Philosophiae Doctor - PhD / The aim of this study was to use a case study approach to explore and describe how students and teachers perceived performance assessment and context-based assessment models that were used within a real world context teaching and learning approach. The topics Electricity and Air and Living Things formed the science knowledge base for the study. Four junior secondary school science teachers and their students in four schools participated. Participants; experiences of the assessment models were achieved through teachers administering and scoring performance assessment tasks and context-based unit tests to their students. Perceptions were obtained through questionnaires and interviews from students. Interviews and informal discussions were used to elicit teachers; perceptions. Observations during the administration of performance assessment tasks were also used for triangulation. / South Africa

Magister Educationis - MEd / Bullying is rife at South African schools. Previous studies published in 2008 revealed the frequency of bullying amongst high school learners to be 36% in Cape Town and 41% at national level of the total number of high school learners who participated in the investigation. This behaviour amongst learners hampers efforts to raise educational standards and improve schools in our country. Besides, the vicious cycle of bully/victim relationships has a negative influence on individual learners. In South Africa, bullying behaviour in schools has been found to lead to problems such as a low self-esteem, low academic performance, absenteeism, depression, and consequently school dropout. In this study the frequency and different forms of bullying experienced by learners in South African schools were investigated using questionnaires, individual interviews, and focus group interviews with grade 10 learners and their teachers at three selected schools in the Western Cape. Questionnaires were administered to two grade 10 classes in each of the three selected schools. Analysis of the questionnaires was followed by two sets of interviews: individual interviews with one female grade 10 learner and one male grade 10 learner at each of the three selected schools, and focus group interviews with two male grade 10 teachers and two female grade 10 teachers in each school. The findings confirm that bullying is rampant in the three selected schools. A mean of 96% of the respondents reported that bullying happens at their school. In addition, a mean of 38% of the respondents stated that bullying happens every day at their school. Furthermore, all the different types of bullying, that is, physical, verbal, emotional, and cyber-bullying, occur at the three selected schools, and each of them is influenced by individual and contextual factors. However, this investigation discovered that the most flexible and influential cause of peer bullying is the contextual (that is, ‘inside of school’) factors. This study also revealed that learners at the three selected schools experience various consequences of bullying such as lowering of self-esteem, high rates of absenteeism, self-harm, inability to make progress in their studies, insecurity, and isolation of victims. Finally, some recommendations to address the issue of school bullying are made in respect of schools, teachers, parents and learners. Recommendations are also made in respect of future research on bullying.

This exploration into the individual’s experience of industrial theatre has aimed to determine the underlying dynamics involved in the individual’s experience of industrial theatre in order to attempt to understand the value of industrial theatre in the workplace. Thus, to understand how industrial theatre can be applied in the organisational context to influence human behaviour in such as way as to enhance the individual’s productivity and satisfaction. In addition, this investigation extends on a body of knowledge on the nature and application of theatre and art-based methods in the work context. The exploration establishes the experience of industrial theatre as an aesthetic experience of an aesthetic object (theatre) at its core. Industrial theatre is then framed as an adaptation of theatre, applied in various ways for various purposes in the work context. The nature of industrial theatre, as deduced from relevant literature, describes industrial theatre as a unique medium for instruction and agent of change. The existing literature is then deconstructed to provide graphic representations of the ideal experience of theatre and interactive industrial theatre. The production of an industrial theatre performance entitled Birds of a Feather was performed on 13 August 2009 and used to explore the individual’s experience. Semi-structured interviews were conducted with a sample of nine participants [n=9]. The concepts that emerged from the data were theatrical experience; industrial theatre experience; overall experience (perceived value-added); and influencing factors (individual and performance). These concepts were further coded and analysed by means of content analysis, within the social constructivist methodology. The Atlas.ti (x5) program was utilized to analyse, manage and store the data. The resulting findings led to the conclusion that the individual experiences industrial theatre in four distinct phases, namely: perception, engagement, response and reaction. Perception refers to the initial contact between audience and performance and relates to the external experience (visual and auditory). Engagement refers to the audience’s relation with the industrial theatre production – here the spectator-actor relationship takes centre stage. Response refers to the audience’s initial response, whereas reaction refers to the prolonged response to the industrial theatre production. A graphic presentation of the individual’s experience of these four phases during Birds of a Feather was created and presented in the conclusion. Overall, the study concluded that industrial theatre is experienced as a value-adding intervention for organisations – providing both entertainment and educational value to the individual and the organisation alike. Copyright 2010, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. Please cite as follows: Howes, L 2010, The individual’s experience of industrial theatre : an exploration, MCom dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-02162012-123115 / > C12/4/201/gm / Dissertation (MCom)--University of Pretoria, 2012. / Human Resource Management / unrestricted

Numerous studies have been undertaken on the political economy of agricultural policies in developing countries. These studies have explained agricultural policies in terms of urban bias, economic reforms, and domestic politics. Recently, the emphasis has been on explanations that reference the existence of a rational-legal and patronage element within the African state. Such explanations tend to underplay the extent to which agricultural policies are devised in a context of power asymmetries between the state and international donors or financial institutions. In the Malawian context specifically, limited attention has been paid to the possibility that policies are a negotiated outcome of interactions informed by competing objectives at the state-donor interface. Accordingly, the proposed study will attempt to fill this existing gap in the literature. Malawi is currently at the center of policy debates regarding the state’s capacity to launch a uniquely African Green Revolution within a marketized and capitalist configuration. Such debates mark the continued underinvestment in agriculture on the African continent. The Malawi case, therefore, provides a unique opportunity to explore the extent to which state level efforts are either confounded or enabled by donors and international financial institutions. The specific successes and failures of the Malawi case speak to the question of how other countries in Sub-Saharan Africa might successfully address food production and food security issues. This dissertation will explore the overarching question of the role of the state and international donors in shaping agricultural and food security policies using Malawi’s farm input subsidy program as a case study. The main research methods to explore this question are qualitative, including interviews with various development stakeholders (government ministries, international development agencies, researchers from policy research and academic institutions, and civil society organizations) associated with agriculture and food policy-making, and textual analysis of publications associated with them. The research specifically targets key experts in the area of agriculture and food security. The findings indicate that policies have been greatly influenced by the competing ideologies of the state and donors, with each recognizing the problem but differing on the approach and modalities for solving food insecurity in Malawi. To this extent, there has been considerable inconsistency in policies with obvious negative outcomes. More recently, there has been an aligning of policy positions towards the use of social welfare programs and commercialization in addressing food insecurity. This alignment relates to policy positions on both the FISP and the configuration of the wider agricultural sector as manifest in the National Agricultural Policy, for example. The role of domestic politics vs. donors in policy processes has been in flux due to changes in the political and economic environment and configuration at specific junctures. The study also finds that evidence has been important in informing policy-making, more importantly, finance has had significant impact in attenuating the influence of domestic politics, so that the recently proposed and implemented reforms to FISP, although connected to considerable sociopolitical pressure from various quarters, have been largely precipitated by a serious fiscal crisis on the part of the government. To this extent, the state has assumed a pragmatic approach to policy-making i.e., one that is cognizant of the limitations imposed by finance and Malawi’s very harsh, challenging, and complex context.

Driver distraction remains a matter of concern throughout the world as the number of car accidents caused by distracted driving is still unacceptably high. Industry and academia are working intensively to design new techniques that will address all types of driver distraction including visual, manual, auditory and cognitive distraction. This research focuses on an existing technology, namely in-car communication systems (ICCS). ICCS allow drivers to interact with their mobile phones without touching or looking at them. Previous research suggests that ICCS have reduced visual and manual distraction. Two problems were identified in this research: existing ICCS are still expensive and only available in limited models of car. As a result of that, only a small number of drivers can obtain a car equipped with an ICCS, especially in developing countries. The second problem is that existing ICCS are not aware of the driving context, which plays a role in distracting drivers. This research project was based on the following thesis statement: A mobile, context-aware model can be designed to reduce driver distraction caused by the use of ICCS. A mobile ICCS is portable and can be used in any car, addressing the first problem. Context-awareness will be used to detect possible situations that contribute to distracting drivers and the interaction with the mobile ICCS will be adapted so as to avert calls and text messages. This will address the second problem. As the driving context is dynamic, drivers may have to deal with critical safety-related tasks while they are using an existing ICCS. The following steps were taken in order to validate the thesis statement. An investigation was conducted into the causes and consequences of driver distraction. A review of literature was conducted on context-aware techniques that could potentially be used. The design of a model was proposed, called the Multimodal Interface for Mobile Info-communication with Context (MIMIC) and a preliminary usability evaluation was conducted in order to assess the feasibility of a speech-based, mobile ICCS. Despite some problems with the speech recognition, the results were satisfying and showed that the proposed model for mobile ICCS was feasible. Experiments were conducted in order to collect data to perform supervised learning to determine the driving context. The aim was to select the most effective machine learning techniques to determine the driving context. Decision tree and instance-based algorithms were found to be the best performing algorithms. Variables such as speed, acceleration and linear acceleration were found to be the most important variables according to an analysis of the decision tree. The initial MIMIC model was updated to include several adaptation effects and the resulting model was implemented as a prototype mobile application, called MIMIC-Prototype.

Mobile devices with access to large numbers of sensors with internet access move forwards the development of intelligent applications towards new shape of ubiquitous applications. In order to create such applications we need to be able to do simulations to test and deploy. Current simulators do not permit this since they are centralized and the information is not shared globally. Therefore we cannot use them to test application built on distributed sensor information. I selected Siafu as the simulator component. In the next step, the simulator was customized according to the requirements of the project. There are different possibilities to achieve this task, but a simple GUI is made to control the simulator.The end result is a complete architecture for simulating context aware scenarios. The implementation is tested by running the simulator and dumping the context data into the PGRID overlay. For future work, implementing proximity estimation between the agents will be a good idea and can be interesting as well.

The presence of Allophone students in French-language secondary schools in Ottawa is gradually increasing. While the politique d’aménagement linguistique (PAL) insists on the use of French within the school, one may begin to wonder which language Allophone students are speaking. French? English? Their native language(s)? This qualitative case study of four multilingual Allophone students explores their language repertoire use in relation to their desired linguistic representation, their linguistic proficiency in French, English, and their native language(s), and their perceptions of language prestige. The results indicate that students spoke a significant amount of English, some French (particularly with their teacher or Francophone classmates), and minimal amounts of their native language. Recommendations are suggested to increase the effectiveness of PAL within a Francophone minority context and to ensure that the policy’s objects are attained.

Due to the rapid increase of social network resources and services, Internet users are now overwhelmed by the vast quantity of social media available. By utilizing the user’s context while consuming diverse multimedia contents, we can identify different personal preferences and settings. However, there is still a need to reinforce the recommendation process in a systematic way, with context-adaptive information. This thesis proposes a recommendation model, called HPEM, that establishes a bridge between the multimedia resources, user collaborative preferences, and the detected contextual information, including physiological parameters. The collection of contextual information and the delivery of the resulted recommendation is made possible by adapting the user’s environment using Ambient Intelligent (AmI) interfaces. Additionally, this thesis presents the potential of including a user’s biological signal and leveraging it within an adapted collaborative filtering algorithm in the recommendation process. First, the different versions of the proposed HPEM model utilize existing online social networks by incorporating social tags and rating information in ways that personalize the search for content in a particular detected context. By leveraging the social tagging, our proposed model computes the hidden preferences of users in certain contexts from other similar contexts, as well as the hidden assignment of contexts for items from other similar items. Second, we demonstrate the use of an optimization function to maximize the Mean Average Prevision (MAP) measure of the resulted recommendations. We demonstrate the feasibility of HPEM with two prototype applications that use contextual information for recommendations. Offline and online experiments have been conducted to measure the accuracy of delivering personalized recommendations, based on the user’s context; two real-world and one collected semi-synthetic datasets were used. Our evaluation results show a potential improvement to the quality of the recommendation when compared to state-of-the-art recommendation algorithms that consider contextual information. We also compare the proposed method to other algorithms, where user’s context is not used to personalize the recommendation results. Additionally, the results obtained demonstrate certain improvements on cold start situations, where relatively little information is known about a user or an item.

Scene parsing, or segmenting all the objects in an image and identifying their categories, is one of the core problems of computer vision. In order to achieve an object-level semantic segmentation, we build upon the recent superparsing approach by Tighe and Lazebnik, which is a nonparametric solution to the image labeling problem. Superparsing consists of four steps. For a new query image, the most similar images from the training dataset of labeled images is retrieved based on global features. In the second step, the query image is segmented into superpxiels and 20 di erent local features are computed for each superpixel. We propose to use the SLICO segmentation method to allow control of the size, shape and compactness of the superpixels because SLICO is able to produce accurate boundaries. After all superpixel features have been extracted, feature-based matching of superpixels is performed to nd the nearest-neighbour superpixels in the retrieval set for each query superpxiel. Based on the neighbouring superpixels a likelihood score for each class is calculated. Finally, we formulate a Conditional Random Field (CRF) using the likelihoods and a pairwise cost both computed from nonparametric estimation to optimize the labeling of the image. Speci cally, we de ne a novel pairwise cost to provide stronger semantic contextual constraints by incorporating the similarity of adjacent superpixels depending on local features. The optimized labeling obtained with the CRF results in superpixels with the same labels grouped together to generate segmentation results which also identify the categories of objects in an image. We evaluate our improvements to the superparsing approach using segmentation evaluation measures as well as the per-pixel rate and average per-class rate in a labeling evaluation. We demonstrate the success of our modi ed approach on the SIFT Flow dataset, and compare our results with the basic superparsing methods proposed by Tighe and Lazebnik.

This thesis achieved the goal of obtaining high accuracy rates (precision and recall) in a real-time system that detects and recognizes text in the automotive context. For the sake of simplicity, this work targets two Objects of Interest (OOIs): North American (NA) traffic boards (TBs) and license plates (LPs). The proposed approach adopts a hybrid detection module consisting of a Connected Component Analysis (CCA) step followed by a Texture Analysis (TA) step. An initial set of candidates is extracted by highlighting the Maximally Stable Extremal Regions (MSERs). Each sebsequent step in the CCA and TA steps attempts to reduce the size of the set by filtering out false positives and retaining the true positives. The final set of candidates is fed into a recognition stage that integrates an open source Optical Character Reader (OCR) into the framework by using two additional steps that serve the purpose of minimizing false readings as well as the incurred delays. A set of of manually taken videos from various regions of Ottawa were used to evaluate the performance of the system, using precision, recall and latency as metrics. The high precision and recall values reflect the proposed approach's ability in removing false positives and retaining the true positives, respectively, while the low latency values deem it suitable for the automotive context. Moreover, the ability to detect two OOIs of varying appearances demonstrates the flexibility that is featured by the hybrid detection module.