Engineering dynamics is a fundamental sophomore-level course that is required for nearly all engineering students. As one of the most challenging courses for undergraduates, many students perform poorly or even fail because the dynamics course requires students to have not only solid mathematical skills but also a good understanding of fundamental concepts and principles in the field. A valid model for predicting student academic performance in engineering dynamics is helpful in designing and implementing pedagogical and instructional interventions to enhance teaching and learning in this critical course. The goal of this study was to develop a validated set of mathematical models to predict student academic performance in engineering dynamics. Data were collected from a total of 323 students enrolled in ENGR 2030 Engineering Dynamics at Utah State University for a period of four semesters. Six combinations of predictor variables that represent students’ prior achievement, prior domain knowledge, and learning progression were employed in modeling efforts. The predictor variables include X1 (cumulative GPA), X2~ X5 (three prerequisite courses), X6~ X8 (scores of three dynamics mid-term exams). Four mathematical modeling techniques, including multiple linear regression (MLR), multilayer perceptron (MLP) network, radial basis function (RBF) network, and support vector machine (SVM), were employed to develop 24 predictive models. The average prediction accuracy and the percentage of accurate predictions were employed as two criteria to evaluate and compare the prediction accuracy of the 24 models. The results from this study show that no matter which modeling techniques are used, those using X1 ~X6, X1 ~X7, and X1 ~X8 as predictor variables are always ranked as the top three best-performing models. However, the models using X1 ~X6 as predictor variables are the most useful because they not only yield accurate prediction accuracy, but also leave sufficient time for the instructor to implement educational interventions. The results from this study also show that RBF network models and support vector machine models have better generalizability than MLR models and MLP network models. The implications of the research findings, the limitation of this research, and the future work are discussed at the end of this dissertation.

Enrollment in online courses has outpaced overall university enrollment for the past several years. The growth of online courses does not appear to be slowing. The purpose of this study was to examine the origins of online education at Tarleton State University, to compare course completion and student academic performance between online and traditional courses, and to develop a predictive model for students’ successful completion of online courses. Archival data from the Tarleton student records system was collected using the Structured Query Language. Descriptive statistics were used to analyze student characteristics. Chi-square analysis was used to determine if significant differences existed between students enrolled in online and traditional courses when comparing course completion and academic performance. Analysis found significant differences existed in both course completion and academic performance for students enrolled in online vs. traditional courses. Additional analysis indicated significant differences existed in course completion by course discipline. A predictive model was created using binary logistic regression and included the predictor variables age, student classification, term course load, and cumulative GPA. The final model correctly predicted successful completion of 85.5 percent of all cases.

This study aims at looking deeper into school-based leadership and teacher leadership in particular. The starting point of any line of thought is to be found in the claim that there is a positive correlation between teacher leadership and student academic performance.When searching the curriculum for the non-compulsory school system in Sweden, Lpf94,for its position on school-based leadership, the only item that is found on the subjectrefers to principal leadership. I therefore chose to perform interviews with a number ofhigh-school teachers, to attain a complementary image of how they perceive that they, as teachers, practice leadership on a daily basis. The results show that they all feel that their professional role entails a leader role, but the analysis shows that how they practice leadership can be recognized in slightly different ways.

En esta tesis, se utilizan t ecnicas matem atico-epidemiol ogicas para modelar el rendimiento acad emico en Espa~na (prestando especial atenci on en el fracaso escolar) para comprender mejor los mecanismos detr as de esta importante cuesti on, as como para predecir c omo evolucionar an los resultados acad emicos en el Bachillerato espa~nol en los pr oximos a~nos. El nivel educativo de Bachillerato en Espa~na est a formado por los dos ultimos cursos antes de acceder a la universidad o al mercado de trabajo y corresponde a los estudiantes de 16 18 a~nos. Este nivel educativo es muy importante para la formaci on de los estudiantes ya que representa un periodo en el que deber an tomar importantes decisiones sobre el futuro acad emico y profesional. En primer lugar, en el Cap tulo 2, se presenta un modelo determinista donde se analiza el rendimiento acad emico asumiendo que la actitud negativa de los alumnos de Bachillerato puede ser debida a su comportamiento aut onomo y la in uencia de compa~neros con malos resultados acad emicos. Luego, en el Cap tulo 3, se mejora el modelo basado en la idea de que no s olo los malos h abitos acad emicos se transmiten socialmente sino tambi en los buenos h abitos de estudio. Adem as, descomponemos los par ametros de transmisi on de h abitos acad emicos con el n de analizar con m as detalle qu e grupos de estudiantes son m as susceptibles a ser in uenciados por compa~neros con buenos o malos h abitos acad emicos. El abandono escolar tambi en han sido incluido en este modelo. El enfoque adoptado permite proporcionar predicciones deterministas y con intervalos de con anza de la evoluci on del rendimiento escolar (incluyendo las tasas de abandono) en Bachillerato en Espa~na en los pr oximos a~nos. Este enfoque, adem as, nos permite modelar el rendimiento acad emico en otros niveles educativos del sistema acad emico espa~nol o de fuera de Espa~na tal y como se muestra en el Cap tulo 4, donde el modelo se aplica satisfactoriamente al sistema acad emico actual de la regi on alemana de Renania del Norte-Westfalia. Para concluir esta tesis, proporcionamos una estimaci on de los costes relacionados con el rendimiento acad emico espa~nol basado en nuestras predicciones. Esta estimaci on representa la inversi on en Bachillerato por parte del Gobierno espa~nol y las familias en los pr oximos a~nos, con especial atenci on en los grupos de estudiantes que no promocionan y abandonan en los diferentes cursos acad emicos. / In this dissertation, we use epidemiologic-mathematical techniques to model the academic performance in Spain (paying special attention on the academic underachievement) to understand better the mechanisms behind this important issue as well as to predict how academic results will evolve in the Spanish Bachillerato over the next few years. The Spanish Bachillerato educational level is made up of the last courses before accessing to the university or to the work market and corresponds to students of 16¿18 years old. This educational level is a milestone in the career training of students because it represents a period to make important decisions about academic and professional future. In a rst step, in the Chapter 2 we will present a deterministic model where academic performance is analyzed assuming the negative attitude of Bachillerato students may be due to their autonomous behavior and the in uence of classmates with bad academic results. Then, in the Chapter 3, the model is improved based on the idea that not only the bad academic habits are socially transmitted but also the good study habits. Besides, we decompose the transmission academic habits into good and bad academic habits, in order to analyze with more detail which group of students are more susceptible to be in uenced by good or bad academic students. The consideration of quantifying the abandon rates is also a new issue dealt with in it. The adopted approach allow to provide both punctual and con dence intervals predictions to the evolution of academic performance (including the abandon rates) in Bachillerato in Spain over the next few years. The adopted approach allows us to model academic performance in academic levels other than Bachillerato and/or beyond the Spanish academic system. This issue is assessed in Chapter 4, where the model is satisfactorily applied to the current academic system of the German region of North Rhine-Westphalia. To conclude this dissertation, we provide an estimation of the cost related to the Spanish academic underachievement based on our predictions. This estimation represents the investment in the Spanish Bachillerato from the Spanish Government and families over the next few years, paying special attention on the groups of students who do not promote and abandon during their corresponding academic year. / Sánchez Sánchez, A. (2013). Modelling the evolution dynamics of the academic performance in high school in Spain. Probabilistic predictions of future trends and their economical consequences [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/32280