Elite swimmers can be distinguished from novice swimmers by freestyle stroke technique. Elite swimmers move through multiple coordination modes, increases in stroke lengths, stroke rates, and body roll allowing for a more symmetrical stroke and increased speed compared with novice swimmer during 100m freestyle. Coaches strive to improve swimmers’ performance by providing feedback about stroke technique, mostly from the pool deck where view of the full stroke cycle is obstructed by the water. Tools to assess swimming are often expensive and require extra training, which does not provide a pragmatic solution. A dryland rotational swimbench would provide a means to evaluate freestyle swimming. The aim of the present study is to evaluate the sensory motor system of elite and novice level swimmers by comparing kinematic, coordinative structures and spatial-temporal characteristics of freestyle stroke on a dryland swimbench with a rotational component. Thirty elite and novice collegiate and masters swimmers were instrumented with reflective markers bilaterally on the upper extremity and torso. A series of four ten second trials of freestyle sprint swimming were performed on the swimbench. Repeated measures were used for statistical analysis for comparison between and within groups. Bonferroni corrections were used as post-hoc analysis. Results indicated no significant difference between elite and novice swimmers’ sensory-motor system, kinematics or spatio-temporal systems on a rotational swimbench. Similarities could be accounted for by swimmers perceiving a novel task due to differences in sensory feedback, and mechanical limitations of the bench. It is noteworthy that catch-up/opposition coordination are more common than superposition which provides support for the swimbench providing a more similar representation to in water swimming.

Learning readiness is deficient in many first time school-going children. Learning readiness depends on a well-functioning neural network. Research has shown that movement as an early learning experience is necessary for optimal neural development. Presumably it is movement that activates the neural wiring in the brain. It influences neural organisation and stimulates the specific neurological systems required for optimal functioning and development of the brain. Some children are faced with motor proficiency deficits which may influence their learning and their readiness to learn. This study aimed at determining whether movement programmes are a means to promote and achieve learning readiness. A selected group of Grade two learners who participated in a specifically designed movement programme for ten weeks showed improvement in their levels of learning readiness based on their movement proficiency and academic level. Based on these findings, recommendations were made for the inclusion of movement in the school curriculum. / Educational Studies / M Ed. (Guidance and Counselling)

<p>A recent trend in evolutionary robotics and artificial life research is to maximize self-organization in the design of robotic systems, in particular using artificial evolutionary techniques, in order to reduce the human designer bias. This dissertation presents experiments in competitive co-evolutionary robotics that integrate and extend previous work on competitive co-evolution of neural robot controllers in a predator-prey scenario with work on the ‘co-evolution’ of robot morphology and control systems. The focus here is on a systematic investigation of tradeoffs and interdependencies between morphological parameters and behavioral strategies through a series of predator-prey experiments in which increasingly many aspects are subject to self-organization through competitive co-evolution. The results show that there is a strong interdependency between morphological parameters and behavioral strategies evolved, and that the competitive co-evolutionary process was able to find a balance between and within these two aspects. It is therefore concluded that competitive co-evolution has great potential as a method for the automatic design of robotic systems.</p>

Learning readiness is deficient in many first time school-going children. Learning readiness depends on a well-functioning neural network. Research has shown that movement as an early learning experience is necessary for optimal neural development. Presumably it is movement that activates the neural wiring in the brain. It influences neural organisation and stimulates the specific neurological systems required for optimal functioning and development of the brain. Some children are faced with motor proficiency deficits which may influence their learning and their readiness to learn. This study aimed at determining whether movement programmes are a means to promote and achieve learning readiness. A selected group of Grade two learners who participated in a specifically designed movement programme for ten weeks showed improvement in their levels of learning readiness based on their movement proficiency and academic level. Based on these findings, recommendations were made for the inclusion of movement in the school curriculum. / Educational Studies / M Ed. (Guidance and Counselling)

A recent trend in evolutionary robotics and artificial life research is to maximize self-organization in the design of robotic systems, in particular using artificial evolutionary techniques, in order to reduce the human designer bias. This dissertation presents experiments in competitive co-evolutionary robotics that integrate and extend previous work on competitive co-evolution of neural robot controllers in a predator-prey scenario with work on the ‘co-evolution’ of robot morphology and control systems. The focus here is on a systematic investigation of tradeoffs and interdependencies between morphological parameters and behavioral strategies through a series of predator-prey experiments in which increasingly many aspects are subject to self-organization through competitive co-evolution. The results show that there is a strong interdependency between morphological parameters and behavioral strategies evolved, and that the competitive co-evolutionary process was able to find a balance between and within these two aspects. It is therefore concluded that competitive co-evolution has great potential as a method for the automatic design of robotic systems.