South African Computer Journal - Volume 51, Issue 1, 2013
Volumes & issues
Volume 51, Issue 1, 2013
Author Philip MachanickSource: South African Computer Journal 51 (2013)More Less
Source: South African Computer Journal 51, pp 1 –9 (2013)More Less
The study is designed to examine students' perceptions of the introductory Information Systems (IS) course. It was an exploratory study in which 67 students participated. A quantitative approach was followed making use of questionnaires for the collection of data. Using the theory of reasoned action as a framework, the study explores the factors that influence non-IS major students' perceived relevance of the IS introductory course. The analysis of collected data included descriptive and inferential statistics. Using multiple regression analysis, the results suggest that overall, the independent variables, relevance of the content, previous IT knowledge, relevance for professional practice, IT preference in courses and peers' influence may account for 72% of the explanatory power for the dependent variable, perceived relevance of the IS course. In addition, the results have shown some strong predictors (IT preference and peers' influence) that influence students' perceived relevance of the IS course. Practical work was found to be a strong mediating variable toward positive perceptions of IS. The results of this study suggest that students do indeed perceive the introductory IS course to be relevant and match their professional needs, but more practical work would enhance their learning. Implications for theory and practice are discussed as a result of the behavioural intention to perceive the IS course to be relevant and eventually to recruit more IS students.
Author Carl MarnewickSource: South African Computer Journal 51, pp 10 –21 (2013)More Less
Research has been done within the South African information technology (IT) industry over the last decade with regard to project management maturity (PMM) and the impact it has on delivering information systems (IS) projects successfully. The research was done to determine whether IS PMM per knowledge area has improved over the last decade. It investigates if there is a correlation between maturity levels and project success. Four independent surveys over the last decade focused on IS PMM and the longitudinal analysis provides a benchmark for whether IS PMM has increased or not. This article focuses on whether certain knowledge areas are more of a problem within the IT industry and to determine what the overall IS PMM is. The longitudinal analysis indicates trends and highlights areas of concern. It indicates that most IT companies are still operating at level 3 and that risk and procurement management are the knowledge areas of concern. A comparative analysis indicates that there is no difference between South African and international maturity levels. The results provide a South African perspective of IS PMM. It highlights that risk management is still a knowledge area that is neglected and that emphasis must be placed on managing risk within IT projects.
Source: South African Computer Journal 51, pp 22 –43 (2013)More Less
This paper proposes Polyandry, a new nature-inspired modification to canonical Genetic Programming (GP). Polyandry aims to improve evolvability in GP. Evolvability is a critically important GP trait, the maintenance of which determines the arrival of the GP at a global optimum solution. Specifically evolvability is defined as the ability of the genetic operators employed in GP to produce offspring that are fitter than their parents. When GP fails to exhibit evolvability, further adaptation of the GP individuals towards a global optimum solution becomes impossible. Polyandry improves evolvability by improving the typically disruptive standard GP crossover operator. The algorithm employs a dual strategy towards this goal. The chief part of this strategy is an incorporation of genetic material from multiple mating partners into broods of offspring. Given such a brood, the offspring in the brood then compete according to a culling function, which we make equivalent to the main GP fitness function. Polyandry's incorporation of genetic material from multiple GP individuals into broods of offspring represents a more aggressive search for building block information. This characteristic of the algorithm leads to an advanced explorative capability in both GP genotype space and fitness space. The second component of the Polyandry strategy is an attempt at multiple crossover points, in order to find crossover points that minimize building block disruption from parents to offspring. This strategy is employed by a similar algorithm, Brood Recombination. We conduct experiments to compare Polyandry with the canonical GP. Our experiments demonstrate that Polyandry consistently exhibits better evolvability than the canonical GP. As a consequence, Polyandry achieves higher success rates and discovers globally optimal solutions in significantly fewer generations than the latter. The result of these observations is that given certain brood size settings, Polyandry requires less computational effort to arrive at a global optimum solution than the canonical GP. We also conduct experiments to compare Polyandry with the analogous nature-inspired modification to canonical GP, Brood Recombination. The adoption of Brood Recombination in order to improve evolvability is ubiquitous in GP literature. Our results demonstrate that Polyandry consistently exhibits better evolvability than Brood Recombination, due to a more explorative nature of the algorithm in both genotype and fitness space. As a result, although the two algorithms exhibit similar success rates, Polyandry consistently discovers globally optimal solutions in significantly fewer GP generations than Brood Recombination. The key advantage of Polyandry over Brood Recombination is therefore faster solution discovery. As a consequence Polyandry consistently requires less computational effort to arrive at a global optimum solution compared to Brood Recombination. Further, we establish that the computational effort exerted by Polyandry is competitively low, relative to other Evolutionary Algorithm (EA) methodologies in literature. We conclude that Polyandry is a better alternative to both the canonical GP as well as Brood Recombination with regards to the achievement and maintenance of evolvability.