports the findings of an evaluative research that attempts to assess the effectiveness of feed-forward within assessment intervention. The study focus on the improvement in the overall quality of students’ attempt at summative assessment and students’ engagement in their modules