Students Of Applied Mathematics Research Articles

Virtual Learning and Undergraduate Students’ Academic Achievement in Mathematics During Covid-19 Lockdown in Ibadan, Oyo State

This paper investigated Virtual Learning and Undergraduate Students’ Academic Achievement in Mathematics during Covid-19 Lockdown in Ibadan, Oyo State. The study adopted One-group pretest-posttest Quasi-Experimental design. The population for this study was two hundred and eighty (280) First-year students in the faculty of Basic Medical and Applied Science, Lead City University, Ibadan, Nigeria. Sample for the study comprised Fifty (50) students who participated in the virtual learning in Applied Mathematics coded MTH 112 during COVID-19 Lockdown. The instrument for the study was Forty (40) objective questions optioned A to D on Applied Mathematics Achievement Test (AMAT). The instrument was validated and tested for reliability with reliability coefficients of 0.71. Student t-test statistics was used to test the Hypotheses generated at 0.05 level of significance. Hypothesis one revealed a significant difference in the achievement of students in Applied Mathematics when exposed to virtual learning, t-calculated (21.328) was greater than t-table (1.985). Hence hypothesis one was rejected. Hypothesis two also revealed a significant difference in the achievement of male and female students in Applied Mathematics in favour of male students, t-calculated (20.050) was higher than t-table (2.011). This infers that the male students achieved better than female students in AMAT when exposed to virtual learning. Hence, hypothesis two was also rejected. The study concluded that, Virtual learning encourages students’ achievement in Applied Mathematics and recommended virtual learning to be adopted especially where physical classroom is constrained.

La eficiencia terminal de los alumnos de algunas licenciaturas y posgrados en ciencias

Este es un trabajo que se basa en datos de historiales académicos de los alumnos de las generaciones 2000-2008 de las licenciaturas de Matemáticas, Matemáticas Aplicadas, Física y Física Aplicada, que se imparten en la Facultad de Ciencias Físico Matemáticas (FCFM) de la Benemérita Universidad Autónoma de Puebla (BUAP) y una base de datos de los alumnos de las Maestría en Ciencias del Posgrado de la FCFM de la BUAP (Matemáticas y Física Aplicada). Aquí se recopilan varios resultados que se han modelado y presentado en algunas tesis de licenciatura en Matemáticas o Matemáticas Aplicadas. Por otro lado, para las Maestrías y Doctorados en Ciencias de la FCFM de la BUAP, se toman los periodos de 2003-2012 para las dos líneas en Matemáticas y Física Aplicada, respectivamente. La población de mujeres involucradas en los posgrados durante los primeros años es en general menos de la mitad de los inscritos, y se ve un relativo aumento en los últimos años. En particular, todos los alumnos de los Doctorado en Matemáticas y Física Aplicada están teniendo un tiempo muy similar para obtener el grado, aunque en general para todos los posgrados en los hombres es menor. Finalmente, observando la conducta terminal de las poblaciones, vemos que en las licenciaturas las mujeres en general terminan más que los hombres, aunque en los posgrados que revisamos, los hombres terminan en menos tiempo. De toda esta información, vemos un aumento relativo en la población de las mujeres en los posgrados, en las áreas de Matemáticas y Física Aplicada. El tiempo en que terminan en general, las mujeres se llevan más tiempo aunque en los últimos años se está pareciendo al de los hombres. Para el caso de los posgrados, todavía no contamos con trabajos de modelación estadística por no tener suficientes datos en las generaciones, pero sí mencionamos las evidencias descriptivas que nos permiten plantear conjeturas.

Graph Applications to Data Structures

This paper presents a topic on Graph theory and its application to data Structures which I consider basic and useful to students in APPLIED MATHEMATICS and ENGINEERING.This paper gives an elementary introduction of Graph theory and its application to data structures. Elements of Graph theory are indispensable in almost all computer Science areas .It can be used in Some areas such as syntactic analysis, fault detection, diagnosis in computers and minimal path problems. The computer representation and manipulation of graph are also discussed so that certain algorithms can be included .A major theme of this paper is to study Graph theory and its Application to data structures Furthermore I hope the students not only learn the course but also develop their analogy perceive, formulate and to solve mathematical programs Thus Graphs especially trees, binary trees are used widely in the representation of data structures this course one can develop mathematical maturity, ability to understand and create mathematical argumentsMethod of derivation is procedure given in the text books with necessary formulae and their application . Concepts and notations from discrete mathematics are useful in studying and describing objects and problems in branches of computer science, such as computer algorithms, programming languages.

APL tutorial in mathematical modelling

The software presented below is a computer tutorial in mathematical modeling. The term "Mathematical Modeling" does not have a precise definition. We use the term to imply problem description in mathematical terms and the use of mathematical tools to investigate the given problem. For example, by using differential equations it is possible to describe a vast variety of different phenomena in the areas of physics, biology, sociology, etc. Some types of differential equations can be solved analytically, others require numerical methods and a computer. So today's mathematical modeler should be prepared to use a computer as an accessory.There are a great number of software packages allowing mathematical models to be studied numerically as well as analytically. Among these packages are MatLab, MathCad, Maple, Mathematica and others. However, students of Applied Mathematics should not only know how to apply numerical methods but also understand their principles and the limits to their application. Therefore, any student class in Numerical Methods should include some coding of numerical methods by using a programming language.Classical programming languages are overburdened with ritual operations (data description, cycles, manual distribution of memory) to such an extent that after programming the numerical method very little time is left to investigate the method itself: its behavior with different parameters and in different sorts of problem. Moreover, the object known as a "program" in a classical programming language is something monolithic; there are very few useful operations defined over such objects. Therefore APL enjoys a considerable advantage over classical programming. It allows students to concentrate on the algorithm itself and not on the data description.But one faces some disadvantages when using APL. APL does not provide for alternative representations of numbers or for the creation of standalone executable modules.The tutorial presented below is a program having a Windows interface which lets students familiarize themselves with the Theory of Calculation and problem solving in connection with numerical methods or actual models.The tutorial consists of lectures, problems, hints and solutions, plus a library of numerical methods. But most importantly, when using this tutorial, students can solve problems in the actual tutorial environment, i.e. the APL session and the GRAN subsystem for interactive graph plotting are available for the student's use.The tutorial below is not up to commercial standards, but is intended only as an illustration of APL's capabilities as a teaching tool. Clearly, this tutorial could be adapted to a variety of disciplines and this is a course of action we hope to pursue. In accordance with APL's history, this tutorial is an individualized and personalized study-aid and not a product for mass consumption.