Syllabus
Course Title: Mathematics for Teaching – Problem Solving and Data Analysis
Course Number: MTHE 6780
Course Credit Hours: 3 credit hours
Prerequisites: Elementary teaching experience
Catalog Description:
This course will develop a firm problem-solving foundation. Using skills and strategies applied in mathematical contexts practicing teachers will learn to think, work with others, present solutions, and facilitate problem solving instruction in the classroom. This course will also provide practicing teachers a deeper understanding of probability and statistics content in the state core and instructional strategies to facilitate the instruction of this content.
Course Objectives:
During this course teachers will:
· Select appropriate strategies, solve challenging mathematical problems in groups and individually.
Suggested Texts:
Parker, Thomas H. and Baldridge, Scott J. (2005). Elementary Geometry for Teachers. Portland, OR: Sefton-Ash Publishers Chapter 10.
Ministry of Education, Singapore (1981). Primary Mathematics 1A-6A,Marshall Cavendish Education, 2003.
Johnson, K; Herr, T. & Kysh, J. (2004) Crossing the River with Dogs: Problem Solving for College Students, Key Curriculum Press (rites to book have been sold)
References:
Course Coverage:
1. Problem Solving Topics:
· Draw a diagram
· Make a systematic list
· Eliminate possibilities
· Use matrix logic
· Look for a pattern
· Guess and check
· Identify sub-problems
· Analyze the units
· Solve an easier related problem
· Create a physical representation
· Draw Venn diagrams
· Convert to algebra
· Evaluate finite differences
2. Data Analysis
Formulating appropriate questions for data analysis research
Tools for collecting and organizing data: (Tally marks, tables, pictographs, bar graphs, line graphs, frequency tables, line plots, stem-and-leaf plots, circle graphs, scatter plots, histograms, and box-and-whisker plots),
Measures of Central Tendency: what they are, when to use them, how to interpret (mean, median, and mode, including the impact of outliers),
Measures of Dispersion: what they are, when to use them, how to interpret them (range, variance, standard deviation, percentiles)
3. Probability
Concepts of Probability: (likely, unlikely, certain, impossible, sample space, experimental and theoretical, and recognition of probability as a value between 0 and 1)
Theoretical and Experimental Probabilities