Learner-Teacher Interaction (LTI): engaging and supporting students in achieving self-regulated learning

This report represents the second stage of a study which was part of a wide-ranging research programme conducted by the Centre for Excellence of Interprofessional Education, Queen’s University Belfast. The study was an investigation into learner-teacher interaction in the education of undergraduate medical and other healthcare students in order to inform how teachers might facilitate learning in a healthcare setting. It focused in particular on clinical and ward-based tutorials and seminars.

In order to give meaning to this second stage of the study, the report will contextualise the learner-teacher interaction study, will describe the research methods and methods of analysis developed and used to explore learner-teacher interaction. It will then focus on this second stage of the research and the results of the analysis of video sessions of clinical and ward-based tutorials and seminars. In particular it will identify examples of good practice and missed opportunities for the engagement of the learners.

Self-regulated Shocks in Massive Star Binary Systems

In an early-type, massive star binary system, X-ray bright shocks result from the powerful collision of stellar winds driven by radiation pressure on spectral line transitions. We examine the influence of the X-rays from the wind-wind collision shocks on the radiative driving of the stellar winds using steady-state models that include a parameterized line force with X-ray ionization dependence. Our primary result is that X-ray radiation from the shocks inhibits wind acceleration and can lead to a lower pre-shock velocity, and a correspondingly lower shocked plasma temperature, yet the intrinsic X-ray luminosity of the shocks, L X, remains largely unaltered, with the exception of a modest increase at small binary separations. Due to the feedback loop between the ionizing X-rays from the shocks and the wind driving, we term this scenario as self-regulated shocks. This effect is found to greatly increase the range of binary separations at which a wind-photosphere collision is likely to occur in systems where the momenta of the two winds are significantly different. Furthermore, the excessive levels of X-ray ionization close to the shocks completely suppress the line force, and we suggest that this may render radiative braking less effective. Comparisons of model results against observations reveal reasonable agreement in terms of log (L X/L bol). The inclusion of self-regulated shocks improves the match for kT values in roughly equal wind momenta systems, but there is a systematic offset for systems with unequal wind momenta (if considered to be a wind-photosphere collision).

Conceptions of Teacher Identity: Creating Self-Boxes as Arts-Based Self-Study

This paper presents a palimpsest of ways in which self-study draws upon arts-based methods not just as processes towards teacher development, but also as means to problematize and inquire into conceptualizations of the self. It focuses on the creation of individual self-boxes that mediate teachers’ dynamic narratives of identity. Concepts of the unitary self, the decentred self and the relationship between inner and outer experience are challenged and illustrated through two interlapping stories made manifest through the creation of self-boxes. From time immemorial man has known that he is the subject most deserving of his own study, but he has also fought shy of treating this subject as a whole, that is, in accordance with its total character. (Buber, 1947, p. 140)

Evaluation of extended training for general practice in Northern Ireland: qualitative study.

Objective To evaluate participants' perceptions of the impact on them of an additional six months' training beyond the standard 12 month general practice vocational training scheme. Design Qualitative study using focus groups. Setting General practice vocational training in Northern Ireland. Participants 13 general practitioner registrars, six of whom participated in the additional six months' training, and four trainers involved in the additional six months' training. Main outcome measures: Participants' views about their experiences in 18 month and 12 month courses. Results Participants reported that the 12 month course was generally positive but was too pressurised and focused on examinations, and also that it had a negative impact on self care. The nature of the learning and assessment was reported to have left participants feeling averse to further continuing education and lacking in confidence. In contrast, the extended six month component was reported to have restimulated learning by focusing more on patient care and promoting self directed learning. It developed confidence, promoted teamwork, and gave experience of two practice contexts, and was reported as valuable by both ex-registrars and trainers. However, both the 12 and 18 month courses left participants feeling underprepared for practice management and self care. Conclusions 12 months' training in general practice does not provide doctors with the necessary competencies and confidence to enter independent practice. The extended period was reported to promote greater professional development, critical evaluation skills, and orientation to lifelong learning but does not fill all the gaps.

How counselling psychologists view their personal therapy

A survey of UK chartered counselling psychologists (N = 192) was carried out to investigate how they viewed their personal therapy. Eighty-four respondents completed questionnaires about their reasons and motivations for therapy, as well as its outcome and process. The results indicated that the majority (88%) were in favour of personal therapy as a training requirement. Most respondents rated the outcome and process of their personal therapy as positive, however 27% also reported some negative effects. A factor analysis of various components of personal therapy indicated that counselling psychologists made a distinction between three factors, i.e. learning about therapy itself, issues arising out of training and dealing with personal issues. Analyses of the data suggested that aims and motivation for therapy were related to dealing with personal issues, whereas these were not important for the other factors. Learning about therapy itself was related to the number of sessions: more specifically, chose who had more than the mandatory 40 sessions rated contributions of their personal therapy co understanding therapeutic relationships and processes more highly than those who had less. Initial sessions may be used by trainees to explore personal issues, leading to a preoccupation with the self, and learning about therapy per se may only occur once this has been dealt with.

A strategy towards professionalism in the dissecting room

The teaching and cultivation of professionalism is an integral part of medical education as professionalism is central to maintaining the public’s trust in the medical profession. Traditionally professional values would have been acquired through an informal process of socialisation and observation of role models. Recently, however, medical educators have accepted the responsibility to explicitly teach and effectively evaluate professionalism. A comprehensive working definition of the term professionalism and a universally agreed list of the constituent elements of professionalism are currently debated. The School of Medicine and Dentistry of The Queen’s University of Belfast uses an approach of self-directed learning for teaching anatomy, and students are given the opportunity to learn anatomy from human dissection. Self-directed learning teams have been found to be underutilised as educational strategies and presented an opportunity to utilise the first year dissection room teaching environment to nurture the development of the attributes of professionalism. An educational strategy based on role-playing was developed to engage all students around the dissection table. Students received comprehensive background reviews on professionalism, its attributes and the identification of such attributes in the context of the dissection room. Roles, with specific duties attached, were allocated to each team member. Circulating academic staff members directly observed student participation and gave formative feedback. Students were given the opportunity to reflect on their ability to identify the attributes and reflect on their own and their peer’s ability to develop and practise these attributes. This strategy indicated that small group learning teams in the dissection room utilise widely accepted principles of adult learning and offer an opportunity to create learning activities that will instil in students the knowledge, values, attitudes and behaviours that characterise medical professionalism. Anatomy faculty have a responsibility to nurture and exemplify professionalism and play a significant role in the early promotion and inculcation of professionalism. It remains imperative not only to assess this strategy but also to create opportunities for critical reflection and evaluation within the strategy. Key words: Medical Education – Professionalism – Anatomy - Reflective Practise – Role-play

Children's use of interventions to learn causal structure

Children aged between 5 and 8 years freely intervened on a three-variable causal system, with their task being to discover whether it was a common-cause structure or one of two causal chains. From 6-7 years, children were able to use information from their interventions to correctly disambiguate the structure of a causal chain. We used a Bayesian model to examine children’s interventions on the system; this showed that with development children became more efficient in producing the interventions needed to disambiguate the causal structure and that the quality of interventions, as measured by their informativeness, improved developmentally. The latter measure was a significant predictor of children’s correct inferences about the causal structure. A second experiment showed that levels of performance were not reduced in a task in which children did not select and carry out interventions themselves, indicating no advantage for self-directed learning. However, children’s performance was not related to intervention quality in these circumstances, suggesting that children learn in a different way when they carry out interventions themselves.

Social categorizations, social comparisons and stigma: Presentations of self in people with learning difficulties

Self-categorization theory stresses the importance of the context in which the metacontrast principle is proposed to operate. This study is concerned with how 'the pool of psychologically relevant stimuli' (Turner, Hogg, Oakes, Reicher & Wetherell, 1987, p. 47) comprising the context is determined. Data from interviews with 33 people with learning difficulties were used to show how a positive sense of self might be constructed by members of a stigmatized social category through the social worlds that they describe, and therefore the social comparisons and categorizations that are made possible. Participants made downward comparisons which focused on people with learning difficulties who were less able or who displayed challenging behaviour, and with people who did not have learning difficulties but who, according to the participants, behaved badly, such as beggars, drunks and thieves. By selection of dimensions and comparison others, a positive sense of self and a particular set of social categorizations were presented. It is suggested that when using self-categorization theory to study real-world social categories, more attention needs to be paid to the involvement of the perceiver in determining which stimuli are psychologically relevant since this is a crucial determinant of category salience.

A self-learning algorithm for biased molecular dynamics

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.