Disciplinary Core Ideas
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1 Independence Junior High 7th grade science Pacing Guide Trimester 2 Disciplinary Core Ideas Unit: Motion and Stability- Forces and Interactions Standard number Learning target I can statements MS-PS2-3. MS-PS2-4. MS-PS2-5. Ask questions about data to determine the factors that affect the strength of electric and magnetic forces. Construct and present arguments using evidence to support the claim that gravitational interactions are attractive and depend on the masses of interacting objects. Conduct an investigation and evaluate the experimental design to provide evidence that fields exist between objects exerting forces on each other even though the objects are not in contact. Examples of devices that use electric and magnetic forces could include electromagnets, electric motors, or generators. Examples of data could include the effect of the number of turns of wire on the strength of an electromagnet, or the effect of increasing the number or strength of magnets on the speed of an electric motor.] Examples of evidence for arguments could include data generated from simulations or digital tools; and charts displaying mass, strength of interaction, distance from the Sun, and orbital periods of objects within the solar system. Examples of this phenomenon could include the interactions of magnets, electrically-charged strips of tape, and electrically-charged pith balls. Examples of investigations could include first-hand experiences or simulations. MS-PS4-1 Use mathematical representations to describe a simple model for waves that includes how the amplitude of a wave is related to the energy in a wave. A simple wave has a repeating pattern with a specific wavelength, frequency, and amplitude. MS-PS4-2 Develop and use a model to describe that Emphasis is on both light and mechanical waves. Examples of models
2 waves are reflected, absorbed, or transmitted through various materials. could include drawings, simulations, and written descriptions. MS-PS4-3 Integrate qualitative scientific and technical information to support the claim that digitized signals are a more reliable way to encode and transmit information than analog signals. Emphasis is on a basic understanding that waves can be used for communication purposes. Examples could include using fiber optic cable to transmit light pulses, radio wave pulses in wifi devices, and conversion of stored binary patterns to make sound or text on a computer screen 1 Does Not Meet 2 Progressing 3 Meets expectations 4 Exceeds expectations The student demonstrates very little understanding of the grade level standard. The student does not show any significant ability to perform the skill. The student demonstrates incomplete understanding of the grade level standard. The student makes significant errors when performing the skill or has significant gaps in applying his or her knowledge. The student demonstrates complete understanding of the grade level standard with very few errors. The student demonstrates complete and detailed understanding of the grade level standard and exhibits some understanding of the next grade level standard. Science and Engineering Practices Practice: Asking Questions and Defining Problems Asking Questions & Defining Problems
3 Asking questions based on observations Questions are asked to seek additional information about/ clarify phenomena, models or results of an investigation or design solution. In addition, questions are asked to clarify evidence used in an argument and determine relationships between independent and dependent variables or relationships in models. Questions link to unexpected results and seek to clarify information, understand relationships and refine models/explanations/ or problems. Formulates, refines, and evaluates empirically testable questions and design problems using models and simulations. Ask questions that arise from careful observation of phenomena, or unexpected results, to clarify and/or seek additional information that arise from examining models or a theory, to clarify and/or seek additional information to determine relationships, including quantitative relationships, between independent and dependent variables. o to clarify and refine a model, an explanation, or an engineering problem. Asking questions that can be answered by an investigation Questions can be investigated and used to predict outcomes. Questions require evidence to answer and a hypothesis can be written from observation and scientific principles. Questions focus on whether an investigation is relevant, doable, and result in a hypothesis that is based on a model or theory. Evaluate a question to determine if it is testable and relevant. Ask questions that can be investigated within the scope of the school laboratory, research facilities, or field (e.g., outdoor environment) with available resources and, when appropriate, frame a hypothesis based on a model or theory. Challenging through questions Questions are asked about phenomena Questions are formed as a response to arguments and challenge arguments. Questions challenge data sets used to support arguments, data sets or designs. Ask and/or evaluate questions that challenge the premise(s) of an argument, the interpretation of a data set, or the suitability of a design. Defining a problem Prior knowledge is used to describe a simple problem The problem includes criteria for success and constraints on A design problem can be defined and solved through the development Define a design problem that involves the development of a process or system with interacting
4 that can be solved through the development of an object, tool, process or system. solutions. of an object, tool, process or system that includes criteria and constraints backed by scientific knowledge and limitations. components and criteria and constraints that may include social, technical, and/or environmental considerations. Practice: Developing and Using Models Developing and Using Models Developing model(s) to describe phenomena Model is incomplete, does not describe some mechanisms, and does not use key content vocabulary. Model is used to describe mechanisms and/or phenomena using key content vocabulary and several pieces of evidence. Model is used to describe unobservable mechanisms and/or phenomena using key content vocabulary and observable and unobservable evidence. Model explains a relationship within the system. Develop a complex model that allows for manipulation and testing of a proposed process or system. Design a test of a model to ascertain its reliability. Develop, revise, and/or use a model based on evidence to illustrate and/or predict the relationships between systems or between components of a system. Analysis of model(s) The model does not explain the benefits and limitations of the system. Model provides the benefits and limitations of one model. Model provides the benefits and limitations of two different models. Evaluate merits and limitations of two different models of the same proposed tool, process, mechanism or system in order to select or revise a model that best fits the evidence or design criteria. Using models to predict phenomena Model does not predict phenomena. Model predicts phenomena. Model clearly defines the areas of the system that lends itself to predict Develop and/or use multiple types of models to provide mechanistic accounts and/or predict phenomena, and move
5 phenomena. flexibly between model types based on merits and limitations. Using models to communicate ideas share with small group/class nor provide reasoning behind the model. Students are able to answer questions about the model when asked to present to the whole class. Student shares advantages and disadvantages of the model with the whole class and is able to answer questions about the model. Modeling for data Model demonstrates no use of data during the investigation. The model clearly demonstrates data used during investigation. The model clearly demonstrates data used during the investigation and suggests data missing or other pieces of data to make the model more comprehensive. Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems Practice: Planning and Carrying Out Investigations Planning and Carrying Out Investigations Hypothesis Hypothesis is made based on limited knowledge of the purpose of the investigation. A hypothesis is logical and made based on knowledge of the purpose of the investigation. Hypothesis also includes reasoning for claims and predictions for changes in variables. Hypothesis includes models and explanations of scientific Make directional hypotheses that specify what happens to a dependent variable when an independent variable is manipulated.
6 principles and theories. Procedure follow a step by step procedure. Student does not evaluate tools needed and number of trials needed. Create, with assistance, and follow a step by step procedure, including tools needed and number of trials needed. Create and follow a step by step procedure, including tools, number of trials and measurements needed. Consider environmental and social impacts. Manipulate variables and collect data about a complex model of a proposed process or system to identify failure points or improve performance relative to criteria for success or other variables. Select appropriate tools to collect, record, analyze, and evaluate data. Plan an investigation or test a design individually and collaboratively to produce data to serve as the basis for evidence as part of building and revising models, supporting explanations for phenomena, or testing solutions to problems. Plan and conduct an investigation or test a design solution in a safe and ethical manner including considerations of environmental, social, and personal impacts. Variables identify controls and constants or the number of trials needed to conduct a fair investigation. Independent and dependent variables are identified as well as controls and constants. Independent and dependent variables are identified as well as controls and constants. Variables are added or manipulated when appropriate. Consider possible confounding variables or effects and evaluate the investigation s design to ensure variables are controlled. Data Data is not collected when following a procedure. Data is collected when a procedure is developed and is accurate or logical. Data can be used as evidence to support a claim. Limitations on data collection are considered. Plan and conduct an investigation individually and collaboratively to produce data to serve as the basis for evidence, and in the design: decide on types, how much, and accuracy of
7 data needed to produce reliable measurements and consider limitations on the precision of the data (e.g., number of trials, cost, risk, time), and refine the design accordingly. Results The investigation results cannot be used to explain a model, tool or processes. The investigation results can be used to determine improvements to any part of the investigation. Results are used to back up a claim. The investigation results in a claim that includes data evidence and proven scientific theories and principles. The investigation results can be used to make predictions and explain other phenomena. The investigation results in a claim, can predict and explain phenomena, and serve as the basis for evidence to build and revise models, support explanations for phenomena, or test solutions to problems. Practice: Analyzing and Interpreting Data Analyzing and Interpreting Data Using math to interpret data use data to make sense of phenomena. Uses data, statistics and probability to interpret data. Use statistics and probability to answer questions and solve problems. Use digital tools. Apply concepts of statistics and probability (including determining function fits to data, slope, intercept, and correlation coefficient for linear fits) to scientific and engineering questions and problems, using digital tools when feasible.. Limitations of data analysis identify a source of Identify a source of error within an Identify multiple sources of error and explain how Consider limitations of data analysis (e.g., measurement error, sample selection) when
8 error within an investigation. investigation and identify improvements in tools or methods of gathering data. this may affect data results. analyzing and interpreting data. Comparing data compare and contrast data from different groups to find similarities and differences in the results. Analyze data from an investigation to determine similarities and differences in the results. Analyze data from several investigations to determine similarities and differences in the results. Compare and contrast several types of data sets to determine consistency of measurement and observation. Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims or determine an optimal design solution. Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations Evaluate the impact of new data on a working explanation and/or model of a proposed process or system. Analyze data to identify design features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success.
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