This study involved examination of the processes employed in tailoring fourth-grade reading instruction to increase levels of student motivation. A participatory action research approach was utilized to design and conduct reading instruction that fourth-grade students perceived to be motivating. The reading instructional program was designed using the five key components of the MUSIC Model of Academic Motivation (eMpowerment, Usefulness, Success, Interest, and Caring; Jones, 2009) and was implemented daily in an elementary classroom. Students were interviewed to identify their perspectives about the reading program and student input was used by the teacher to inform instruction and adapt the program to increase motivation. The fourth-grade students in this study were motivated to read for a variety of reasons and enjoyed participating in numerous reading activities. The common theme among all of these motivating activities was personal choice or empowerment, such as selecting a book or choosing a topic of interest. When students made suggestions for improving reading instruction, most of the suggestions related to having the ability to make more meaningful choices. After the teacher implemented the suggestions and changes, the inventory scores for all five components of the MUSIC Model increased, with empowerment increasing slightly more than other components. Findings indicated that it was particularly important that students' voices were valued. The teacher finely honed the reading program based upon students' needs and ideas, resulting in increased reading motivation and achievement during a time when the motivation and achievement of fourth-grade students tends to decline. / Ph. D.

This dissertation examined the differences in group mean scores of traditional and pilot groups on the students' motivational beliefs and their intention to pursue majors and careers in engineering. The difference between the two groups was in terms of instruction techniques used. The instructional techniques used for the traditional group was that of traditional engineering design (TED), while the technique used for the pilot group had more features of an active learning approach. Further, it tested the tenability of the domain identification model. The domain identification model was used to understand students' decision-making processes in committing to engineering majors and engineering careers. The data for this study was collected via online survey from first-year engineering students enrolled in an introductory engineering course at a research-intensive university located in southeastern US. The sample sizes of the traditional group and pilot group at the beginning of the semester were 875 and 188, respectively. The sample sizes of the traditional group and pilot group at the end of the semester were 812 and 242, respectively. The mean differences between the two groups were computed using t-tests via SPSS version 22.0. The causality hypothesized among variables in the domain identification model were tested using structural equation modeling (SEM) techniques. The measurement and structural models were estimated using LISREL version 9.1. This study followed the two-step SEM approach that Anderson and Gerbing (1988) suggested. A measurement model with an acceptable fit to the data was obtained followed by an estimation and evaluation of structural models. All the independent sample t-tests were not statistically significant indicating that the mean scores of students in the two groups did not differ significantly on any of the motivational and intention variables. The hypothesized measurement and structural models provided a good fit to the data. A few post-hoc revisions were made to the models. This study brought empirical evidence that the domain identification model can be used to understand students' major-and career-decision making processes. Engineering identification was a better predictor of major intention and career intention compared to engineering program utility, engineering program belonging, and engineering program expectancy. / Ph. D.

This dissertation examined the extent to which pre-high school students' motivation-related perceptions of their science class affected their science identification, which sequentially affected their future science-related career goals. The MUSIC® Model of Motivation (Jones, 2009, 2018) includes five components (i.e., eMpowerment, Usefulness, Success, Interest, and Caring) and is designed to help teachers design instruction to promote students' motivation. Domain identification (Osborne and Jones, 2011) is a concept closely related to students' motivation and academic outcomes. In this study, data was collected from 311 pre-high school students and Structural Equation Modeling (SEM) analysis was conducted to test the structure pattern among the MUSIC model components, science identification, and science-related career goals. Results indicate that with three of the MUSIC model components (i.e., usefulness, success, and interest) significantly related to students' science identification, students' science identification was highly correlated to their science career goals. Moreover, this study demonstrated the structure patterns among the MUSIC model components and science identification varied by gender by conducting multi-group SEM analyses for a separate female sample (N = 161) and male sample (N = 150). Consistently, students' science identification was a strong predictor of their science career goals in both female and male groups. These findings are important for STEM educators because they indicate that it may be possible for teachers to impact students' science identification and career goals by focusing on students' perceptions of the MUSIC model components in science class. Moreover, these results contribute to the study of the large gender gap in STEM careers. Teachers can focus on specific teaching strategies and help female students develop their science identification in ways that lead to their long-term science-related career goals. / Ph. D.

Communicative Language Teaching (CLT) is regarded as an effective approach to teaching foreign languages because it focuses on students' engagement and communicative competence. In the realm of educational psychology, researchers have identified many teaching strategies that can have positive effects on students' motivation and engagement. Jones (2009, 2015) synthesized these strategies and created the MUSIC® Model of Motivation. MUSIC is an acronym for the strategies related to eMpowerment, Usefulness, Success, Interest and Caring. The MUSIC model can be used to help instructors to redesign their instruction to motivate and engage their students in learning activities. The purpose of this research was to examine the effectiveness of incorporating the MUSIC model strategies into CLT classes at a university in China. I used a self-report survey comprised of seven subscales (representing five motivation-related variables and two engagement variables) to collect data on students' course perceptions and their engagement in a college English class. The participants were first year college students at a university in central China (n = 259). Independent samples t-tests, regression, and correlation were used to answer the following two research questions: 1. Is there a difference in students' motivation and achievement in traditional lecture classes versus CLT classes that incorporate MUSIC model strategies? 2. To what extent do students' MUSIC model perceptions relate to their engagement and achievement? The results indicated that there was a significant difference between the traditional lecture class and the CLT classes incorporating MUSIC model strategies. Students in CLT classes perceived more control in the class, found the course to be more useful, were more interested, and perceived more caring from their teacher. As a result, students in CLT classes put forth more effort and achieved higher scores on a standardized English test. In addition, the results revealed that students' MUSIC model perceptions predicted their engagement both in CLT classes and the traditional classes. However, the results showed that the MUSIC model components did not significantly predict student achievement. These findings suggest that the MUSIC model and the MUSIC Inventory are ideal tools for Chinese college English teachers to use when they design instruction. / Ph. D.

Student motivation in medical education courses is essential for the development of life-long medical knowledge. Researchers have demonstrated that student learning in anatomy courses, fundamental to students' future medical learning, has suboptimal long-term outcomes. The purpose of this study was to investigate how medical students' motivation-related perceptions and course effort were different during the academic year through varied course content and elements of instruction. The study was guided by the MUSIC Model of Motivation theoretical framework and nested in the pragmatic paradigm. First-year medical students enrolled at a small, public allopathic medical school in the southeastern United States were surveyed and interviewed regarding their course perceptions. Quantitative data from 18 students and qualitative data from 14 students indicated that students' motivation-related perceptions and effort do vary over different course content and elements of instruction. Students consistently reported lower motivation-related perceptions and effort for prerecorded lectures, whereas they reported more positive motivation-related perceptions and effort for cadaver dissection. Results also indicated variability in motivation-related perceptions and effort among specific block content areas (e.g., musculoskeletal, cardiovascular, abdominopelvic). Study findings resulted in a variety of suggestions for course instructors on how anatomy course design and instructional practices could be intentionally adjusted in the interest of fostering student motivation and engagement. Implications for course design and instruction included general course guidance (e.g., clinical relevance, clear and broad understanding of course usefulness), prerecorded lecture recommendations (e.g., catalogued for easy reference, short and focused, effective use of visual and verbal elements), and cadaver lab instruction guidance (e.g., faculty and upper-level student engagement, student preparation expectations). / Doctor of Philosophy / The purpose of this study was to investigate how medical students' motivation-related perceptions and course effort were different during the academic year through varied course content and elements of instruction. The study was guided by the MUSIC Model of Motivation which is a resource course instructors can use to develop their courses in ways that support students' motivation and engagement. The MUSIC Model is an acronym (i.e., eMpowerment, Usefulness, Success, Interest, and Caring) and each letter represents one of five categories of strategies that teachers can use to motivate students. Instructors who use strategies in these categories can improve student motivation which can help encourage students to engage in their learning. First-year medical students enrolled in an anatomy course at a small, public medical school in the southeastern United States were surveyed and interviewed regarding their perceptions of the anatomy course. Information gathered from this study indicated that students' motivation and engagement vary over different course content and elements of instruction. Students consistently reported lower motivation-related perceptions and effort for prerecorded lectures. Students reported more positive motivation-related perceptions and effort for cadaver dissection. Results also indicated unevenness in motivation-related perceptions and effort among specific block content areas (e.g., musculoskeletal, cardiovascular, abdominopelvic). This study offered a variety of suggestions for course instructors on how anatomy course design and instructional practices could be intentionally adjusted in the interest of fostering student motivation and engagement.

The adsorption behavior of silicic acid and arsenite alone and competitively on goethite over a broad pH range (3-11) at environmentally relevant concentrations was investigated utilizing pH adsorption data and zeta potential measurements. Both addition scenarios (Si before As(III) and As(III) before Si) were examined. The results of the adsorption experiments and zeta potential measurements were then used to model the single ion and competitive ion adsorption on goethite with the CD-MUSIC model implemented in the FITEQL 4.0 computer program. Silicic acid adsorption was reduced by the presence of arsenite for all but one of the adsorption scenarios examined, while in contrast silicic acid had little effect upon arsenite adsorption. However, the presence of silicic acid, regardless of the addition scenario, dramatically increased the arsenite equilibrium solution concentration over the entire pH range investigated. The CD-MUSIC model was able to predict the single ion adsorption behavior of silicic acid and arsenite on goethite. The modeled zeta potential data provided further evidence of the CD-MUSIC model's ability to describe the single anion adsorption on goethite. Our model was also able to collectively describe adsorption and zeta potential data for the low Si-arsenite adsorption scenario quite well however, our model under-predicted silicic acid adsorption for the high Si-arsenite competitive scenario. / Master of Science

This work presents a novel approach for the design of a predictive model of music that can be used to analyze and generate musical material that is highly context dependent. The system is based on an approach known as n-gram modeling, often used in language processing and speech recognition algorithms, implemented initially upon a framework of Variable-Length Markov Models (VLMMs) and then extended to Variable-Length Hidden Markov Models (VLHMMs). The system brings together various principles like escape probabilities, smoothing schemes and uses multiple representations of the data stream to construct a multiple viewpoints system that enables it to draw complex relationships between the different input n-grams, and use this information to provide a stronger prediction scheme. It is implemented as a MAX/MSP external in C++ and is intended to be a predictive framework that can be used to create generative music systems and educational and compositional tools for music. A formal quantitative evaluation scheme based on entropy of the predictions is used to evaluate the model in sequence prediction tasks on a database of tabla compositions. The results show good model performance for both the VLMM and the VLHMM while highlighting the expensive computational cost of higher-order VLHMMs.