Exiles on Main Street: A Pedagogy of Popular Music Through Technology and Aesthetic Education

This dissertation investigates the application of instructional technology within the specific context of popular music education. Synthesizing the work of Mishra & Koehler (2006) and Bauer (2014), this dissertation operationalizes a broader, more contemporary definition of instructional technology that goes beyond the traditional conception of mere instructional tool towards one that is more protean, unstable, and opaque. Research questions about technology’s impact on music education are central to this curriculum study and evolve into considerations on how the relationship of popular music and instructional technology shape a pedagogy for popular music education. Making use of principles rooted in aesthetic education, critical pedagogy, and TPACK, the curriculum created fulfills the requirements of an undergraduate program in music education mapped onto the National Association of Schools of Music standards. Presented along with a standards map are course overviews, syllabi, and lesson plans that specifically make use of the theoretical backgrounds discussed

Engaging Middle School Students Through Music History Mini-Lessons: a Mixed-Methods Study

Understanding history is a vital part of learning. Nearly every question asked in a music classroom about musical context involves its history, from notation to gestures or technicality to aural listening. History can bring music to life for both the performers and listeners. Despite multiple studies on specific historical music events, music history perspectives have not been addressed in the choral classroom. Moreover, research forums have yet to explore engagement factors of middle school students through a music history curriculum in the choir classrooms. Such research could provide a valid model for educators. This mixed-methods research study seeks to determine if music history lessons offer a statistically significant difference in student engagement by identifying viewpoints that have not been explored and documented concerning middle school choir students’ learning, values, and understanding of music. The researcher will illustrate an engagement of middle school choir students with the musical genres of jazz, rock, pop, and classical before and after mini-lessons about the historical context. Responses were collected through a pre-test and post-test survey and questionnaire. This quasi-experiment will utilize a control and variable group of seventh-grade choir students (N=68) from a middle school in Iowa

BagStack Classification for Data Imbalance Problems with Application to Defect Detection and Labeling in Semiconductor Units

abstract: Despite the fact that machine learning supports the development of computer vision applications by shortening the development cycle, finding a general learning algorithm that solves a wide range of applications is still bounded by the ”no free lunch theorem”. The search for the right algorithm to solve a specific problem is driven by the problem itself, the data availability and many other requirements. Automated visual inspection (AVI) systems represent a major part of these challenging computer vision applications. They are gaining growing interest in the manufacturing industry to detect defective products and keep these from reaching customers. The process of defect detection and classification in semiconductor units is challenging due to different acceptable variations that the manufacturing process introduces. Other variations are also typically introduced when using optical inspection systems due to changes in lighting conditions and misalignment of the imaged units, which makes the defect detection process more challenging. In this thesis, a BagStack classification framework is proposed, which makes use of stacking and bagging concepts to handle both variance and bias errors. The classifier is designed to handle the data imbalance and overfitting problems by adaptively transforming the multi-class classification problem into multiple binary classification problems, applying a bagging approach to train a set of base learners for each specific problem, adaptively specifying the number of base learners assigned to each problem, adaptively specifying the number of samples to use from each class, applying a novel data-imbalance aware cross-validation technique to generate the meta-data while taking into account the data imbalance problem at the meta-data level and, finally, using a multi-response random forest regression classifier as a meta-classifier. The BagStack classifier makes use of multiple features to solve the defect classification problem. In order to detect defects, a locally adaptive statistical background modeling is proposed. The proposed BagStack classifier outperforms state-of-the-art image classification techniques on our dataset in terms of overall classification accuracy and average per-class classification accuracy. The proposed detection method achieves high performance on the considered dataset in terms of recall and precision.Dissertation/ThesisDoctoral Dissertation Computer Engineering 201

The Effects of the Orff Approach on Language Acquisition for Spanish Foreign Language Students

Despite the abundance of literature that supports music education connecting to language learning, limited research evaluates the effectiveness of elementary music methodologies, such as the Orff approach, in helping foreign language students in their language learning. The Orff approach develops musicianship in every student through music, movement, speech, and drama. Guided by Gardner’s theory of multiple intelligences, the researcher implemented a quasi-experimental research study to measure the language fluency of 100 elementary students participating in general music and learning Spanish as a foreign language. The researcher placed half of the students in the treatment group exploring the Orff approach in general music and half in the control group in music appreciation. After completing a Spanish pretest and participating in the two-month intervention, both groups are assessed via the Spanish Student Growth Objective (SGO) halfway benchmark. Scores reflect students’ listening, speaking, reading, and writing abilities. This work provides evidence of the effects of the Orff approach on language acquisition. It allows readers to ascertain the potential connections between the brain regions responsible for language learning and those responsible for developing musicianship. Such a study is groundbreaking because it can inspire the development of professional learning communities among the arts and language departments and promote further cross-curricular connections to music. Furthermore, this study can encourage further research as scholars can test various general music methodologies and successful acquisition of other target or foreign languages

Neural Mechanisms for Information Compression by Multiple Alignment, Unification and Search

This article describes how an abstract framework for perception and cognition may be realised in terms of neural mechanisms and neural processing. This framework — called information compression by multiple alignment, unification and search (ICMAUS) — has been developed in previous research as a generalized model of any system for processing information, either natural or artificial. It has a range of applications including the analysis and production of natural language, unsupervised inductive learning, recognition of objects and patterns, probabilistic reasoning, and others. The proposals in this article may be seen as an extension and development of Hebb’s (1949) concept of a ‘cell assembly’. The article describes how the concept of ‘pattern’ in the ICMAUS framework may be mapped onto a version of the cell assembly concept and the way in which neural mechanisms may achieve the effect of ‘multiple alignment’ in the ICMAUS framework. By contrast with the Hebbian concept of a cell assembly, it is proposed here that any one neuron can belong in one assembly and only one assembly. A key feature of present proposals, which is not part of the Hebbian concept, is that any cell assembly may contain ‘references’ or ‘codes’ that serve to identify one or more other cell assemblies. This mechanism allows information to be stored in a compressed form, it provides a robust mechanism by which assemblies may be connected to form hierarchies and other kinds of structure, it means that assemblies can express abstract concepts, and it provides solutions to some of the other problems associated with cell assemblies. Drawing on insights derived from the ICMAUS framework, the article also describes how learning may be achieved with neural mechanisms. This concept of learning is significantly different from the Hebbian concept and appears to provide a better account of what we know about human learning

Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

January 23, 2017 Armstrong Faculty Senate Agenda

January 23, 2017 Armstrong Faculty Senate Agend

Ouachita Baptist University General Catalog 2020-2021

This is the Bulletin of Ouachita Baptist University with Announcements for the 2020-2021 school year in Arkadelphia, Arkansas.https://scholarlycommons.obu.edu/catalogs/1115/thumbnail.jp