This thesis is a documentation of an empirical study in which qualitative methods were employed to investigate the current programmes offered to pre-service Creative Arts teachers at selected South African universities. The subject, Creative Arts, is one of the compulsory learning areas for grades R - 9 in all South African public schools as prescribed by the Curriculum and Assessment Policy Statement of 2011. In order for learners to gain maximum benefit from the subject Creative Arts, pre-service teachers should be educated to gain an understanding of the interrelatedness of the different art forms. The theoretical framework underpinning this study is Mezirow's theory of transformative learning which is based on critical reflection. Pre-service teachers should therefore be encouraged to critically reflect on the learning process, rethinking their own perspectives and constructing new knowledge in the process of discourse with others. Information on the current programmes offered at five South African universities involved in this collective case study, was extrapolated from interviews with both lecturers of Creative Arts programmes, and pre-service teachers enrolled for courses in Creative Arts. Furthermore, observations were done at various sites to obtain an in-depth perspective of how the arts are presented at these institutions. Findings revealed that most universities offer Creative Arts programmes with an arts specific approach. This corresponds with the demands of artistic disciplines, and especially performance arts, which require the development of practical skills which should be developed over an extended period. Although developing these specialized skills and knowledge in each art form is important, the discrete presentation of these arts may limit opportunities for students to experience integrated arts activities. Moreover, pre-service teachers need practice in school based settings to hone their teaching skills in delivering meaningful arts activities to learners. The recognition of common grounds between the different art disciplines makes the merging of these arts into the broad subject, Creative Arts possible. These commonalities should be further explored, especially in a South African context where African arts are inherently integrated. Benefits of co-operative curriculum planning between the departments of Basic and Higher Education in the provision of competent and skilful teachers for Creative Arts is the key to successful arts education in South African schools. / Thesis (DMus)--University of Pretoria, 2016. / Music / DMus / Unrestricted

Philosophiae Doctor - PhD / Many low- and middle-income countries are faced with a rise in the double burden of malnutrition - undernutrition and overweight/obesity. Nutrition-related factors contribute to approximately 45% of deaths in children under five years (mainly due to undernutrition) globally, while low- and middle-income countries are simultaneously witnessing a rise in childhood overweight and obesity. In 2016, an estimated 41 million children under the age of five in low- and middle-income countries were overweight or obese, while 155 million were chronically undernourished. In Africa alone, the estimated prevalence of overweight and obese children in 2010 was 8.5%, expected to reach 12.7% in 2020. In comparison, globally, one in nine people are either hungry or undernourished, while one in three people are overweight. / 2024

Poor student achievement at some community colleges results in low retention and graduation rates. Addressing the problem of unpreparedness for college with good academic advising may help to improve student achievement. The purpose of this study was to determine whether there is a difference in the academic achievement of 1st year full-time (FYFT) community college students, based on having received 1 semester of any of 4 different academic advising methods (prescriptive, developmental, intrusive, proactive) while controlling for high school grade point average (GPA). Bandura's social learning theory was used as the theoretical framework. A quantitative research method, deploying 1 research question and 5 hypotheses, was used to guide the examination of a sample of 349 archived data records of Fall 2016 FYFT students at a community college in the northeastern United States. The study included a categorical (factor) and a metric (covariate) measures of variables; therefore, a 1-way ANCOVA was used to estimate the effect of the academic advising method on student achievement. The findings showed no significant difference in FYFT student GPA, based on having received academic advising in general or any method of academic advising, during the 1st semester of enrollment. Despite these findings, the literature supports academic advising as critical for improving GPA, implying that further research is needed to adequately determine trends in student achievement related to advising over more than 1 semester at the college studied. By understanding the difference in the academic achievement of FYFT students based on having received academic advising consistently, academic advisors will have information that can potentially enhance student achievement and increase students' chances of graduating, thus promoting positive social change.

Animals are commonly trained to perform behaviors during routine husbandry procedures. However, some husbandry procedures have aversive consequences when the real procedure is performed. This commonly results in loss of the trained behavior. The present study assessed whether maintaining the antecedent environmental stimulus conditions between appetitive and aversive outcomes would prevent this effect and, conversely, whether adding a stimulus discrepancy would facilitate this effect. Three domestic rats served as participants in a multiple baseline across participants design with multi-element components. All three rats stopped performing a trained behavior when a discrepant stimulus reliably predicted an aversive outcome. In addition, all three rats continued to perform the same behavior when antecedent environmental stimulus conditions were consistent between aversive and appetitive outcomes. Results are discussed in terms of practical implications for behavior change agents and conceptual implications for learning theory.

<p>High-dimensional regression problems are ubiquitous in science and engineering. Deep learning has been a critical tool for solving a wide range of high-dimensional problems with surprising performance. Even though in theory neural networks have good properties in terms of approximation and optimization, numerically obtaining an accurate neural network solution is a challenging problem due to the highly non-convex objective function and implicit bias of least square optimization. In this dissertation, we mainly discuss two topics involving the high dimensional regression using efficient deep learning algorithms. These two topics include solving PDEs with high dimensional domains and data-driven dynamical modeling. </p> <p><br></p> <p>In the first topic, we aim to develop an efficient solver for PDE problems. Firstly, we focus on neural network structures to increase efficiency. We propose a data-driven activation function called reproducing activation function which can reproduce traditional approximation tools and enable faster convergence of deep neural network training with smaller parameter cost. Secondly, we target the application of neural networks to mitigate the numerical issues that hamper the traditional approach. As an example, we develop a neural network solver for elliptic PDEs on unknown manifolds and verify its effectiveness for the large-scale problem. </p> <p><br></p> <p>In the second topic, we aim to enhance the accuracy of learning the dynamical system from data by incorporating the prior. In the missing dynamics problem, taking advantage of known partial dynamics, we propose a framework that approximates a map that takes the memories of the resolved and identifiable unresolved variables to the missing components in the resolved dynamics. With this framework, we achieve a low error to predict the missing component, enabling the accurate prediction of the resolved variables. In the recovering Hamiltonian dynamics, by the energy conservation property, we learn the conserved Hamiltonian function instead of its associated vector field. To better learn the Hamiltonian from the stiff dynamics, we identify and splits the</p> <p>training data into stiff and nonstiff portions, and adopt different learning strategies based on the classification to reduce the training error. </p>

<p>Misunderstanding or misinterpreting specific animal behavior and welfare terminology, as well as principles of learning theory, may influence an individual’s perceptions of horse behavior. This error could potentially result in unnecessary applications of horse training principles and/or human interventions, which could potentially worsen the behavior or situation, leading to unnecessary welfare problems. </p><p>The purpose of this dissertation was to explore interpretations and understandings of specific animal behavior and welfare terminology, and learning theory principles, as applied to horses, among adults within the horse industry. Chapters 1 and 2 introduced, summarized, and linked the connection between horse behavior, horse welfare, learning theory, and schema theory. Chapter 3 and Chapter 4 each pilot-tested an online survey that was completed at the convenience of each participant to explore these interpretations and understandings. Chapter 3 (n = 46) utilized a survey containing general demographic questions, psychographic questions related to horse industry involvement, five videos of horse-human interactions (each with corresponding heart rate, HR, data), and 11 learning theory scenarios. Chapter 4 (n = 21) used a survey containing general demographic questions and five videos of various human-horse interactions, including the same five videos with horse HR information included. Using results from Chapter 3 and Chapter 4, further investigation of how individuals interpret and understand specific animal behavior and welfare terminology, and learning theory principles, as applied to horses was explored across a larger sample of adults within the horse industry. Chapter 5 (n = 1,145) utilized the same survey instrument as Chapter 3 among a more robust sample of adults within the horse industry. </p><p>Across all three studies, the main results suggest that although participants demonstrated a high level of agreement between each other when identifying fear, stress, and reactivity to describe a horse’s behavior, participants could not correctly define fear, stress, reactivity, or principles of learning theory, as related to horses. They also could not connect these states to an important physiological factor, i.e., HR, when identifying these states. Results across all three studies suggest that most participant demographics (such as age, gender, or race) did not influence participants’ abilities to correctly identify or define fear, stress, reactivity, or learning theory principles. Similarly, results from Chapters 3 and 5 suggest that most participant psychographics, such as horse ownership, or level of involvement with horses, did not affect ability to correctly identify key horse behaviors related to fear, stress, and reactivity, or understanding of learning theory principles, or ability to correctly define these states and principles. </p><p> Overall, this dissertation identified the need for additional education when it comes to clearly defining specific states such as fear, stress, and reactivity for individuals across the horse industry. Additional psychographic factors, such as an individual’s specific role or niche in the industry, or an individuals’ overall view of horses, should be further explored.</p>

<p>    </p> <p>The first article presents a study that measured exhibit visitors' reported attitudes as measured by an early iteration of the attitudinal learning inventory (ALI) (Watson et al., 2018). The study, which was conducted at the Indiana State Fair and measured visitors’ self-reported attitude changes after visiting an exhibit about hellbender salamanders, found that 73% of survey respondents claimed they would change their behavior and 70% claimed they would tell others what they learned by visiting the exhibit. The second article presents a study that measured visitors' time spent at the exhibit to calculate holding power. Holding power was calculated by dividing the amount of time spent at the exhibit by the minimum amount of time it takes to read the text and interact with the exhibit. The holding power for the <em>What's Bugging Belva? </em>exhibit was favorable at .67 and is compared with exhibits with holding powers of .47 (Boisvert et al, 1995) and .69 (Peart, 1984). The third study gathered visitor data using the validated ALI and analyzed the data using the FREQ procedure (SAS 9.4). The study was conducted at the Indiana State Fair and Purdue Springfest and measured visitors’ responses to an exhibit about animal welfare. At both events, visitors had positive perceptions in the categories of cognitive and general learning, affective learning, behavioral learning, and social learning.  </p>

We design efficient algorithms for computational problems over strings in several models where the algorithms have limited access to the input. These models, and algorithms developed respecting these constraints, are becoming increasingly relevant due to the rapidly increasing size of datasets in myriad applications. Our first problem of interest is \emph{trace reconstruction}. This is an important problem in learning theory and coding theory, and has applications in computational biology. In this problem, the goal is to recover an unknown string given independent samples (\emph{traces}) of it generated via a probabilistic noise process called the deletion channel. We give state-of-the-art algorithms for this problem in several settings. Then we consider the problem of estimating the \emph{longest increasing subsequence (LIS)} of a given string in sublinear time, given query access to the string. While the LIS of a string can be computed exactly in near-linear time, the optimal complexity of approximating the LIS length, especially when the LIS is much less than the string length, is still open. We significantly improve upon prior work in terms of both approximation and time complexity in this regime. The runtime of our algorithm essentially matches the trivial query complexity lower bound as a function of the length of the LIS. Finally, we consider the problem of local decoding, or random access, on compressed strings. The Burrows-Wheeler Transform (BWT) is an important preprocessing step in lossless text compression that rearranges a string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings. However, the decoding process of the BWT is inherently sequential, and prevents fast random access to the original string. We design a succinct data structure for locally decoding short substrings (and answering several other queries) of a given string under its compressed BWT efficiently.

Thesis advisor: Audrey A. Friedman / Through adventure-based learning (ABL), individuals analyze unique experiences in order to generalize and apply critical skills and dispositions to their homes, schools, workplaces, and communities (Dillon, Tannehill, & O’Sullivan, 2010).  However, there is a lack of research documenting the transferability of ABL to other contexts (Kraft, 1999; Furman & Sibthorp, 2012). In educator preparation programs, coursework in ABL has been found inadequate for its incorporation into practice (Sutherland & Legge, 2016; Dillon, Tannehill, & O’Sullivan, 2010). Expanding this research base is critical in justifying “adventure programming [as] more than just fun and games, and to support it as the powerful form of change that practitioners tacitly know it to be” (Priest & Gass, 1999, p. 478), and understanding how that change can impact teachers. This research is informed by the overall question: In what ways can experience as an adventure-based learning (ABL) leader impact the subsequent epistemologies and practices of professional educators? Utilizing qualitative, collective case study methodology (Yin, 2018; Hancock & Algozzine, 2017) and grounded in Mezirow’s (2000) transformative learning theory, this research studies ten professional educators who, as college students, had served as ABL facilitators. Findings indicate that participants’ experience in facilitating ABL aligned with Mezirow’s criteria for transformative learning both personally and professionally. While participants rarely incorporated the physical challenges and fantastical premises typically associated with ABL, they reported their pre-professional experiences deeply influenced their pedagogical practice.  This research posits a new framework for these connections, adventure-informed pedagogy, to explore how ABL philosophies and processes, but not practices, impacted former facilitators and their classrooms. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.

This study aims to explore teachers’ experiences of an invitational learning environment in culturally diverse Foundation Phase classrooms. Foundation Phase teachers as well as members from the School Management Team were identified as participants to create in-depth information on the topic of research. An interpretivist research paradigm was used to portray the lived experiences and personal responses of the participants. A combined theoretical framework consisting of the Open Systems Theory and The Invitational Learning Theory guided this research. The literature in this study provides a detailed discussion of Invitation Education (IE) the roles and responsibilities of stakeholders in creating invitational learning environments, the relationship between culture and invitational educational, the effects of the environment on invitational teaching and learning. Semi-structured interviews, observation and visual data formed the data collection instruments in this study. Data were coded, examined and emerging themes were identified. The teachers and school management team members who participated in this study shared their insight in invitational learning environments, their methods for creation as well as the challenges that prevented their creation. This research summarised teachers experiences in creating an invitational learning environment and provided valuable techniques to create invitation and methods for overcoming challenges. / Dissertation (MEd)--University of Pretoria, 2019. / Early Childhood Education / MEd / Unrestricted