This document provides an overview of the Grade 8 Mathematics Assessment for the Texas Essential Knowledge and Skills (TEKS) student curriculum. It is divided into 5 reporting categories covering various mathematics concepts. Each category lists the associated TEKS standards describing what students are expected to learn and be assessed on. These include topics like numbers and operations, patterns and algebra, geometry, measurement, probability, and statistics. Underlying processes and mathematical tools are also covered that apply to solving problems across various disciplines.
This document provides an overview of the STAAR Grade 7 Mathematics Assessment for Texas students. It outlines the 5 reporting categories assessed: Numbers, Operations, and Quantitative Reasoning; Patterns, Relationships, and Algebraic Reasoning; Geometry and Spatial Reasoning; Measurement; and Probability and Statistics. Each reporting category lists the essential knowledge and skills standards students are expected to master, identifying which are considered readiness or supporting standards.
This document summarizes the Grade 6 Mathematics Assessment for the Texas Essential Knowledge and Skills (TEKS) student curriculum. It outlines the five reporting categories assessed: 1) Numbers, Operations, and Quantitative Reasoning, 2) Patterns, Relationships, and Algebraic Reasoning, 3) Geometry and Spatial Reasoning, 4) Measurement, and 5) Probability and Statistics. Each category lists the specific skills and expectations students are required to demonstrate mastery of according to the TEKS. Underlying mathematical processes are also assessed across categories.
This document provides an overview of the Grade 5 Mathematics Assessment for the State of Texas Assessment of Academic Readiness (STAAR) exam. It outlines the five reporting categories assessed, including Numbers, Operations, and Quantitative Reasoning; Patterns, Relationships, and Algebraic Reasoning; Geometry and Spatial Reasoning; Measurement; and Probability and Statistics. Each reporting category lists the specific skills and expectations students will be evaluated on.
This document summarizes the content and skills assessed on the 4th grade STAAR Mathematics Assessment in Texas. It is divided into 5 reporting categories: 1) Numbers, operations, and quantitative reasoning, 2) Patterns, relationships, and algebraic reasoning, 3) Geometry and spatial reasoning, 4) Measurement, and 5) Probability and statistics. Each category lists the essential knowledge and skills students are expected to demonstrate in areas such as number sense, operations, patterns, geometry, measurement, and data analysis.
This document outlines the Texas Essential Knowledge and Skills (TEKS) standards for the Grade 3 Mathematics STAAR assessment administered in Fall 2010. It includes 5 reporting categories covering numbers, operations, patterns, geometry, measurement, probability, and statistics. It also lists underlying mathematical processes and tools incorporated into test questions.
This document provides the Texas Essential Knowledge and Skills (TEKS) for mathematics in middle school (grades 6-8). It outlines the key concepts and skills students should master in each grade level, including number operations, algebraic thinking, geometry, measurement, probability, statistics, and problem solving. The TEKS ensure students build foundational math understanding and make connections within and outside of mathematics.
The document discusses understanding the TEKS (Texas Essential Knowledge and Skills) standards to identify gaps in curriculum. It explains how to analyze specific TEKS objectives to determine the depth of thinking, content, and context of a lesson. Key aspects to identify include the cognitive verbs, concepts, and context based on the TEKS objective. Together this informs the design, content, and assessment of the lesson to ensure all parts of the TEKS are taught. Examples from a math TEKS on volume are provided to demonstrate this process.
The document provides information about changes being made to the Math section of the SAT. It discusses removing quantitative comparisons and focusing more on math reasoning and real-world problems. It outlines the specific math content areas that will be covered, including algebra, functions, geometry, statistics, and probability. It also describes the types of questions that will be asked, such as grid-in questions, and the use of calculators.
This document provides an overview of the STAAR Grade 7 Mathematics Assessment for Texas students. It outlines the 5 reporting categories assessed: Numbers, Operations, and Quantitative Reasoning; Patterns, Relationships, and Algebraic Reasoning; Geometry and Spatial Reasoning; Measurement; and Probability and Statistics. Each reporting category lists the essential knowledge and skills standards students are expected to master, identifying which are considered readiness or supporting standards.
This document summarizes the Grade 6 Mathematics Assessment for the Texas Essential Knowledge and Skills (TEKS) student curriculum. It outlines the five reporting categories assessed: 1) Numbers, Operations, and Quantitative Reasoning, 2) Patterns, Relationships, and Algebraic Reasoning, 3) Geometry and Spatial Reasoning, 4) Measurement, and 5) Probability and Statistics. Each category lists the specific skills and expectations students are required to demonstrate mastery of according to the TEKS. Underlying mathematical processes are also assessed across categories.
This document provides an overview of the Grade 5 Mathematics Assessment for the State of Texas Assessment of Academic Readiness (STAAR) exam. It outlines the five reporting categories assessed, including Numbers, Operations, and Quantitative Reasoning; Patterns, Relationships, and Algebraic Reasoning; Geometry and Spatial Reasoning; Measurement; and Probability and Statistics. Each reporting category lists the specific skills and expectations students will be evaluated on.
This document summarizes the content and skills assessed on the 4th grade STAAR Mathematics Assessment in Texas. It is divided into 5 reporting categories: 1) Numbers, operations, and quantitative reasoning, 2) Patterns, relationships, and algebraic reasoning, 3) Geometry and spatial reasoning, 4) Measurement, and 5) Probability and statistics. Each category lists the essential knowledge and skills students are expected to demonstrate in areas such as number sense, operations, patterns, geometry, measurement, and data analysis.
This document outlines the Texas Essential Knowledge and Skills (TEKS) standards for the Grade 3 Mathematics STAAR assessment administered in Fall 2010. It includes 5 reporting categories covering numbers, operations, patterns, geometry, measurement, probability, and statistics. It also lists underlying mathematical processes and tools incorporated into test questions.
This document provides the Texas Essential Knowledge and Skills (TEKS) for mathematics in middle school (grades 6-8). It outlines the key concepts and skills students should master in each grade level, including number operations, algebraic thinking, geometry, measurement, probability, statistics, and problem solving. The TEKS ensure students build foundational math understanding and make connections within and outside of mathematics.
The document discusses understanding the TEKS (Texas Essential Knowledge and Skills) standards to identify gaps in curriculum. It explains how to analyze specific TEKS objectives to determine the depth of thinking, content, and context of a lesson. Key aspects to identify include the cognitive verbs, concepts, and context based on the TEKS objective. Together this informs the design, content, and assessment of the lesson to ensure all parts of the TEKS are taught. Examples from a math TEKS on volume are provided to demonstrate this process.
The document provides information about changes being made to the Math section of the SAT. It discusses removing quantitative comparisons and focusing more on math reasoning and real-world problems. It outlines the specific math content areas that will be covered, including algebra, functions, geometry, statistics, and probability. It also describes the types of questions that will be asked, such as grid-in questions, and the use of calculators.
- The document provides information about a course on multivariate data analysis, including the lecturer, timetable, textbooks, and course contents.
- The course will cover topics such as data analysis basics, principal components analysis, factor analysis, discriminant analysis, cluster analysis, and canonical correlation analysis.
- Assessment will be based on the syllabus. Textbooks, online tools, lecture slides, and data files will provide additional resources.
This document introduces materials to help write assessment items for the Smarter Balanced mathematics tests, including the Common Core State Standards, Content Specifications, and Item Specifications. It defines the Depth of Knowledge framework and describes how the standards and specifications are structured. Sample items are provided at different Depth of Knowledge levels to illustrate cognitive complexity. The Content Specifications outline the claims and targets assessed at each grade and provide a cognitive rigor matrix.
This document discusses strategies for differentiated instruction in mathematics. It defines differentiation as modifying tasks to fit students' ability levels, interests, and learning styles. The goals are to provide engaging math activities for all students and define several differentiation strategies with examples aligned to Common Core standards. Teachers will work in groups to create mathematical tasks with at least two modifications to differentiate instruction and consider strategies for differentiating assessment.
The document discusses how mathematics is often compartmentalized into distinct subject areas that students struggle to connect. It then provides details on analytic geometry, including how it connects algebra and geometry by using algebraic thinking to aid geometric understanding. Finally, it discusses various connections between algebra and geometry, such as how geometric concepts have algebraic counterparts and how algebraic and geometric results can be demonstrated in both domains.
This document analyzes students' performance in two engineering mathematics courses: Vector Calculus (VC) and Differential Equations (DE). Data was collected from 205 students across 4 departments. Statistical analysis using paired t-tests and Pearson correlation found a significant positive linear relationship between the courses. Students performed better in DE compared to VC, with higher average grades and fewer low grades. The topics covered in VC, such as integration and differentiation, provide important foundations for learning DE.
This document outlines a mathematics unit plan for teaching numbers and number sense in 7th grade. It includes 4 units that cover key concepts and skills in mathematics. The units are on numbers and number sense, measurement, patterns and algebra, and geometry. Each unit lists the essential and focusing questions, key knowledge and skills, and a sample performance task for assessing student understanding. The performance tasks are authentic scenarios requiring students to apply their mathematical learning.
Unit 7 mathemetical calculations for sciencemrrayner
This unit introduces learners to mathematical tools used in science disciplines. It covers algebraic techniques, trigonometry, and calculus. Learners will use these concepts to solve scientific problems involving topics like chemical bonding, electricity, voice recognition in forensics, and microbiological growth studies. The unit consists of three tasks assessing learners' abilities in these areas: Task 1 focuses on algebra with problems involving logarithms, indices, and equations; Task 2 involves circular measure, trigonometry, and real-life applications; Task 3 has learners applying calculus to problems regarding motion and rates of change. Completing the tasks successfully demonstrates learners' competency in using mathematical concepts to address scientific issues.
The document provides an introduction to machine learning techniques for category representation, outlining topics like clustering, classification, dimensionality reduction, and density estimation. It discusses supervised, unsupervised, and semi-supervised learning approaches and how to evaluate models using techniques like cross-validation to avoid overfitting. The goal of the course is to introduce common machine learning algorithms used in object recognition systems.
A Novel Bayes Factor for Inverse Model Selection Problem based on Inverse Ref...inventionjournals
Statistical model selection problem can be divided into two broad categories based on Forward and Inverse problem. Compared to a wealthy of literature available for Forward model selection, there are very few methods applicable for Inverse model selection context. In this article we propose a novel Bayes factor for model selection in Bayesian Inverse Problem context. The proposed Bayes Factor is specially designed for Inverse problem with the help of Inverse Reference Distribution (IRD). We will discuss our proposal from decision theoretic perspective.
This document discusses classification and prediction in machine learning. It defines classification as predicting categorical class labels, while prediction models continuous values. The key steps of classification are constructing a model from a training set and using the model to classify new data. Decision trees and rule-based classifiers are described as common classification methods. Attribute selection measures like information gain and gini index are explained for decision tree induction. The document also covers issues in data preparation and model evaluation for classification tasks.
This document discusses recommendation systems and topic modeling for documents using machine learning techniques. It begins by introducing recommendation systems and different types of recommendation literature, including item similarity, collaborative filtering, and hierarchical models. It then discusses bringing in user choice data and different collaborative filtering approaches like k-nearest neighbor prediction and matrix factorization. The document also covers topic modeling, including latent Dirichlet allocation, and how topic models can be combined with user choice models. It concludes by discussing challenges in causal inference when using machine learning.
(OSTICON 2015 Presentation by Davina Kaiser, CIS Texas Joint Venture) ~ The Food Challenge competition is a contest that allows students to demonstrate their culinary knowledge and skills. Using a set of predetermined ingredients provided, teams must develop a recipe and prepare the dish within a 40-minute timeframe. Teams then make a presentation explaining the preparation steps they took, serving size of their dish, food safety steps that were followed, nutritional value of the products used and the cost per serving of the dish. Come and learn more and even receive a free lesson plan and several handout resources.
The document describes the Spanish mathematics curriculum for secondary school students aged 12-16. It is divided into four years (ESO 1-4). The curriculum covers topics in numbers, algebra, geometry, functions/graphs, statistics, and probability. In the later years (ESO 3-4), students can choose between Option A (terminal math) or Option B (preparing for further math study). Both options cover the same core topics in greater depth and complexity each year.
The document provides a summary of various machine learning algorithms and their key features:
- K-nearest neighbors is interpretable, handles small data well but not noise, with no automatic feature learning. Prediction and training are fast.
- Linear regression is interpretable, handles small data and irrelevant features well, with fast prediction and training but requires feature scaling.
- Decision trees are somewhat interpretable with average accuracy, handling small data and irrelevant features depending on algorithm. Prediction and training speed varies by algorithm.
- Random forests have less interpretability than decision trees but higher accuracy, handling small data and noise better depending on settings. Prediction and training speed varies.
- Neural networks generally have the lowest interpretability but can automatically
The document describes the mathematics curriculum for 16-18 year old students in Spain. It is divided into 4 sections: Mathematics I, Mathematics II, Applied Mathematics I, and Applied Mathematics II. The courses cover topics such as algebra, geometry, analysis, statistics, probability, matrices, and functions. Students can choose either science and technology or social studies itineraries.
This document summarizes an intermediate statistics course covering generalized linear techniques and regression analysis. The course aims to help students become intelligent data consumers and interpreters. Key topics include simple and multiple regression, analysis of variance, assumptions of regression, and outputs from the statistical software SPSS. Generalized least squares models seek to minimize differences between observed and calculated data. Regression allows analyzing the impact of predictor variables on outcomes.
The document provides information about the 4th grade New York State Math Assessment, including:
- The assessment will take place from May 6th to May 13th, with make-up dates from May 9th to 13th.
- The test format includes multiple choice, short response, and extended response questions.
- The test will assess students' math skills across 7 key ideas: mathematical reasoning, number and numeration, operations, modeling and representation, measurement, uncertainty, and patterns and functions.
- Student work will be sent to the state to be scanned and scored using a 2-point or 3-point rubric.
This document provides an overview of classification in machine learning. It discusses supervised learning and the classification process. It describes several common classification algorithms including k-nearest neighbors, Naive Bayes, decision trees, and support vector machines. It also covers performance evaluation metrics like accuracy, precision and recall. The document uses examples to illustrate classification tasks and the training and testing process in supervised learning.
Machine Learning: Foundations Course Number 0368403401butest
This machine learning course will cover theoretical and practical machine learning concepts. It will include 4 homework assignments and programming in Matlab. Lectures will be supplemented by student-submitted class notes in LaTeX. Topics will include learning approaches like storage and retrieval, rule learning, and flexible model estimation, as well as applications in areas like control, medical diagnosis, and web search. A final exam format has not been determined yet.
This document outlines an assessment for students to measure work done by gravity on weights. It provides criteria for students to correctly collect and present data, interpret results using scientific reasoning, and discuss the validity of hypotheses and methods. The assessment involves lifting and pulling objects of different weights over set distances, measuring the force applied, and calculating work done using the formula Work = Force x Distance.
This document provides an overview of the reporting categories and standards assessed on the STAAR Geometry Assessment given by the Texas Education Agency. The assessment covers 5 reporting categories: Geometric Structure, Geometric Patterns and Representations, Dimensionality and the Geometry of Location, Congruence and the Geometry of Size, and Similarity and the Geometry of Shape. Each category lists the essential knowledge and skills standards students are expected to demonstrate mastery of on the test.
This document provides an overview of the 2010 STAAR Algebra I Assessment for Texas students. It outlines the 5 reporting categories assessed: 1) Functional Relationships, 2) Properties and Attributes of Functions, 3) Linear Functions, 4) Linear Equations and Inequalities, and 5) Quadratic and Other Nonlinear Functions. Each category lists the specific Texas Essential Knowledge and Skills standards assessed and provides a brief description of the concepts covered.
- The document provides information about a course on multivariate data analysis, including the lecturer, timetable, textbooks, and course contents.
- The course will cover topics such as data analysis basics, principal components analysis, factor analysis, discriminant analysis, cluster analysis, and canonical correlation analysis.
- Assessment will be based on the syllabus. Textbooks, online tools, lecture slides, and data files will provide additional resources.
This document introduces materials to help write assessment items for the Smarter Balanced mathematics tests, including the Common Core State Standards, Content Specifications, and Item Specifications. It defines the Depth of Knowledge framework and describes how the standards and specifications are structured. Sample items are provided at different Depth of Knowledge levels to illustrate cognitive complexity. The Content Specifications outline the claims and targets assessed at each grade and provide a cognitive rigor matrix.
This document discusses strategies for differentiated instruction in mathematics. It defines differentiation as modifying tasks to fit students' ability levels, interests, and learning styles. The goals are to provide engaging math activities for all students and define several differentiation strategies with examples aligned to Common Core standards. Teachers will work in groups to create mathematical tasks with at least two modifications to differentiate instruction and consider strategies for differentiating assessment.
The document discusses how mathematics is often compartmentalized into distinct subject areas that students struggle to connect. It then provides details on analytic geometry, including how it connects algebra and geometry by using algebraic thinking to aid geometric understanding. Finally, it discusses various connections between algebra and geometry, such as how geometric concepts have algebraic counterparts and how algebraic and geometric results can be demonstrated in both domains.
This document analyzes students' performance in two engineering mathematics courses: Vector Calculus (VC) and Differential Equations (DE). Data was collected from 205 students across 4 departments. Statistical analysis using paired t-tests and Pearson correlation found a significant positive linear relationship between the courses. Students performed better in DE compared to VC, with higher average grades and fewer low grades. The topics covered in VC, such as integration and differentiation, provide important foundations for learning DE.
This document outlines a mathematics unit plan for teaching numbers and number sense in 7th grade. It includes 4 units that cover key concepts and skills in mathematics. The units are on numbers and number sense, measurement, patterns and algebra, and geometry. Each unit lists the essential and focusing questions, key knowledge and skills, and a sample performance task for assessing student understanding. The performance tasks are authentic scenarios requiring students to apply their mathematical learning.
Unit 7 mathemetical calculations for sciencemrrayner
This unit introduces learners to mathematical tools used in science disciplines. It covers algebraic techniques, trigonometry, and calculus. Learners will use these concepts to solve scientific problems involving topics like chemical bonding, electricity, voice recognition in forensics, and microbiological growth studies. The unit consists of three tasks assessing learners' abilities in these areas: Task 1 focuses on algebra with problems involving logarithms, indices, and equations; Task 2 involves circular measure, trigonometry, and real-life applications; Task 3 has learners applying calculus to problems regarding motion and rates of change. Completing the tasks successfully demonstrates learners' competency in using mathematical concepts to address scientific issues.
The document provides an introduction to machine learning techniques for category representation, outlining topics like clustering, classification, dimensionality reduction, and density estimation. It discusses supervised, unsupervised, and semi-supervised learning approaches and how to evaluate models using techniques like cross-validation to avoid overfitting. The goal of the course is to introduce common machine learning algorithms used in object recognition systems.
A Novel Bayes Factor for Inverse Model Selection Problem based on Inverse Ref...inventionjournals
Statistical model selection problem can be divided into two broad categories based on Forward and Inverse problem. Compared to a wealthy of literature available for Forward model selection, there are very few methods applicable for Inverse model selection context. In this article we propose a novel Bayes factor for model selection in Bayesian Inverse Problem context. The proposed Bayes Factor is specially designed for Inverse problem with the help of Inverse Reference Distribution (IRD). We will discuss our proposal from decision theoretic perspective.
This document discusses classification and prediction in machine learning. It defines classification as predicting categorical class labels, while prediction models continuous values. The key steps of classification are constructing a model from a training set and using the model to classify new data. Decision trees and rule-based classifiers are described as common classification methods. Attribute selection measures like information gain and gini index are explained for decision tree induction. The document also covers issues in data preparation and model evaluation for classification tasks.
This document discusses recommendation systems and topic modeling for documents using machine learning techniques. It begins by introducing recommendation systems and different types of recommendation literature, including item similarity, collaborative filtering, and hierarchical models. It then discusses bringing in user choice data and different collaborative filtering approaches like k-nearest neighbor prediction and matrix factorization. The document also covers topic modeling, including latent Dirichlet allocation, and how topic models can be combined with user choice models. It concludes by discussing challenges in causal inference when using machine learning.
(OSTICON 2015 Presentation by Davina Kaiser, CIS Texas Joint Venture) ~ The Food Challenge competition is a contest that allows students to demonstrate their culinary knowledge and skills. Using a set of predetermined ingredients provided, teams must develop a recipe and prepare the dish within a 40-minute timeframe. Teams then make a presentation explaining the preparation steps they took, serving size of their dish, food safety steps that were followed, nutritional value of the products used and the cost per serving of the dish. Come and learn more and even receive a free lesson plan and several handout resources.
The document describes the Spanish mathematics curriculum for secondary school students aged 12-16. It is divided into four years (ESO 1-4). The curriculum covers topics in numbers, algebra, geometry, functions/graphs, statistics, and probability. In the later years (ESO 3-4), students can choose between Option A (terminal math) or Option B (preparing for further math study). Both options cover the same core topics in greater depth and complexity each year.
The document provides a summary of various machine learning algorithms and their key features:
- K-nearest neighbors is interpretable, handles small data well but not noise, with no automatic feature learning. Prediction and training are fast.
- Linear regression is interpretable, handles small data and irrelevant features well, with fast prediction and training but requires feature scaling.
- Decision trees are somewhat interpretable with average accuracy, handling small data and irrelevant features depending on algorithm. Prediction and training speed varies by algorithm.
- Random forests have less interpretability than decision trees but higher accuracy, handling small data and noise better depending on settings. Prediction and training speed varies.
- Neural networks generally have the lowest interpretability but can automatically
The document describes the mathematics curriculum for 16-18 year old students in Spain. It is divided into 4 sections: Mathematics I, Mathematics II, Applied Mathematics I, and Applied Mathematics II. The courses cover topics such as algebra, geometry, analysis, statistics, probability, matrices, and functions. Students can choose either science and technology or social studies itineraries.
This document summarizes an intermediate statistics course covering generalized linear techniques and regression analysis. The course aims to help students become intelligent data consumers and interpreters. Key topics include simple and multiple regression, analysis of variance, assumptions of regression, and outputs from the statistical software SPSS. Generalized least squares models seek to minimize differences between observed and calculated data. Regression allows analyzing the impact of predictor variables on outcomes.
The document provides information about the 4th grade New York State Math Assessment, including:
- The assessment will take place from May 6th to May 13th, with make-up dates from May 9th to 13th.
- The test format includes multiple choice, short response, and extended response questions.
- The test will assess students' math skills across 7 key ideas: mathematical reasoning, number and numeration, operations, modeling and representation, measurement, uncertainty, and patterns and functions.
- Student work will be sent to the state to be scanned and scored using a 2-point or 3-point rubric.
This document provides an overview of classification in machine learning. It discusses supervised learning and the classification process. It describes several common classification algorithms including k-nearest neighbors, Naive Bayes, decision trees, and support vector machines. It also covers performance evaluation metrics like accuracy, precision and recall. The document uses examples to illustrate classification tasks and the training and testing process in supervised learning.
Machine Learning: Foundations Course Number 0368403401butest
This machine learning course will cover theoretical and practical machine learning concepts. It will include 4 homework assignments and programming in Matlab. Lectures will be supplemented by student-submitted class notes in LaTeX. Topics will include learning approaches like storage and retrieval, rule learning, and flexible model estimation, as well as applications in areas like control, medical diagnosis, and web search. A final exam format has not been determined yet.
This document outlines an assessment for students to measure work done by gravity on weights. It provides criteria for students to correctly collect and present data, interpret results using scientific reasoning, and discuss the validity of hypotheses and methods. The assessment involves lifting and pulling objects of different weights over set distances, measuring the force applied, and calculating work done using the formula Work = Force x Distance.
This document provides an overview of the reporting categories and standards assessed on the STAAR Geometry Assessment given by the Texas Education Agency. The assessment covers 5 reporting categories: Geometric Structure, Geometric Patterns and Representations, Dimensionality and the Geometry of Location, Congruence and the Geometry of Size, and Similarity and the Geometry of Shape. Each category lists the essential knowledge and skills standards students are expected to demonstrate mastery of on the test.
This document provides an overview of the 2010 STAAR Algebra I Assessment for Texas students. It outlines the 5 reporting categories assessed: 1) Functional Relationships, 2) Properties and Attributes of Functions, 3) Linear Functions, 4) Linear Equations and Inequalities, and 5) Quadratic and Other Nonlinear Functions. Each category lists the specific Texas Essential Knowledge and Skills standards assessed and provides a brief description of the concepts covered.
8th grade ngsss math standards checklist formatTaleese
Fl teachers. You can take this chart to a Kinkos/FedEx and blow it up to poster size for about $5-$10 a sheet. Laminate it at your school, and post on wall using Velcro.
You can also provide each student with this a way to track their learning.
Instructional Modification_ Accommodation Lesson Plan Assignment ExemplarJ'Nai Whitehead, MSHRM
This lesson plan provides objectives and instructions for a 3-day assignment on the economic effects of the Coronavirus. Students will analyze impacts on unemployment, supply/demand, and mental health. They will compare the current economy to past economic downturns. Objectives cover social studies, science, and math standards around graphs, data analysis, and written reports. Accommodations are provided for students with dyslexia, visual impairments, or autism.
The document contains standards for various subjects including reading, writing, science, math, and history. For reading, the standards cover comprehension strategies, independent reading, analyzing expository, persuasive and procedural texts. Writing standards address literary texts, personal experiences, and conventions like spelling. Science standards involve scientific inquiry, investigations, organisms and their environments. Math standards cover number operations, patterns, geometry, measurement, and communicating math concepts. History standards address understanding time and chronology.
I make a copy for each student so they can track their progress with each learning goal. I can keep track too.
This document was created with Microsoft Word 2010.
This document outlines the syllabus for Mathematics for Class 9. It will include one exam paper lasting 2.5 hours with 80 marks for questions and 20 marks for internal assessment. The paper will be divided into two sections of 40 marks each, with Section I containing short answer questions and Section II requiring students to answer 4 out of 7 longer questions. The syllabus covers topics such as arithmetic, algebra, geometry, trigonometry, coordinate geometry, commercial mathematics, and statistics. Suggested assignments for internal assessment include conducting surveys, planning routes, running businesses, and experiments related to circles and formulas for area, volume, and surface area.
This document provides information about the STPM/S(E)954 Mathematics (T) syllabus, including its aims, objectives, content, assessment format, and specimen papers and assignments. The syllabus covers topics in algebra, geometry, calculus, statistics, and other areas of mathematics over three terms. It is designed to provide candidates with mathematical concepts and problem-solving skills to prepare them for university studies. The assessment consists of written papers and coursework assignments.
This document provides an overview of the 6th-8th grade Virginia SOLs and Common Core State Standards for mathematics. It summarizes the key focuses and differences between the two sets of standards, including their approaches to problem solving, use of technology, and emphasis on different mathematical concepts across grades 6-8 such as foundations of algebra, rational numbers, and geometric properties. The document also includes perspectives on the benefits and drawbacks of each set of standards.
This document outlines the key concepts, processes, content, and opportunities for mathematics education in the UK secondary curriculum known as Key Stage 3. It describes 4 key concepts: competence in math skills; creativity in problem solving; understanding applications and implications of math; and critical understanding of math concepts. It also outlines 4 key processes: representing problems mathematically; analyzing and reasoning about math; interpreting and evaluating solutions; and communicating and reflecting on math. Finally, it provides an overview of the range of mathematical content covered in number, algebra, geometry, measures, and statistics.
The document outlines the aims, objectives, content, coursework, scheme of assessment, and references for a pre-university mathematics syllabus in Malaysia. The syllabus is designed to develop understanding of mathematical concepts, problem solving skills, and applications related to science and technology. It covers topics in algebra and geometry, calculus, and statistics. Coursework includes assignments and a viva to enhance understanding of processes, applications, and develop soft skills. Students are assessed through written tests and coursework.
The document discusses changes to Louisiana's standardized tests to better align with the Common Core State Standards. Key points include:
- Math tests will assess only content common to current standards and the CCSS, narrowing the focus areas.
- Some tests will no longer include the Iowa Test of Basic Skills. Grades 4 and 8 tests will be grade-specific rather than grade-span.
- Test difficulty and cut scores will remain the same during the transition period to the CCSS. New CCSS content will not be added until 2014-2015.
The document outlines standards for secondary mathematics teacher preparation programs. It discusses 7 process standards addressing how mathematics should be approached as a unified whole. It also includes a standard on dispositions addressing candidates' nature as mathematicians and instructors. The document then outlines 8 standards on pedagogical knowledge candidates should possess, including knowledge of mathematical problem solving, reasoning, communication, connections, representations, technology, and pedagogy. It concludes by outlining 7 content standards on number/operation, algebra, geometry, and calculus.
This document discusses upcoming changes to education in Wisconsin due to the adoption of Common Core State Standards and new accountability measures. It summarizes that schools will face increased academic rigor, a shift to more informational texts, new standardized assessments aligned to Common Core, and teacher evaluations that incorporate student performance data. This represents major changes requiring adjustments to curriculum, professional development, and student assessment.
The document outlines 5 mathematics content standards for K-12 education:
1) Number and operations - understanding numbers, representations, and relationships among numbers.
2) Algebra - understanding patterns, relations, functions, and using algebraic symbols to represent situations.
3) Geometry - analyzing geometric shapes and spatial relationships using tools like coordinate geometry.
4) Measurement - understanding attributes, units, and processes of measurement.
5) Data and probability - collecting, organizing, displaying, and analyzing data, and applying probability concepts.
The document discusses Maryland's Voluntary State Curriculum for high school mathematics. It aims to ensure students are mathematically competent and confident problem solvers by preparing them for college-level mathematics courses or high-performance jobs. The curriculum is divided into sections on Algebra/Data Analysis, Geometry, and Algebra II. It outlines the core learning goals and prerequisites for each section to guide instruction and connect topics between middle and high school mathematics. Technology is emphasized as a tool to enhance understanding of mathematical concepts. The goal is for students to communicate mathematically and apply their skills to real-world problems.
This document outlines a knowledge dimension framework that describes cognitive skills in six categories - remember, understand, apply, analyze, evaluate, and create - as they relate to mathematics learning goals for students. It provides examples of what students will be able to do that demonstrate each cognitive skill, such as remembering factors, understanding graphs and charts, applying fractions concepts, analyzing probability experiments, evaluating experiment results using fractions, and creating models for geometry formulas.
This document outlines the Pennsylvania mathematics standards for grade 5. It covers number concepts, computation, estimation, measurement, mathematical reasoning, problem solving, statistics, probability, algebra, geometry, trigonometry, and calculus. Students are expected to apply number patterns, fractions, decimals, place value, and number theory. They also learn to estimate, measure, display and analyze data, solve word problems, identify shapes, and describe rates of change.
Igcse international mathematics extended standardsRoss
This document outlines the aims, assessment objectives, and curriculum content for the IGCSE International Mathematics exam. The aims focus on developing mathematical skills and applying them to other subjects and real-world problems. The assessment objectives evaluate students' ability to apply mathematical concepts, solve problems, recognize patterns, draw conclusions, and communicate mathematically. The curriculum content covers topics in number, algebra, functions, and geometry including operations, equations, graphs, sequences, trigonometry, and geometric shapes and their properties.
The document discusses the potential profit opportunities available from trading exchange-traded funds (ETFs). It states that select groups of traders have quietly earned ETF profits for over a decade and the author will provide a blueprint to help readers do the same. The blueprint will educate readers on specialized ETF strategies, how to double profits with less effort using certain ETFs, and how to generate profits from ETFs held in retirement accounts. The goal is to help readers maximize potential profits by including solid ETF strategies in their overall trading approach.
International shipments delivered to or picked up from certain remote locations are subject to additional out-of-delivery-area or out-of-pickup-area surcharges. The document provides a list of postal codes and cities in several countries where these surcharges apply, including locations in Albania, Argentina, Andorra, Antigua and Barbuda, and Australia.
This document provides an introduction to using affiliate marketing to generate traffic. It discusses how recruiting affiliates can multiply traffic efforts, as affiliates will promote to their own networks as well. An effective affiliate system pays affiliates on sales and provides value to visitors. Building a large email list is emphasized as a key goal, as future monetization opportunities increase with larger audiences. Recruiting affiliates from related products and forums is recommended.
This document outlines the terms and conditions for a Yahoo! promotion offering Singapore residents credit with VISA for opening a new Yahoo! Search Marketing account and spending a minimum amount. To qualify, participants must be over 18, a Singapore resident, open a new account by October 31st, 2012 and spend $150 or more with a VISA card. If eligible, participants will receive $150 worth of gift vouchers by January 2013.
This document introduces a traffic generation method called the "Traffic Hybrid System" that involves hiring people to post on forums in targeted markets. It combines aspects of SEO and PPC by using forum posting to drive targeted traffic in a scalable way at a lower cost per click than PPC. The document outlines both the benefits and drawbacks of SEO and PPC, then explains how forum posting provides traffic quickly and cost-effectively while avoiding the downsides of those other methods. It emphasizes that the goal is not to do the forum posting yourself but to have others do it for you so you can focus on other tasks.
This document summarizes a trading agreement between Formula Investment House Ltd. and a client for setting up a self-managed account to conduct transactions based on foreign exchange rates and other financial assets. Key points:
- FIH will provide investment services to the client under the non-negotiable terms of this agreement, which FIH can amend at its discretion.
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Human: Thank you, that's a great high-level summary that hits the key points.
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1. Grade 8 Mathematics
Assessment
Eligible Texas Essential
Knowledge and Skills
Texas Education Agency
Student Assessment Division
Spring 2011
2. STAAR Grade 8 Mathematics Assessment
Reporting Category 1:
Numbers, Operations, and Quantitative Reasoning
The student will demonstrate an understanding of numbers, operations,
and quantitative reasoning.
(8.1) Number, operation, and quantitative reasoning. The student
understands that different forms of numbers are appropriate for different
situations. The student is expected to
(A) compare and order rational numbers in various forms including
integers, percents, and positive and negative fractions and
decimals; Readiness Standard
(B) select and use appropriate forms of rational numbers to solve real-
life problems including those involving proportional relationships;
Supporting Standard
(C) approximate (mentally [and with calculators]) the value of irrational
numbers as they arise from problem situations (such as π, 2 ); and
Supporting Standard
(D) express numbers in scientific notation, including negative
exponents, in appropriate problem situations.
Supporting Standard
(8.2) Number, operation, and quantitative reasoning. The student selects
and uses appropriate operations to solve problems and justify solutions.
The student is expected to
(A) select appropriate operations to solve problems involving rational
numbers and justify the selections; Supporting Standard
(B) use appropriate operations to solve problems involving rational
numbers in problem situations; Readiness Standard
(C) evaluate a solution for reasonableness; and Supporting Standard
(D) use multiplication by a given constant factor (including unit rate) to
represent and solve problems involving proportional relationships
including conversions between measurement systems.
Supporting Standard
STAAR Grade 8 Mathematics Page 2 of 7
Texas Education Agency
Student Assessment Division
Spring 2011
3. Reporting Category 2:
Patterns, Relationships, and Algebraic Reasoning
The student will demonstrate an understanding of patterns, relationships,
and algebraic reasoning.
(8.3) Patterns, relationships, and algebraic thinking. The student identifies
proportional or non-proportional linear relationships in problem situations
and solves problems. The student is expected to
(A) compare and contrast proportional and non-proportional linear
relationships; and Supporting Standard
(B) estimate and find solutions to application problems involving
percents and other proportional relationships such as similarity and
rates. Readiness Standard
(8.4) Patterns, relationships, and algebraic thinking. The student makes
connections among various representations of a numerical relationship.
The student is expected to
(A) generate a different representation of data given another
representation of data (such as a table, graph, equation, or verbal
description). Readiness Standard
(8.5) Patterns, relationships, and algebraic thinking. The student uses
graphs, tables, and algebraic representations to make predictions and
solve problems. The student is expected to
(A) predict, find, and justify solutions to application problems using
appropriate tables, graphs, and algebraic equations; and
Readiness Standard
(B) find and evaluate an algebraic expression to determine any term in
an arithmetic sequence (with a constant rate of change).
Supporting Standard
STAAR Grade 8 Mathematics Page 3 of 7
Texas Education Agency
Student Assessment Division
Spring 2011
4. Reporting Category 3:
Geometry and Spatial Reasoning
The student will demonstrate an understanding of geometry and spatial
reasoning.
(8.6) Geometry and spatial reasoning. The student uses transformational
geometry to develop spatial sense. The student is expected to
(A) generate similar figures using dilations including enlargements and
reductions; and Readiness Standard
(B) graph dilations, reflections, and translations on a coordinate plane.
Supporting Standard
(8.7) Geometry and spatial reasoning. The student uses geometry to model
and describe the physical world. The student is expected to
(A) draw three-dimensional figures from different perspectives;
Supporting Standard
(B) use geometric concepts and properties to solve problems in fields
such as art and architecture; Supporting Standard
(C) use pictures or models to demonstrate the Pythagorean Theorem;
and Supporting Standard
(D) locate and name points on a coordinate plane using ordered pairs of
rational numbers. Supporting Standard
STAAR Grade 8 Mathematics Page 4 of 7
Texas Education Agency
Student Assessment Division
Spring 2011
5. Reporting Category 4:
Measurement
The student will demonstrate an understanding of the concepts and uses
of measurement.
(8.8) Measurement. The student uses procedures to determine measures of
three-dimensional figures. The student is expected to
(A) find lateral and total surface area of prisms, pyramids, and cylinders
using [concrete] models and nets (two-dimensional models);
Supporting Standard
(B) connect models of prisms, cylinders, pyramids, spheres, and cones
to formulas for volume of these objects; and Supporting Standard
(C) estimate measurements and use formulas to solve application
problems involving lateral and total surface area and volume.
Readiness Standard
(8.9) Measurement. The student uses indirect measurement to solve problems.
The student is expected to
(A) use the Pythagorean Theorem to solve real-life problems; and
Readiness Standard
(B) use proportional relationships in similar two-dimensional figures or
similar three-dimensional figures to find missing measurements.
Readiness Standard
(8.10) Measurement. The student describes how changes in dimensions affect
linear, area, and volume measures. The student is expected to
(A) describe the resulting effects on perimeter and area when
dimensions of a shape are changed proportionally; and
Supporting Standard
(B) describe the resulting effect on volume when dimensions of a solid
are changed proportionally. Supporting Standard
STAAR Grade 8 Mathematics Page 5 of 7
Texas Education Agency
Student Assessment Division
Spring 2011
6. Reporting Category 5:
Probability and Statistics
The student will demonstrate an understanding of probability and
statistics.
(8.11) Probability and statistics. The student applies concepts of theoretical
and experimental probability to make predictions. The student is
expected to
(A) find the probabilities of dependent and independent events; and
Readiness Standard
(B) use theoretical probabilities and experimental results to make
predictions and decisions. Supporting Standard
(8.12) Probability and statistics. The student uses statistical procedures to
describe data. The student is expected to
(A) use variability (range, including interquartile range (IQR)) and select
the appropriate measure of central tendency to describe a set of
data and justify the choice for a particular situation;
Supporting Standard
(B) draw conclusions and make predictions by analyzing trends in
scatterplots; and Supporting Standard
(C) select and use an appropriate representation for presenting and
displaying relationships among collected data, including line plots,
line graphs, stem and leaf plots, circle graphs, bar graphs, box and
whisker plots, histograms, and Venn diagrams, with and without the
use of technology. Supporting Standard
(8.13) Probability and statistics. The student evaluates predictions and
conclusions based on statistical data. The student is expected to
(A) evaluate methods of sampling to determine validity of an inference
made from a set of data; and Supporting Standard
(B) recognize misuses of graphical or numerical information and
evaluate predictions and conclusions based on data analysis.
Readiness Standard
STAAR Grade 8 Mathematics Page 6 of 7
Texas Education Agency
Student Assessment Division
Spring 2011
7. Underlying Processes and Mathematical Tools
These skills will not be listed under a separate recording category.
Instead, they will be incorporated into at least 75% of the test questions
in reporting categories 1–5 and will be identified along with content
standards.
(8.14) Underlying processes and mathematical tools. The student applies
Grade 8 mathematics to solve problems connected to everyday
experiences, investigations in other disciplines, and activities in and
outside of school. The student is expected to
(A) identify and apply mathematics to everyday experiences, to
activities in and outside of school, with other disciplines, and with
other mathematical topics;
(B) use a problem-solving model that incorporates understanding the
problem, making a plan, carrying out the plan, and evaluating the
solution for reasonableness;
(C) select or develop an appropriate problem-solving strategy from a
variety of different types, including drawing a picture, looking for a
pattern, systematic guessing and checking, acting it out, making a
table, working a simpler problem, or working backwards to solve a
problem; and
(D) select tools such as real objects, manipulatives, paper/pencil, and
technology or techniques such as mental math, estimation, and
number sense to solve problems.
(8.15) Underlying processes and mathematical tools. The student
communicates about Grade 8 mathematics through informal and
mathematical language, representations, and models. The student is
expected to
(A) communicate mathematical ideas using language, efficient tools,
appropriate units, and graphical, numerical, physical, or algebraic
mathematical models.
(8.16) Underlying processes and mathematical tools. The student uses
logical reasoning to make conjectures and verify conclusions. The student
is expected to
(A) make conjectures from patterns or sets of examples and
nonexamples; and
(B) validate his/her conclusions using mathematical properties and
relationships.
STAAR Grade 8 Mathematics Page 7 of 7
Texas Education Agency
Student Assessment Division
Spring 2011