MathTrackX: Polynomials and Functions
Master essential mathematical concepts through a comprehensive study of polynomials, functions, and graphs. Perfect foundation for advanced math.
Master essential mathematical concepts through a comprehensive study of polynomials, functions, and graphs. Perfect foundation for advanced math.
This foundational mathematics course is part of the MathTrackX XSeries Program, designed to build a strong understanding of mathematical fundamentals. Students explore the core concept of functions, essential for advanced mathematics. The course covers polynomial algebra, real number sets, and graphing techniques. Led by experts from the University of Adelaide's School of Mathematics, participants develop crucial mathematical vocabulary and problem-solving skills through practical applications. The course emphasizes building confidence in mathematical functions while providing a solid foundation for more complex mathematical concepts.
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What you'll learn
Master the fundamentals of algebra and arithmetic operations
Understand and apply basic concepts of mathematical functions
Develop proficiency in graphing and analyzing polynomials
Learn essential vocabulary for working with real number sets
Gain confidence in mathematical problem-solving techniques
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 5 modules in this course
This comprehensive mathematics course focuses on fundamental concepts of polynomials, functions, and graphs. Students begin with basic mathematical vocabulary and progress through the algebra of numbers and polynomials. The curriculum covers essential topics including sets of real numbers, intervals on the real number line, and function concepts. Throughout the course, learners develop problem-solving skills and mathematical confidence through guided instruction and practical applications.
Numbers
Module 1
Linear functions and their graphs
Module 2
Polynomials and their graphs
Module 3
Functions and graphs
Module 4
Assessment
Module 5
Fee Structure
Instructors
7 Courses
Distinguished Mathematics Educator and Learning Innovation Expert
David Butler serves as Lecturer and Coordinator of the Maths Learning Centre and Writing Centre at the University of Adelaide, where he specializes in helping students develop effective mathematical learning strategies across all disciplines. His academic background combines pure mathematics, with a PhD in Finite Geometry, and educational expertise through a Graduate Diploma in Education. As a former high school mathematics teacher, he brings practical pedagogical experience to his university role. His innovative approach emphasizes the integration of play and artistic elements in mathematical education, making complex concepts more accessible to students. At the Maths Learning Centre, he focuses on developing students' mathematical thinking skills and confidence, working across diverse academic disciplines to support students in mastering course-specific mathematical concepts. His passion for mathematics education extends beyond the classroom through his active engagement in mathematical education communities and his development of creative learning resources.
5 Courses
A Pioneering Statistician Bridging Applied Mathematics and Forensic Science
Melissa Humphries serves as Senior Lecturer in Statistics at the University of Adelaide, where she combines her unique background as a former chef with expertise in statistical analysis and cognitive modeling. After completing her PhD in Statistics and Mathematical Psychology from the University of Tasmania in 2017, she has built an impressive career spanning teaching and research. Her work focuses on applied statistics across diverse fields including forensic science, defense, psychology, and wastewater analysis, with particular emphasis on developing tools that support expert decision-making. As a lecturer, she coordinates multiple courses including second-year undergraduate statistics and has helped develop innovative online learning units in Bayesian reasoning. Her teaching portfolio includes Data Literacy, Statistical Analysis and Modeling, and Research Methods and Statistics. Recently named a Superstar of STEM for 2023-24, she advocates for making academia more accessible while maintaining an active research program in Bayesian inference, stochastic processes, and large dataset management. Her expertise extends to analyzing spatially and temporally autocorrelated data, contributing to fields ranging from astrophysics to forensic anthropology, while her background in psychology enhances her ability to communicate complex technical concepts to diverse audiences.
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