A study of novice programmer performance and programming pedagogy.

Identifying and mitigating the difficulties experienced by novice programmers is an active area of research that has embraced a number of research areas. The aim of this research was to perform a holistic study into the causes of poor performance in novice programmers and to develop teaching approaches to mitigate them. A grounded action methodology was adopted to enable the primary concepts of programming cognitive psychology and their relationships to be established, in a systematic and formal manner. To further investigate novice programmer behaviour, two sub-studies were conducted into programming performance and ability. The first sub-study was a novel application of the FP-Tree algorithm to determine if novice programmers demonstrated predictable patterns of behaviour. This was the first study to data mine programming behavioural characteristics rather than the learner’s background information such as age and gender. Using the algorithm, patterns of behaviour were generated and associated with the students’ ability. No patterns of behaviour were identified and it was not possible to predict student results using this method. This suggests that novice programmers demonstrate no set patterns of programming behaviour that can be used determine their ability, although problem solving was found to be an important characteristic. Therefore, there was no evidence that performance could be improved by adopting pedagogies to promote simple changes in programming behaviour beyond the provision of specific problem solving instruction. A second sub-study was conducted using Raven’s Matrices which determined that cognitive psychology, specifically working memory, played an important role in novice programmer ability. The implication was that programming pedagogies must take into consideration the cognitive psychology of programming and the cognitive load imposed on learners. Abstracted Construct Instruction was developed based on these findings and forms a new pedagogy for teaching programming that promotes the recall of abstract patterns while reducing the cognitive demands associated with developing code. Cognitive load is determined by the student’s ability to ignore irrelevant surface features of the written problem and to cross-reference between the problem domain and their mental program model. The former is dealt with by producing tersely written exercises to eliminate distractors, while for the latter the teaching of problem solving should be delayed until the student’s program model is formed. While this does delay the development of problem solving skills, the problem solving abilities of students taught using this pedagogy were found to be comparable with students taught using a more traditional approach. Furthermore, monitoring students’ understanding of these patterns enabled micromanagement of the learning process, and hence explanations were provided for novice behaviour such as difficulties using arrays, inert knowledge and “code thrashing”. For teaching more complex problem solving, scaffolding of practice was investigated through a program framework that could be developed in stages by the students. However, personalising the level of scaffolding required was complicated and found to be difficult to achieve in practice. In both cases, these new teaching approaches evolved as part of a grounded theory study and a clear progression of teaching practice was demonstrated with appropriate evaluation at each stage in accordance with action researc

Support Vector Machines for Anatomical Joint Constraint Modelling

The accurate simulation of anatomical joint models is becoming increasingly important for both realistic animation and diagnostic medical applications. Recent models have exploited unit quaternions to eliminate singularities when modeling orientations between limbs at a joint. This has led to the development of quaternion based joint constraint validation and correction methods. In this paper a novel method for implicitly modeling unit quaternion joint constraints using Support Vector Machines (SVMs) is proposed which attempts to address the limitations of current constraint validation approaches. Initial results show that the resulting SVMs are capable of modeling regular spherical constraints on the rotation of the limb

Self Organising Maps for Anatomical Joint Constraint

The accurate simulation of anatomical joint models is becoming increasingly important for both realistic animation and diagnostic medical applications. Recent models have exploited unit quaternions to eliminate ingularities when modelling orientations between limbs at a joint. This has led to the development of quaternion based joint constraint validation and correction methods. In this paper a novel method for implicitly modelling unit quaternion joint constraints using Self Organizing Maps (SOMs) is proposed which attempts to address the limitations of current constraint validation and correction approaches. Initial results show that the resulting SOMs are capable of modelling regular spherical constraints on the orientation of the limb

Evolved Topology Generalized Multi-layer Perceptron (GMLP) for Anatomical Joint Constraint Modelling

The accurate simulation of anatomical joint models is becoming increasingly important for both medical diagnosis and realistic animation applications. Quaternion algebra has been increasingly applied to model rotations providing a compact representation while avoiding singularities. We propose the use of Artificial Neural Networks to accurately simulate joint constraints based on recorded data. This paper describes the application of Genetic Algorithm approaches to neural network training in order to model corrective piece-wise linear / discontinuous functions required to maintain valid joint configurations. The results show that artificial Neural Networks are capable of modeling constraints on the rotation of and around a virtual limb

Reprint

New Foreword by John D. Nystuen.http://deepblue.lib.umich.edu/bitstream/2027.42/60207/1/Reprint94MDacey.pd

Evidence in Managing the Learning Experience

Quality systems in general rely on the availability of appropriate evidence to permit the development of continuous improvement schemes. Practical service in managing the learning experience has highlighted the rich variety of sources of information available to the HE manager. Time basis has a critical importance in control, and the cycles of evidence collection occurs across the year are of variable value in terms of critique and analysis. The importance of formal mechanisms for quantitative and qualitative data collection are well established, but some of the use of such data is open to question, particularly where statistics are applied for small samples. The informal mechanisms are no less important, and can offer both short cycle opportunities for practical intervention and long-term quality improvements based on professionalism and systematic developments that are often not captured in the formal reporting cycles. The implications of typical problems and the value of the evidence sources within the context of likely use are assessed, with corrective actions indicated. The role of perception, and particularly of the setting and meeting of expectations, and the complexities arising from prior beliefs, is emphasised. Quality evidence is a matter of signposts for investigation; successful improvement of correct interpretation

Surgery for pituitary tumor apoplexy is associated with rapid headache and cranial nerve improvement

Pituitary tumor apoplexy (PTA) classically comprises sudden-onset headache, loss of vision, ophthalmoparesis, and decreased consciousness. It typically results from hemorrhage and/or infarction within a pituitary adenoma. Presentation is heterologous, and optimal management is debated. The time course of recovery of cranial nerve deficits (CNDs) and headaches is not well established. In this study, a retrospective series of consecutive patients with PTA managed at a single academic institution over a 22-year period is presented. Headaches at the time of surgery were more severe in the early and subacute surgical cohort and improved significantly within 72 h postoperatively

Spatial theory and human behavior

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45971/1/10110_2005_Article_BF01952731.pd