Work in progress: Data explorer - Assessment data integration, analytics, and visualization for STEM education research

Citation: Weese, J. L., & Hsu, W. H. (2016). Work in progress: Data explorer - Assessment data integration, analytics, and visualization for STEM education research.We describe a comprehensive system for comparative evaluation of uploaded and preprocessed data in physics education research with applicability to standardized assessments for discipline-based education research, especially in science, technology, mathematics, and engineering. Views are provided for inspection of aggregate statistics about student scores, comparison over time within one course, or comparison across multiple years. The design of this system includes a search facility for retrieving anonymized data from classes similar to the uploader's own. These visualizations include tracking of student performance on a range of standardized assessments. These assessments can be viewed as pre- and post-tests with comparative statistics (e.g., normalized gain), decomposed by answer in the case of multiple-choice questions, and manipulated using pre-specified data transformations such as aggregation and refinement (drill down and roll up). Furthermore, the system is designed to incorporate a scalable framework for machine learning-based analytics, including clustering and similarity-based retrieval, time series prediction, and probabilistic reasoning. © American Society for Engineering Education, 2016

The impact of STEM experiences on student self-efficacy in computational thinking

Citation: Weese, J. L., Feldhausen, R., & Bean, N. H. (2016). The impact of STEM experiences on student self-efficacy in computational thinking.Since the introduction of new curriculum standards at K-12 schools, computational thinking has become a major research area. Creating and delivering content to enhance these skills, as well as evaluation, remain open problems. This paper describes two different interventions based on the Scratch programming language which aim to improve student self-efficacy in computer science and computational thinking. The two interventions were applied at a STEM outreach program for 5th-9th grade students. Previous experience in STEM related activities and subjects, as well as student self-efficacy, were collected using a developed pre- and post-survey. We discuss the impact of our intervention on student performance and confidence, and evaluate the validity of our instrument. © American Society for Engineering Education, 2016

A convolutive model for polyphonic instrument identification and pitch detection using combined classification

Master of ScienceDepartment of Computing and Information SciencesWilliam H. HsuPitch detection and instrument identification can be achieved with relatively high accuracy when considering monophonic signals in music; however, accurately classifying polyphonic signals in music remains an unsolved research problem. Pitch and instrument classification is a subset of Music Information Retrieval (MIR) and automatic music transcription, both having numerous research and real-world applications. Several areas of research are covered in this thesis, including the fast Fourier transform, onset detection, convolution, and filtering. Basic music theory and terms are also presented in order to explain the context and structure of data used. The focus of this thesis is on the representation of musical signals in the frequency domain. Polyphonic signals with many different voices and frequencies can be exceptionally complex. This thesis presents a new model for representing the spectral structure of polyphonic signals: Uniform MAx Gaussian Envelope (UMAGE). The new spectral envelope precisely approximates the distribution of frequency parts in the spectrum while still being resilient to oscillating rapidly (noise) and is able to generalize well without losing the representation of the original spectrum. When subjectively compared to other spectral envelope methods, such as the linear predictive coding envelope method and the cepstrum envelope method, UMAGE is able to model high order polyphonic signals without dropping partials (frequencies present in the signal). In other words, UMAGE is able to model a signal independent of the signal’s periodicity. The performance of UMAGE is evaluated both objectively and subjectively. It is shown that UMAGE is robust at modeling the distribution of frequencies in simple and complex polyphonic signals. Combined classification (combiners), a methodology for learning large concepts, is used to simplify the learning process and boost classification results. The output of each learner is then averaged to get the final result. UMAGE is less accurate when identifying pitches; however, it is able to achieve accuracy in identifying instrument groups on order-10 polyphonic signals (ten voices), which is competitive with the current state of the field

Phylogenetic utility, and variability in structure and content, of complete mitochondrial genomes among genetic lineages of the Hawaiian anchialine shrimp <i>Halocaridina rubra</i> Holthuis 1963 (Atyidae:Decapoda)

<p>The Atyidae are caridean shrimp possessing hair-like setae on their claws and are important contributors to ecological services in tropical and temperate fresh and brackish water ecosystems. Complete mitochondrial genomes have only been reported from five of the 449 species in the family, thus limiting understanding of mitochondrial genome evolution and the phylogenetic utility of complete mitochondrial sequences in the Atyidae. Here, comparative analyses of complete mitochondrial genomes from eight genetic lineages of <i>Halocaridina rubra</i>, an atyid endemic to the anchialine ecosystem of the Hawaiian Archipelago, are presented. Although gene number, order, and orientation were syntenic among genomes, three regions were identified and further quantified where conservation was substantially lower: (1) high length and sequence variability in the <i>tRNA-Lys</i> and <i>tRNA-Asp</i> intergenic region; (2) a 317-bp insertion between the <i>NAD6</i> and <i>CytB</i> genes confined to a single lineage and representing a partial duplication of <i>CytB</i>; and (3) the putative control region. Phylogenetic analyses utilizing complete mitochondrial sequences provided new insights into relationships among the <i>H. rubra</i> genetic lineages, with the topology of one clade correlating to the geologic sequence of the islands. However, deeper nodes in the phylogeny lacked bootstrap support. Overall, our results from <i>H. rubra</i> suggest intra-specific mitochondrial genomic diversity could be underestimated across the Metazoa since the vast majority of complete genomes are from just a single individual of a species.</p