Search

Introductory Analysis

This course covers the fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and the interchange of limit operations. It shows the utility of abstract concepts and teaches an understanding and construction of proofs. The topics to be covered include

limit of a sequence of real numbers, standard theorems on limits, bounded and monotonic sequences of real numbers, infinite series of real numbers, tests for convergence, power series, limit, continuity and differentiability of functions of one variable,  Rolle’s theorem, mean value theorems, Taylor’s theorem, definition and simple properties of the Riemann integral.

Course Code: 
MAT 303
No. of Credits: 
3
Level: 
Level 300
Course Semester: 
First Semester
Pre-requisite: 
MAT 201 and MAT 203
Select Programme(s): 
Mathematics
Mathematics-with-Business

Quantitative Research Methods in Science Education

This is the first of two courses in research methods aimed at providing opportunities for students to improve their research skills. The course will expose students to the theories that underpin the quantitative research paradigm. It aims at the development of the knowledge and skills of students to enable them conduct a variety of quantitative studies aimed at improving teaching and learning of science in schools and other educational settings. It is expected that at the end of the course students will write a research proposal for a study that could be the focus of their thesis. Topics to be covered include: Realism, subjectivism and the ‘paradigm wars’; Post-positivism, experiential realism and pragmatism; Sampling techniques; Various quantitative research designs, development of instruments, reliability and validity of instruments; Internal and external validity; Parametric statistics such as the t-test, one-way and two-way ANOVA, the F-distribution, correlation and simple regression analysis, used for hypothesis testing, will be applied in the course; Non parametric statistical tests such as, chi-square and the Mann-Whitney U-test will also be applied. The rationale for using these various statistics and the assumptions underlying their use will be a critical focus of this course. 

Course Code: 
ESC815
No. of Credits: 
3
Level: 
Level 800
Course Semester: 
First Semester
Select Programme(s): 
Science Education
Science Education

Instructional Technology in Science Education

Technological skill development is most effective when embedded in content instruction rather than mastering specific Information Communication Technology (ICT) tools in a vacuum.  This course is a shift of ICT teacher professional development towards science content-centric approaches which advocates teaching teachers how to teach with ICT tools to meet content learning goals rather than teaching teachers how to use the tool. The course will provide trainees’ opportunities to develop their Technological Pedagogical Content Knowledge (TPACK) and skills to design, enact and evaluate ICT-based lessons using a variety of ICT tools that support different teaching and learning strategies. Topics to be covered include: The use of Information Communication Technology (ICT) such as internet resources, Java applets, Multimedia and spreadsheet; Online Educational Platforms (e.g. MOOC); Professional Learning Networks (PLN); TPACK as a framework for effective ICT integration; ICT application in didactic science teaching approaches and inquiry -based constructivist teaching approaches; and the use of Web quest.

Course Code: 
ESC851
No. of Credits: 
3
Level: 
Level 800
Course Semester: 
First Semester
Select Programme(s): 
Science Education
Science Education

Contemporary Issues in Curriculum Studies in Science

This course is designed to expose students to contemporary issues in curriculum studies and development in science education. The opportunity will be given to students to engage in some of the current complicated discourses in curriculum development, implementation, supervision and evaluation. Topics to be covered include: Understanding Curriculum in the following contexts: as Historical Text, Political Text, and Institutionalized Text; Gender, sexuality, race and ethnicity in a scientific and diverse milieu; Utopian vision, democracy and the egalitarian ideal; A vision of curriculum in the postmodern era.

Course Code: 
ESC853
No. of Credits: 
3
Level: 
Level 800
Course Semester: 
First Semester
Select Programme(s): 
Science Education
Science Education

Philosophy of Science

Philosophy of Science offers a unique opportunity to study the foundations, practices, and culture of the sciences from a philosophical perspective. Students will study the philosophy of science from the ancient Greeks to the contemporary philosophers of science. The course will expose students to questions addressed by philosophy of science and epistemology. The course will examine various philosophies of science and their implications for the definition of science, the development of science, and the teaching and learning of science. In particular, the course will focus on philosophies such as logicism, intuitionism and formalism. Also, included are contemporary philosophies such as social constructivism and postmodern philosophies. Students will be required to relate the substantial issues in this course to their experience and practice.

Course Code: 
ESC811
Level: 
Level 800
Course Semester: 
First Semester
Select Programme(s): 
Science Education
Science Education

Introduction to Statistics

Not Published

Course Code: 
STA 102
No. of Credits: 
3
Level: 
Level 100
Course Semester: 
Second Semester
Select Programme(s): 
Mathematics and Statistics

Analytic Geometry & Calculus

Not Published

Course Code: 
MAT 102
No. of Credits: 
3
Level: 
Level 100
Course Semester: 
Second Semester
Select Programme(s): 
Mathematics
Mathematics and Statistics

Introduction to Probability

Not Published

Course Code: 
STA 101
No. of Credits: 
3
Level: 
Level 100
Course Semester: 
First Semester
Select Programme(s): 
Mathematics
Mathematics and Statistics

Algebra & Trigonometry

Not Published 

Course Code: 
MAT 101
No. of Credits: 
3
Level: 
Level 100
Course Semester: 
First Semester
Select Programme(s): 
Mathematics
Mathematics and Statistics
Degree Type: 
Bachelor of ScienceDepartment of Mathematics
Programme Duration: 
4 years (Standard Entry)
About Programme: 

Not Published

Career Opportunities: 

Objectives 

  • To produce graduates who can undertake research work that requires knowledge in both mathematics and statistics.

  • To produce graduates who can use mathematics and statistics as a tool to do research work in other disciplines such as sciences, business, government, health and economics.

  • To provide a solid foundation for students to pursue further specialised courses such as actuarial science, econometrics and operations research.

Entry Requirements: 

Not Published

Pages