A Qualitative Exploration of Perceived Key Knowledge and Skills in End-of-Life Care in Dementia Patients among Medical, Nursing, and Pharmacy Students

Background: The steady increase in the number of people living and dying with dementia, coupled with the recent focus on quality of care, has highlighted the importance of dementia training for health care professionals. This exploratory study aimed to discover which skills health care students felt were important in providing quality end-of-life care to dementia patients.

Methods: Ninety-four medicine, nursing, and pharmacy students participated in a larger study using open-ended and closed questions to explore attitudes related to caring for dementia patients at the end of life. This study looks at the student responses to an open-ended question regarding the skills and knowledge they believe are needed to provide end-of-life care to dementia patients. Individual responses were reviewed by the researchers, coded into key issues, and tabulated for frequency of occurrences and group differences.

Results: Several common issues emerged: knowledge, patience, empathy, understanding, family involvement, compassion, medication knowledge, respect/patient autonomy, communication, quality of life, and patient education. Significant differences were observed among the participant groups on the following issues: Patience and understanding (pharmacy students mentioned these issues less frequently than medical and nursing students), compassion (medical students mentioned this issue more frequently than pharmacy students), and medication knowledge (pharmacy students mentioned this issue more frequently than medical and nursing students).

Conclusions: Different health care disciplines (in-training) value different skill sets for the provision of dementia care at the end-of-life. As health care education for dementia patients at the end of life is expanded, it will be important to understand which skills both patients and health care students value.

Measuring critical thinking skills and dispositions in undergraduate students

This thesis investigates critical thinking with a particular focus on measurement in undergraduate students. A higher education context was chosen because many regard critical thinking development as a primary goal for third level education. Nine studies, both cross-sectional and longitudinal in design, were conducted with undergraduate psychology students (N=387), using the California Critical Thinking Disposition Inventory (CCTDI) and the California Critical Thinking Skills Test (CCTST). Studies 1-3 revealed psychometric weaknesses in the CCTDI and revised the scale with factor analysis and reliability analysis to form the CCTDI United Kingdom revision (CCTDI-UK). Study 4 investigated convergent validity and showed significant inter-correlation between the sub-scales of the CCTDI-UK, and significant correlations with the Openness scale of the NEO Personality Inventory (NEO PI-R). The study also provided evidence for improvement in scores on three of the six sub-scales in the CCTDI-UK (Truth-Seeking, Inquisitiveness, Open-Mindedness) during the course of an undergraduate degree. Study 5 explored a two factor structure for critical thinking dispositions. Study 6 used reliability analysis to revise the CCTST to produce the CCTST-UK. Study 7 showed that the CCTST-UK had a moderate correlation with degree attainment and a slightly higher correlation with a test of non-verbal intelligence (Raven’s Advanced Progressive Matrices short form); in addition, the study showed that scores on the CCTST-UK improved during the course of the degree. Studies 8 and 9 investigated the potential of critical thinking for predicting degree attainment. A-levels predicted approximately 10% of the variance of degree attainment while entry level scores on the CCTST-UK predicted an additional 5%. Exit level scores on the CCTST-UK and the Inquisitive sub-scale of the CCTDI-UK were found to be predictors of degree attainment The main conclusions of the thesis were that these tests had significant potential for predicting degree attainment and that they measured a substantial proportion of the theoretical constructs identified by the major authors in critical thinking.

How Video Lecture Capture affects Student Engagement in a University Computer Programming Course: Attendance, Video Viewing Behaviours and Student Attitudes

Introduction
The use of video capture of lectures in Higher Education is not a recent occurrence with web based learning technologies including digital recording of live lectures becoming increasing commonly offered by universities throughout the world (Holliman and Scanlon, 2004). However in the past decade the increase in technical infrastructural provision including the availability of high speed broadband has increased the potential and use of videoed lecture capture. This had led to a variety of lecture capture formats including pod casting, live streaming or delayed broadcasting of whole or part of lectures.
Additionally in the past five years there has been a significant increase in the popularity of online learning, specifically via Massive Open Online Courses (MOOCs) (Vardi, 2014). One of the key aspects of MOOCs is the simulated recording of lecture like activities. There has been and continues to be much debate on the consequences of the popularity of MOOCs, especially in relation to its potential uses within established University programmes.
There have been a number of studies dedicated to the effects of videoing lectures.
The clustered areas of research in video lecture capture have the following main themes:
• Staff perceptions including attendance, performance of students and staff workload
• Reinforcement versus replacement of lectures
• Improved flexibility of learning
• Facilitating engaging and effective learning experiences
• Student usage, perception and satisfaction
• Facilitating students learning at their own pace
Most of the body of the research has concentrated on student and faculty perceptions, including academic achievement, student attendance and engagement (Johnston et al, 2012).
Generally the research has been positive in review of the benefits of lecture capture for both students and faculty. This perception coupled with technical infrastructure improvements and student demand may well mean that the use of video lecture capture will continue to increase in frequency in the next number of years in tertiary education. However there is a relatively limited amount of research in the effects of lecture capture specifically in the area of computer programming with Watkins 2007 being one of few studies . Video delivery of programming solutions is particularly useful for enabling a lecturer to illustrate the complex decision making processes and iterative nature of the actual code development process (Watkins et al 2007). As such research in this area would appear to be particularly appropriate to help inform debate and future decisions made by policy makers.
Research questions and objectives
The purpose of the research was to investigate how a series of lecture captures (in which the audio of lectures and video of on-screen projected content were recorded) impacted on the delivery and learning of a programme of study in an MSc Software Development course in Queen’s University, Belfast, Northern Ireland. The MSc is conversion programme, intended to take graduates from non-computing primary degrees and upskill them in this area. The research specifically targeted the Java programming module within the course. It also analyses and reports on the empirical data from attendances and various video viewing statistics. In addition, qualitative data was collected from staff and student feedback to help contextualise the quantitative results.
Methodology, Methods and Research Instruments Used
The study was conducted with a cohort of 85 post graduate students taking a compulsory module in Java programming in the first semester of a one year MSc in Software Development. A pre-course survey of students found that 58% preferred to have available videos of “key moments” of lectures rather than whole lectures. A large scale study carried out by Guo concluded that “shorter videos are much more engaging” (Guo 2013). Of concern was the potential for low audience retention for videos of whole lectures.
The lecturers recorded snippets of the lecture directly before or after the actual physical delivery of the lecture, in a quiet environment and then upload the video directly to a closed YouTube channel. These snippets generally concentrated on significant parts of the theory followed by theory related coding demonstration activities and were faithful in replication of the face to face lecture. Generally each lecture was supported by two to three videos of durations ranging from 20 – 30 minutes.
Attendance
The MSc programme has several attendance based modules of which Java Programming was one element. In order to assess the consequence on attendance for the Programming module a control was established. The control used was a Database module which is taken by the same students and runs in the same semester.
Access engagement
The videos were hosted on a closed YouTube channel made available only to the students in the class. The channel had enabled analytics which reported on the following areas for all and for each individual video; views (hits), audience retention, viewing devices / operating systems used and minutes watched.
Student attitudes
Three surveys were taken in regard to investigating student attitudes towards the videoing of lectures. The first was before the start of the programming module, then at the mid-point and subsequently after the programme was complete.
The questions in the first survey were targeted at eliciting student attitudes towards lecture capture before they had experienced it in the programme. The midpoint survey gathered data in relation to how the students were individually using the system up to that point. This included feedback on how many videos an individual had watched, viewing duration, primary reasons for watching and the result on attendance, in addition to probing for comments or suggestions. The final survey on course completion contained questions similar to the midpoint survey but in summative view of the whole video programme.
Conclusions and Outcomes
The study confirmed findings of other such investigations illustrating that there is little or no effect on attendance at lectures. The use of the videos appears to help promote continual learning but they are particularly accessed by students at assessment periods. Students respond positively to the ability to access lectures digitally, as a means of reinforcing learning experiences rather than replacing them. Feedback from students was overwhelmingly positive indicating that the videos benefited their learning. Also there are significant benefits to part recording of lectures rather than recording whole lectures. The behaviour viewing trends analytics suggest that despite the increase in the popularity of online learning via MOOCs and the promotion of video learning on mobile devices in fact in this study the vast majority of students accessed the online videos at home on laptops or desktops However, in part, this is likely due to the nature of the taught subject, that being programming.
The research involved prerecording the lecture in smaller timed units and then uploading for distribution to counteract existing quality issues with recording entire live lectures. However the advancement and consequential improvement in quality of in situ lecture capture equipment may well help negate the need to record elsewhere. The research has also highlighted an area of potentially very significant use for performance analysis and improvement that could have major implications for the quality of teaching. A study of the analytics of the viewings of the videos could well provide a quick response formative feedback mechanism for the lecturer. If a videoed lecture either recorded live or later is a true reflection of the face to face lecture an analysis of the viewing patterns for the video may well reveal trends that correspond with the live delivery.

Domestic Cooking and Food Skills: A Review

Domestic cooking skills (CS) and food skills (FS) encompass multiple components, yet there is a lack of consensus on their constituent parts, inter-relatedness or measurement, leading to limited empirical support for their role in influencing dietary quality. This review assessed the measurement of CS and FS in adults (>16 years); critically examining study designs, psychometric properties of measures, theoretical basis and associations of CS/FS with diet. Electronic databases (PsychInfo), published reports and systematic reviews on cooking and home food preparation interventions (Rees et al. 2012 ; Reicks et al. 2014 ) provided 834 articles of which 26 met the inclusion criteria. Multiple CS/FS measures were identified across three study designs: qualitative; cross-sectional; and dietary interventions; conducted from 1998-2013. Most measures were not theory-based, limited psychometric data was available, with little consistency of items or scales used for CS/FS measurements. Some positive associations between CS/FS and FV intake were reported; though lasting dietary changes were uncommon. The role of psycho-social (e.g., gender, attitudes) and external factors (e.g. food availability) on CS/FS is discussed. A conceptual framework of CS/FS components is presented for future measurement facilitation, which highlights the role for CS/FS on food-related behaviour and dietary quality. This will aid future dietary intervention design.

Strange, But True? Object-oriented Programming Is Best Taught, And Learnt, While Sitting On The Floor.

There is a perception amongst some of those learning computer programming that the principles of object-oriented programming (where behaviour is often encapsulated across multiple class files) can be difficult to grasp, especially when taught through a traditional, didactic ‘talk-and-chalk’ method or in a lecture-based environment.
We propose a non-traditional teaching method, developed for a government funded teaching training project delivered by Queen’s University, we call it bigCode. In this scenario, learners are provided with many printed, poster-sized fragments of code (in this case either Java or C#). The learners sit on the floor in groups and assemble these fragments into the many classes which make-up an object-oriented program.
Early trials indicate that bigCode is an effective method for teaching object-orientation. The requirement to physically organise the code fragments imitates closely the thought processes of a good software developer when developing object-oriented code.
Furthermore, in addition to teaching the principles involved in object-orientation, bigCode is also an extremely useful technique for teaching learners the organisation and structure of individual classes in Java or C# (as well as the organisation of procedural code). The mechanics of organising fragments of code into complete, correct computer programs give the users first-hand practice of this important skill, and as a result they subsequently find it much easier to develop well-structured code on a computer.
Yet, open questions remain. Is bigCode successful only because we have unknowingly predominantly targeted kinesthetic learners? Is bigCode also an effective teaching approach for other forms of learners, such as visual learners? How scalable is bigCode: in its current form can it be used with large class sizes, or outside the classroom?

Using Answer Set Programming for Solving Boolean Games

Boolean games are a framework for reasoning about the rational behaviour of agents, whose goals are formalized using propositional formulas. They offer an attractive alternative to normal-form games, because they allow for a more intuitive and more compact encoding. Unfortunately, however, there is currently no general, tailor-made method available to compute the equilibria of Boolean games. In this paper, we introduce a method for finding the pure Nash equilibria based on disjunctive answer set programming. Our method is furthermore capable of finding the core elements and the Pareto optimal equilibria, and can easily be modified to support other forms of optimality, thanks to the declarative nature of disjunctive answer set programming. Experimental results clearly demonstrate the effectiveness of the proposed method.

Possibilistic Answer Set Programming Revisited

Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an application point of view, existing semantics are not well-motivated, and do not always yield intuitive results. To develop a more suitable semantics, we first introduce a characterization of answer sets of classical ASP programs in terms of possibilistic logic where an ASP program specifies a set of constraints on possibility distributions. This characterization is then naturally generalized to define answer sets of PASP programs. We furthermore provide a syntactic counterpart, leading to a possibilistic generalization of the well-known Gelfond-Lifschitz reduct, and we show how our framework can readily be implemented using standard ASP solvers.

Towards Possibilistic Fuzzy Answer Set Programming

Fuzzy answer set programming (FASP) is a generalization of answer set programming to continuous domains. As it can not readily take uncertainty into account, however, FASP is not suitable as a basis for approximate reasoning and cannot easily be used to derive conclusions from imprecise information. To cope with this, we propose an extension of FASP based on possibility theory. The resulting framework allows us to reason about uncertain information in continuous domains, and thus also about information that is imprecise or vague. We propose a syntactic procedure, based on an immediate consequence operator, and provide a characterization in terms of minimal models, which allows us to straightforwardly implement our framework using existing FASP solvers.

Approximating Credal Network Inferences by Linear Programming

An algorithm for approximate credal network updating is presented. The problem in its general formulation is a multilinear optimization task, which can be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to very accurate inferences. The approach can also be specialized to classification with credal networks based on the maximality criterion. A complexity analysis for both the problem and the algorithm is reported together with numerical experiments, which confirm the good performance of the method. While the inner approximation produced by the algorithm gives rise to a classifier which might return a subset of the optimal class set, preliminary empirical results suggest that the accuracy of the optimal class set is seldom affected by the approximate probabilities