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Description
This project sheds light on trombonist Andy Martin's improvisation and provides tools for further learning. A biographical sketch gives background on Martin, establishing him as a newer jazz master. Through the transcription and analysis of nine improvised solos, Martin's improvisational voice and vocabulary is deciphered and presented as a series of seven thematic hooks. These patterns, rhythms, and gestures are described, analyzed, and presented as examples of how each is used in the solos. The hooks are also set as application exercises for learning jazz style and improvisation. These exercises demonstrate how to use Martin's hooks as a means for furthering one's own improvisation. A full method for successful transcription is also presented, along with the printed transcriptions and their accompanying information sheets.
ContributorsWilkinson, Michael Scott (Author) / Ericson, John (Thesis advisor) / Kocour, Michael (Committee member) / Solis, Theodore (Committee member) / Arizona State University (Publisher)
Created2013
Description
Jazz continues, into its second century, as one of the most important musics taught in public middle and high schools. Even so, research related to how students learn, especially in their earliest interactions with jazz culture, is limited. Weaving together interviews and observations of junior and senior high school jazz players and teachers, private studio instructors, current university students majoring in jazz, and university and college jazz faculty, I developed a composite sketch of a secondary school student learning to play jazz. Using arts-based educational research methods, including the use of narrative inquiry and literary non-fiction, the status of current jazz education and the experiences by novice jazz learners is explored. What emerges is a complex story of students and teachers negotiating the landscape of jazz in and out of early twenty-first century public schools. Suggestions for enhancing jazz experiences for all stakeholders follow, focusing on access and the preparation of future jazz teachers.
ContributorsKelly, Keith B (Author) / Stauffer, Sandra (Thesis advisor) / Tobias, Evan (Committee member) / Kocour, Michael (Committee member) / Sullivan, Jill (Committee member) / Schmidt, Margaret (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsShi, Ge (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-25
Description
Concerto for Piano and Chamber Orchestra was conceived in February of 2013, and conceptually it is my attempt to fuse personal expressions of jazz and classical music into one fully realized statement. It is a three movement work (fast, slow, fast) for 2 fl., 2 ob., 2 cl., bsn., 2 hrn., 2 tpt., tbn., pno., perc., str. (6,4,2,2,1). The work is approximately 27 minutes in duration. The first movement of the Concerto is written in a fluid sonata form. A fugato begins where the second theme would normally appear, and the second theme does not fully appear until near the end of the solo piano section. The result is that the second theme when finally revealed is so reminiscent of the history of jazz and classical synthesis that it does not sound completely new, and in fact is a return of something that was heard before, but only hinted at in this piece. The second movement is a kind of deconstructive set of variations, with a specific theme and harmonic pattern implied throughout the movement. However, the full theme is not disclosed until the final variation. The variations are interrupted by moments of pure rhythmic music, containing harmony made up of major chords with an added fourth, defying resolution, and dissolving each time back into a new variation. The third movement is in rondo form, using rhythmic and harmonic influences from jazz. The percussion plays a substantial role in this movement, acting as a counterpoint to the piano part throughout. This movement and the piece concludes with an extended coda, inspired indirectly by the simple complexities of an improvisational piano solo, building in complexity as the concerto draws to a close.
ContributorsSneider, Elliot (Author) / Rogers, Rodney (Thesis advisor) / DeMars, James (Committee member) / Hackbarth, Glenn (Committee member) / Solis, Theodore (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsShatuho, Kristina (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-27
Description
Accelerated life testing (ALT) is the process of subjecting a product to stress conditions (temperatures, voltage, pressure etc.) in excess of its normal operating levels to accelerate failures. Product failure typically results from multiple stresses acting on it simultaneously. Multi-stress factor ALTs are challenging as they increase the number of experiments due to the stress factor-level combinations resulting from the increased number of factors. Chapter 2 provides an approach for designing ALT plans with multiple stresses utilizing Latin hypercube designs that reduces the simulation cost without loss of statistical efficiency. A comparison to full grid and large-sample approximation methods illustrates the approach computational cost gain and flexibility in determining optimal stress settings with less assumptions and more intuitive unit allocations.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
ContributorsNasir, Ehab (Author) / Pan, Rong (Thesis advisor) / Runger, George C. (Committee member) / Gel, Esma (Committee member) / Kao, Ming-Hung (Committee member) / Montgomery, Douglas C. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Research methods based on the frequentist philosophy use prior information in a priori power calculations and when determining the necessary sample size for the detection of an effect, but not in statistical analyses. Bayesian methods incorporate prior knowledge into the statistical analysis in the form of a prior distribution. When prior information about a relationship is available, the estimates obtained could differ drastically depending on the choice of Bayesian or frequentist method. Study 1 in this project compared the performance of five methods for obtaining interval estimates of the mediated effect in terms of coverage, Type I error rate, empirical power, interval imbalance, and interval width at N = 20, 40, 60, 100 and 500. In Study 1, Bayesian methods with informative prior distributions performed almost identically to Bayesian methods with diffuse prior distributions, and had more power than normal theory confidence limits, lower Type I error rates than the percentile bootstrap, and coverage, interval width, and imbalance comparable to normal theory, percentile bootstrap, and the bias-corrected bootstrap confidence limits. Study 2 evaluated if a Bayesian method with true parameter values as prior information outperforms the other methods. The findings indicate that with true values of parameters as the prior information, Bayesian credibility intervals with informative prior distributions have more power, less imbalance, and narrower intervals than Bayesian credibility intervals with diffuse prior distributions, normal theory, percentile bootstrap, and bias-corrected bootstrap confidence limits. Study 3 examined how much power increases when increasing the precision of the prior distribution by a factor of ten for either the action or the conceptual path in mediation analysis. Power generally increases with increases in precision but there are many sample size and parameter value combinations where precision increases by a factor of 10 do not lead to substantial increases in power.
ContributorsMiocevic, Milica (Author) / Mackinnon, David P. (Thesis advisor) / Levy, Roy (Committee member) / West, Stephen G. (Committee member) / Enders, Craig (Committee member) / Arizona State University (Publisher)
Created2014
Description
Many methodological approaches have been utilized to predict student retention and persistence over the years, yet few have utilized a Bayesian framework. It is believed this is due in part to the absence of an established process for guiding educational researchers reared in a frequentist perspective into the realms of Bayesian analysis and educational data mining. The current study aimed to address this by providing a model-building process for developing a Bayesian network (BN) that leveraged educational data mining, Bayesian analysis, and traditional iterative model-building techniques in order to predict whether community college students will stop out at the completion of each of their first six terms. The study utilized exploratory and confirmatory techniques to reduce an initial pool of more than 50 potential predictor variables to a parsimonious final BN with only four predictor variables. The average in-sample classification accuracy rate for the model was 80% (Cohen's κ = 53%). The model was shown to be generalizable across samples with an average out-of-sample classification accuracy rate of 78% (Cohen's κ = 49%). The classification rates for the BN were also found to be superior to the classification rates produced by an analog frequentist discrete-time survival analysis model.
ContributorsArcuria, Philip (Author) / Levy, Roy (Thesis advisor) / Green, Samuel B (Committee member) / Thompson, Marilyn S (Committee member) / Arizona State University (Publisher)
Created2015
Description
This multiple-case study addresses the nature of the out-of-school musical engagements of four undergraduate students who were enrolled as jazz studies majors in a large school of music in the U.S. southwest. It concerns what they did musically when they were outside of school, why they did what they did, what experiences they said they learned from, and how their out-of-school engagements related to their in-school curriculum. Research on jazz education, informal learning practices in music, and the in-school and out-of-school experiences of students informed this study. Data were generated through observation, interviews, video blogs (vlogs), and SMS text messages.
Analysis of data revealed that participants engaged with music when outside of school by practicing, teaching, gigging, recording, playing music with others, attending live musical performances, socializing with other musicians, listening, and engaging with non-jazz musical styles (aside from listening). They engaged with music because of: 1) the love of music, 2) the desire for musical excellence, 3) financial considerations, 4) the aspiration to affect others positively with music, and 5) the connection with other musicians. Participants indicated that they learned by practicing, listening to recordings, attending live performances, playing paid engagements, socializing, teaching, and reading. In-school and out-of-school experience and learning had substantial but not complete overlap.
The study implies that a balance between in-school and out-of-school musical experience may help undergraduate jazz studies students to maximize their overall musical learning. It also suggests that at least some jazz studies majors are fluent in a wide variety of music learning practices that make them versatile, flexible, and employable musicians. Further implications are provided for undergraduate jazz students as well as collegiate jazz educators, the music education profession, and schools of music. Additional implications concern future research and the characterization of jazz study in academia.
Analysis of data revealed that participants engaged with music when outside of school by practicing, teaching, gigging, recording, playing music with others, attending live musical performances, socializing with other musicians, listening, and engaging with non-jazz musical styles (aside from listening). They engaged with music because of: 1) the love of music, 2) the desire for musical excellence, 3) financial considerations, 4) the aspiration to affect others positively with music, and 5) the connection with other musicians. Participants indicated that they learned by practicing, listening to recordings, attending live performances, playing paid engagements, socializing, teaching, and reading. In-school and out-of-school experience and learning had substantial but not complete overlap.
The study implies that a balance between in-school and out-of-school musical experience may help undergraduate jazz studies students to maximize their overall musical learning. It also suggests that at least some jazz studies majors are fluent in a wide variety of music learning practices that make them versatile, flexible, and employable musicians. Further implications are provided for undergraduate jazz students as well as collegiate jazz educators, the music education profession, and schools of music. Additional implications concern future research and the characterization of jazz study in academia.
ContributorsLibman, Jeffrey B (Author) / Tobias, Evan (Thesis advisor) / Kocour, Michael (Committee member) / Schmidt, Margaret (Committee member) / Solis, Theodore (Committee member) / Stauffer, Sandra (Committee member) / Arizona State University (Publisher)
Created2014
ContributorsCarlisi, Daniel (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-07