Towards enhancement of practicum teaching and learning: a theoretical framework to inform social work field education

During 1996 eighty social work students and 130 field educators from New Zealand were surveyed about their experiences of the teaching during students' first field placements. The sample was drawn from three schools of social work facilitating student placements with clients across nine broad types of client services. Ten percent of the total student and field educator
sample were later interviewed about these experiences and the findings related to this research have been reported elsewhere (Maidment, 2000; 1999). During the course of conducting the research it became apparent that the practicum component of social work education was somewhat bereft of learning theory that could be specifically used to understand the
unpredictable and varied nature of field education and the complexity of the student! supervisor relationship. Hence the development of a conceptual framework to both guide the research and later explain the findings on field teaching and learning became a major focus of the research. The following article traces the process used to develop a framework to understand the diverse nature of practicum education.

Experiential learning in social science theory: an investigation of the relationship between student enjoyment and learning

This paper provides an analysis of student experiences of an approach to teaching theory that integrates the teaching of theory and data analysis. The argument that supports this approach is that theory is most effectively taught by using empirical data in order to generate and test propositions and hypotheses, thereby emphasising the dialectic relationship between theory and data through experiential learning. Bachelor of Commerce students in two second-year substantive organisational theory subjects were introduced to this method of learning at a large, multi-campus Australian university. In this paper, we present a model that posits a relationship between students' perceptions of their learning, the enjoyment of the experience and expected future outcomes. The results of our evaluation reveal that a majority of students:

•enjoyed this way of learning;
•believed that the exercise assisted their learning of substantive theory, computing applications and the nature of survey data; and
•felt that what they have learned could be applied elsewhere.

We argue that this approach presents the potential to improve the way theory is taught by integrating theory, theory testing and theory development; moving away from teaching theory and analysis in discrete subjects; and, introducing iterative experiences in substantive subjects.

Speed control and policing in a cellular mobile network: speedNet

In this paper, we describe SpeedNet, a GSM network variant which resembles an ad hoc wireless mobile network where base stations keep track of the velocities of mobile users (cars). SpeedNet is intended to track mobile users and their speed passively for both speed policing and control of traffic. The speed of the vehicle is controlled in a speed critical zone by means of an electro-mechanical control system, suitably referred to as VVLS (Vehicular Velocity Limiting System). VVLS is mounted on the vehicle and responds to the command signals generated by the base station. It also determines the next base station to handoff, in order to improve the connection reliability and bandwidth efficiency of the underlying network. Robust Extended Kalman Filter (REKF) is used as a passive velocity estimator of the mobile user with the widely used proportional and integral controller speed control. We demonstrate through simulation and analysis that our prediction algorithm can successfully estimate the mobile user’s velocity with low system complexity as it requires two closest mobile base station measurements and also it is robust against system uncertainties due to the inherent deterministic nature in the mobility model.

Learning and teaching assessment: reviewing the evidence

The authors have recently completed a research review on learning and teaching of assessment in social work which was commissioned by the Social Care Institute for Excellence (SCIE) and the Social Policy and Social Work Learning and Teaching Support Network (SWAPltsn) to support the development of the new social work award in England. This involved reviewing relevant literature from social work and cognate disciplines back to 1990 with the aim of identifying best practice in learning and teaching of assessment skills.

Although assessment has been recognised as a core skill in social work and should underpin social work interventions, there is no singular theory or understanding as to what the purpose of assessment is and what the process should entail. Social work involvement in the assessment process may include establishing need or eligibility for services, to seek evidence of past events or to determine likelihood of future danger, may underpin recommendations to other agencies, or may determine the suitability of other service providers. In some settings assessment is considered to begin from the first point of contact and may be a relatively short process, whereas elsewhere it may be a process involving several client contacts over an extended period of time. The assessment process may range from the collection of data on standardised proforma to a flexible approach depending on circumstances. These variations permeate the literature on the learning and teaching of assessment in social work and cognate disciplines.

Several different approaches to classroom based learning were proposed in the literature including case-based teaching, interviews with actors who have been trained to play 'standardised clients', and observation of children and families, as well as didactic lecturing and various uses of video equipment and computers. Furthermore learning by doing has long been one of the hallmarks of social work education, and there are a number of models proposed in which students learn about the assessment process through conducting assessments. The evidence to support these different approaches to learning and teaching is variable. Based on the evidence reviewed, recommendations as to what is good practice in learning and teaching about assessment will be presented.

Evolutionary structure learning algorithm for Bayesian network and penalized mutual information metric

This paper formulates the problem of learning Bayesian network structures from data as determining the structure that best approximates the probability distribution indicated by the data. A new metric, Penalized Mutual Information metric, is proposed, and a evolutionary algorithm is designed to search for the best structure among alternatives. The experimental results show that this approach is reliable and promising.