This research study delves into the multifaceted realm of social presence in online education, encompassing the existence and manifestation of social presence indicators in students' engagement with discussion boards within asynchronous online courses. Social presence manifests when individuals perceive themselves to be simultaneously present with others through a communication medium, thereby cultivating a shared sense of togetherness. The dissertation addresses the impact of course disciplines, exploring the significant influence of both STEM and non-STEM courses on the manifestation of social presence indicators. Furthermore, the study delves into the influence of course duration on the social presence level, unveiling critical insights into the challenges posed by prolonged courses on sustaining student engagement and interaction.This study, randomly selecting sample from Coursera, employed a methodology, encompassing both quantitative and qualitative analysis, to assess social presence within online courses. The approach consisted of five key stages, involving Python-based web crawling, manual keyword identification, data processing, statistical analysis using R, and qualitative exploration. The insights obtained offer valuable suggestions for enhancing social presence in future online educational settings. While acknowledging certain limitations regarding sample size and keyword identification, the study provides valuable contributions to the evolving landscape of online education research, offering practical implications for course design and facilitation in promoting an enriched and engaging online learning environment. / Communication Sciences

The rise of conversational generative AI chatbots such as ChatGPT and Gemini is revolutionizing online interactions. Previous research has identified five categories of uses and gratifications (U&G) for users engaging with these chatbots: information seeking, task efficiency, social interaction, entertainment, and personalization. Despite the wide range of use cases, most chatbots provide one-size-fits-all text-based interactions, neglecting user preferences. Recent advancements are progressively introducing interactive features that empower users to control their interactions, such as choosing a preferred conversational style. However, despite these improvements in the industry, the interactivity in gen AI chatbots remains underexplored. This thesis serves as a user-centric foundational study of user engagement with gen AI chatbots by understanding users’ context of use across the five U&G dimensions, analyzing the limitations of text-based interactions, and proposing practical suggestions for desired interactive features.

With an increase in complexity of software, developers rely more on reuse and dependencies in their source code via code snippets. As a result, it is becoming harder to identify and mitigate vulnerabilities. Although traditional analysis tools are still utilized, machine learning models are being adopted to expand efforts and combat such threats. Given the possibilities towards usage of such models, research in this area has introduced various approaches which vary in usability and prediction. In generalizing models to a more natural language approach, researchers have opted to train models on source code to identify existing and potential vulnerabilities. Exploratory research has been performed by treating source code as plain text, creating “text-based” models. With a motivation to prevent vulnerable code snippets, we present a dissertation on the effectiveness of text-based machine learning models for vulnerability detection. We utilize datasets composed of open-source projects and vulnerability types to generate our own training and testing data via extracted function pairings. Using this data, we evaluate a series of text-based machine learning models, coupled with natural language processing (NLP) techniques and our own data processing methods. Through empirical research, we demonstrate the effectiveness of such models based on statistical evidence. From these results, we determine negative correlations and identify "cross-cutting" features. Finally, we present analysis of models with "cross-cutting" feature removal to improve performance while providing explainability towards model decisions.

This study is concerned with the effect of placing text into a mediated structure form upon the generation of test items for analysis level domain referenced test construction. The item writing methodology used is the linguistic (operationally defined) item writing technology developed by Bormuth, Finn, Roid, Haladyna and others. This item writing methodology is compared to 1) the intuitive method based on Bloom's definition of analysis level test questions and 2) the intuitive with keywords identified method of item writing. A mediated structure was developed by coordinating or subordinating sentences in an essay by following five simple grammatical rules. Three test writers each composed a ten-item test using each of the three methodologies based on a common essay. Tests were administered to 102 Composition 1 community college students. Students were asked to read the essay and complete one test form. Test forms by writer and method were randomly delivered. Analysis of variance showed no significant differences among either methods or writers. Item analysis showed no method of item writing resulting in items of consistent difficulty among test item writers. While the results of this study show no significant difference from the intuitive, traditional methods of item writing, analysis level test item generation using a mediating structure may yet prove useful to the classroom teacher with access to a computer. All three test writers agree that test items were easier to write using the generative rules and mediated structure. Also, some relief was felt by the writers in that the method theoretically assured that an analysis level item was written.

Syftet med denna studie är att undersöka olika stödstrukturer som kan stödja elever när de tarsig an textbaserade problemlösningsuppgifter. Detta har skett genom en systematisklitteraturstudie som sedan resulterade i flera kategorier av stödstrukturer. I studiens resultatsynliggjordes tre huvudkategorier av stödstrukturer: Orienterande stödstrukturer,Digitaliserade stödstrukturer och Visuellt organiserande stödstrukturer. Den sistnämndeinnehöll två underkategorier som fick benämningen, Schema-baserade samt Visuellarepresentationer. Vår slutsats av denna studie var att ett begränsat antal elevanpassadestödstrukturer från de olika kategorierna är att rekommendera för elever som tar sig antextbaserade problemlösningsuppgifter. / Problem solving is a part of school mathematics and students require different types ofsupport. The purpose of this study is to examine the different types of support structureswhich can support students when they try to solve text-based problem-solving tasks. Thisstudy uses a systematic literature study as means to identify different categories of supportstructures. The result identified three main categories which are: Orientating supportstructure, Digitalization support structure and Visual organization support structure. Thelatter contains two subcategories which are, Schema-based and Visual representation. Ourconclusion of this study suggests that a limited amount of student adapted support structuresfrom the different categories is to be recommended for students who are solving text-basedproblem-solving tasks.

This dissertation investigated Taiwanese English as Foreign Language (EFL) learners' incidental noticing and their subsequent language learning in relation to learner proficiency level and dyadic type in a text-based computer-mediated communication (CMC) environment. Sixty participants were included to form 30 dyads. At random, eight low-intermediate and eight advanced nonnative English speakers (NNESs) were paired with 16 native English speakers (NESs) to form 16 NES-NNES dyads; another 14 advanced NNESs and 14 low-intermediate NNESs were paired to form 14 mixedproficiency NNES-NNES dyads. The results revealed that the synchronous computer-mediated communication (SCMC) medium could, in general, enhance the occurrence of learners' incidental noticing and their subsequent second language (L2) learning regardless of learners' proficiency levels and dyadic types. No significant differences were found in the amount of the language-related episodes (LREs) produced by the NES-NNES dyads when compared to the NNES-NNES dyads. With regard to the number of LREs generated by the learners of different proficiency levels, the results showed that: (1) in the NESNNES dyads, no significant difference was found between the low-intermediate and advanced learners, and (2) in the NNES-NNES dyads, the low-intermediate learners produced a significantly greater number of LREs than their advanced interlocutors. In terms of the effect of interlocutors' proficiency levels on the number of LREs produced by the learners, the results revealed that: (1) the low-intermediate learners in the NESNNES dyads produced a significantly greater number of LREs than the low-intermediate learners in the NNES-NNES dyads, and (2) the advanced learners in the NES-NNES dyads also produced a significantly greater number of LREs than the advanced learners in the NNES-NNES dyads. With respect to the learners' performance on both posttests, the results of chi-square analyses showed that: (1) no significant differences were found both within and across the two dyadic types, and (2) no significant differences were found between learners of different proficiency levels within and across both NES-NNS and NNES-NNES dyads. Logistic regression analyses revealed that five LRE characteristics (type, source, complexity, proficiency, and successful uptake) in the NES-NNES dyads and three LRE characteristics (proficiency, timing and successful uptake) in the NNES-NNES dyads were shown to be significant predictor variables of the learners' subsequent L2 learning. Successful uptake was the most prevalent predictor variable of the learners' subsequent L2 learning across the two dyadic types. Besides, proficiency appeared to be the second prevalent variable but played a different role in these two dyadic types. Considering the language aspects focused in the LREs, negotiations on the linguistic features of grammar, vocabulary, and spelling were much more prevalent than the pragmatic aspects of language.

Deep penetration of personal computers, data communication networks, and the Internet has created a massive platform for data collection, dissemination, storage, and retrieval. Large amounts of textual data are now available at a very low cost. Valuable information, such as consumer preferences, new product developments, trends, and opportunities, can be found in this large collection of textual data. Growing worldwide competition, new technology development, and the Internet contribute to an increasingly turbulent business environment. Conducting surveillance on this growing collection of textual data could help a business avoid surprises, identify threats and opportunities, and gain competitive advantages.Current text mining approaches, nonetheless, provide limited support for conducting surveillance using textual data. In this dissertation, I develop novel text quantification approaches to identify useful information in textual data, effective anomaly detection approaches to monitor time series data aggregated based on the text quantification approaches, and empirical evaluation approaches that verify the effectiveness of text mining approaches using external numerical data sources.In Chapter 2, I present free-text chief complaint classification studies that aim to classify incoming emergency department free-text chief complaints into syndromic categories, a higher level of representation that facilitates syndromic surveillance. Chapter 3 presents a novel detection algorithm based on Markov switching with jumps models. This surveillance model aims at detecting different types of disease outbreaks based on the time series generated from the chief complaint classification system.In Chapters 4 and 5, I studied the surveillance issue under the context of business decision making. Chapter 4 presents a novel text-based risk recognition design framework that can be used to monitor the changing business environment. Chapter 5 presents an empirical evaluation study that looks at the interaction between news sentiment and numerical accounting earnings information. Chapter 6 concludes this dissertation by highlighting major research contributions and the relevance to MIS research.

The use of the Internet has increased exponentially over the last decade. Individuals across all continents are progressively engaging in cyberspace interactions at work, in education, and for leisure. These online interactions, unconstrained by the limitations of corporeal reality, offer the potential for unique presentations of the self. The general aim of the research described in this thesis was to examine self-presentation in cyberspace. The research focused on MOOs, multi-user, text-based, user-extensible online environments, as a likely site for identity experimentation and play in cyberspace. Two studies are described. In the first quantitative study, 75 university students logged on to the front page of a social MOO where they selected a screen name, chose their gender, and provided a character description. As hypothesised, self-presentations were more likely to be based on actual identity rather than hoped for or feared selves. Contrary to expectation, little evidence was found of gender play. Self-presentations were typically positively biased and results suggested that players also perceived themselves more positively in the online context. Although sex and age were generally unrelated to self-presentation strategies, previous online experience, ethnicity, and personality profiles helped to explain self-presentation behaviour. / A qualitative study of a further 20 students in an educational MOO explored players understanding of their initial self-presentational choices and their management of these self-presentations over a 12-week period. Findings from the second study were consistent with the results from the first quantitative study and confirmed a strong desire for authentic self-presentation. Despite this emphasis on authenticity, the intention to play with identity was manifest in the form of selective self-disclosure, fantasy play, and exaggeration of traits. Participants also reported behaving in less inhibited ways online. A low incidence of gender play was noted. The overt identity play assumed by the cyberspace literature was not found in either study. Rather self-presentation in the online context appears to be governed by essentially similar processes to those that shape self-presentation in the offline world. The implications of the findings for teaching and learning, particularly for educators who want to use MOOs for identity experimentation, are discussed.

We investigate the factors that determine the performance of text-based language identification, with a particular focus on the 11 official languages of South Africa. Our study uses n-gram statistics as features for classification. In particular, we compare support vector machines, Naïve Bayesian and difference-in-frequency classifiers on different amounts of input text and various values of n, for different amounts of training data. For a fixed value of n the support vector machines generally outperforms the other classifiers, but the simpler classifiers are able to handle larger values of n. The additional computational complexity of training the support vector machine classifier may not be justified in light of importance of using a large value of n, except possibly for small sizes of the input window when limited training data is available. We find that it is more difficult to discriminate languages within language families then those across families. The accuracy on small input strings is low due to this reason, but for input strings of 100 characters or more there is only a slight confusion within families and accuracies as high as 99.4% are achieved. For the smallest input strings studied here, which consist of 15 characters, the best accuracy achieved is only 83%, but when the languages in different families are grouped together, this corresponds to a usable 95.1% accuracy. The relationship between the amount of training data and the accuracy achieved is found to depend on the window size – for the largest window (300 characters) about 400 000 characters are sufficient to achieve close-to-optimal accuracy, whereas improvements in accuracy are found even beyond 1.6 million characters of training data. Finally, we show that the confusions between the different languages in our set can be used to derive informative graphical representations of the relationships between the languages. / Dissertation (MEng)--University of Pretoria, 2008. / Electrical, Electronic and Computer Engineering / unrestricted

Philosophiae Doctor - PhD / The 'conversations' under investigation have all been initiated by the National Department of Education (DoE) and are identified in this thesis as the following: the Values Report (2000); Opening Pathways (2002), the Manifesto (2001); and the Baseline Report (2004). During 2000 the Minister of Education, who recognised the need for public discussion on values in education, appointed a working group to produce a document on values in education, namely the Values Report. That report proposed six values to be nurtured in schools. The DoE invited public comment on the Values Report and these comments were taken into account when a conference on values in education was held during February 2001, namely the Saamtrek Conference. Meanwhile, the DoE commissioned school-based research during 2000. The purpose of the research was to establish what meanings school communities assigned to the values that were proposed in the Values Report. The research findings were published in 2002, but an interim report, Opening Pathways, was published during 2001, and informed discussions at the Saamtrek Conference. The Manifesto was published later during 2001, and proposed ten values to be nurtured in schools. It also proposed sixteen educational strategies that could be employed to nurture these values. During 2004 the DoE again commissioned school-based research, the baseline research, which culminated in the Baseline Report. The purpose of the baseline research was to establish what were the perceptions and practices of school communities in respect of values and human rights. There was vigorous engagement with the issue of values in education during the first few years of the 21st century. During 2002 the DoE launched a Values in Education Programme of Action in order to promote the nurturing of values in education. One of the initiatives of this programme was the introduction of an Advanced Certificate in Education (ACE) programme aimed at practising teachers. This was the ACE: Integrating values and human rights across the curriculum, which was funded by the DoE, and offered at various institutions of Higher Education from July 2003 to June 2005. There was less vigorous engagement with the issue of values in education after 2004, when a new Minister of Education was appointed. An example of less vigorous engagement with values in education is the following: the ACE on values and human rights was not state-funded beyond 2005. It is against this background that I engaged with the mentioned conversations about values in education. My interest in conversations about values in education arose out of my involvement, from 2003 to 2005, with the ACE programme on values and human rights which was offered by the University of the Western Cape. My thesis format differs from the majority of theses in this country since my research was entirely text-based, thus devoid of fieldwork. This thesis corresponds to what I have identified as a topic-based format. Each chapter, with the exclusion of the .introductory, research methodology and conclusions and recommendations chapters, investigates a specific topic that forms part of the conversations about values in education. My research data consisted of conversations about values in education as captured in the documents mentioned above, namely the Values Report. Opening Pathways, the Manifesto and the Baseline Report. My thesis does not have a separate literature review chapter. Neither does it have a chapter in which research findings are presented, analysed and discussed. Separate chapters on a review of the literature and on presentation, analysis and discussion of research findings are usually features of a thesis which relies for its data on fieldwork. However, a review of the literature and research findings are infused in five of the eight chapters that comprise this thesis. I made use of relevant literature in order to interrogate DoE conversations about values in education. That interrogation led me to arrive at research findings in respect of DoE conversations about values in education. My research methodology was located within a qualitative research paradigm, with an interpretive metatheoretical approach. I identified my research design as philosophy as social practice, and my research method as philosophical investigation. I undertook an investigation of the grammar of these conversations about values in education, that is, an investigation of the arguments provided by the DoE for claims made in respect of values in education. That investigation included the following: a clarification of assumptions underpinning DoE arguments; uncovering of DoE conceptions about the goals and purposes of schooling; establishing the extent of continuity amongst DoE conversations; highlighting the extent of conceptual clarity in DoE conversation; and exploring what meanings are assigned by the DoE to value concepts. The investigation of the grammar of the relevant DoE conversations illuminated DoE engagement with the following concepts: 'values', 'character', 'morality', 'conversation', 'education', 'inquiry', 'schooling', 'ethics', 'citizenship' and 'whole school'. In the process of this investigation I developed a conceptual framework for thinking about values in education, engaged with the notion of developing shared understandings in respect of values in education, drew attention to inquiry as a type of conversation that is conceptually linked to education, and investigated the notion of deliberation as a way of nurturing values in education.