Internal Assessment Your overall IB mark (the one sent to universities after the IB test) in any IB science course is based upon two kinds of assessments.

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Presentation transcript:

Internal Assessment Your overall IB mark (the one sent to universities after the IB test) in any IB science course is based upon two kinds of assessments or grades:  External Assessment:  Your score on end-of-course exam (80% of total IB mark) Internal Assessment:  Your performance on in class laboratory work (20% of total IB mark)

Internal Assessment Criteria IB lab reports are graded using three parts They are: Planning – Pl Data collection and processing—DCP (includes lab drawing, statistics and graphing) Discussion, Evaluation and Conclusion – (DEC)

Planning Complete / 2 Partial / 1 Not at all / 0 A S P E C T   Complete / 2 Partial / 1 Not at all / 0 A S P E C T Define problem & select variables States a focused problem/ research question and identifies the relevant variables. States a problem/research question that is incomplete OR identifies only some relevant variables. Does not state a problem/ research question AND does not identify any relevant variables. Controlling variables Designs a method for the effective control of variables. Designs a method that makes some attempt to control the variables. Designs a method that does not allow for the control of the variables. Developing a method for collection of data Describes a method that allows for the collection of sufficient relevant data. Describes a method that does not allow for the collection of sufficient relevant data. Describes a method that does not allow for the collection of any relevant data.

Planning – Pl (Aspect 1) Define problem & select variables Complete / 2 States a focused problem/ research question and identifies the relevant variables. Partial / 1 States a problem/research question that is incomplete OR identifies only some relevant variables. Not at all / 0 Does not state a problem/ research question AND does not identify any relevant variables.

Planning Aspect 1: Defining the Problem and Selecting Variables State variables explicitly, and explain why each is relevant.  All reasonable variables that might affect the outcome should be identified.  Indicate which variable(s) is/are manipulated variables (ones that you will change) and which are the responding variables (ones that will respond to what you did).  Indicate which variables must be controlled and why those variables must be controlled. The variables need to be explicitly identified by the student as the dependent (measured), independent (manipulated) and controlled variables (constants). Relevant variables are those that can reasonably be expected to affect the outcome

Planning Aspect 1: Defining the Problem and Selecting Variables Hypothesis(es) Although not required by the IB Organization, for many labs you will be asked to include a hypothesis.  A hypothesis is like a prediction.  It will often take the form of a proposed relationship between two or more variables that can be tested by experiment:  “If X is done, then Y will occur.”    You must also provide an explanation for your hypothesis.  This should be a brief discussion (paragraph form) about the theory or ‘why’ behind your hypothesis and prediction.  Be sure your hypothesis is related directly to your research question and that the manipulated and responding variables for your experiment are clear.

Controlling variables Planning - P (Aspect 2) Controlling variables Complete / 2 Designs a method for the effective control of variables. Partial / 1 Designs a method that makes some attempt to control the variables. Not at all / 0 Designs a method that does not allow for the control of the variables.

Planning Aspect 2: Controlling Variables Control of Variables “Control of variables” refers to the manipulation of the independent variable and the attempt to maintain the controlled variables at a constant value. You should write a paragraph in which you describe how the control of variables is achieved. If the control of variables is not practically possible, some effort should be made to monitor the variable(s).  State an explicit procedure or method for how each variable will be controlled. ).

Developing a method for collection of data Planning - Pl (Aspect 3) Developing a method for collection of data Complete / 2 Describes a method that allows for the collection of sufficient relevant data. Partial / 1 Describes a method that does not allow for the collection of sufficient relevant data. Not at all / 0 Describes a method that does not allow for the collection of any relevant data.

Planning Aspect 3: Developing a Method for Collection of Data Apparatus and Materials Consider making a list of your experiment and materials needed.  Be as specific as possible.    A diagram or photograph of how you set up the experiment may be appropriate, especially for more complicated experiments.  Be sure your diagram includes a title and any necessary labels. You might have to decide how much of a substance or a solution to use.  If so, state your reasoning or show the calculations.

Planning Aspect 3: Developing a Method for Collection of Data Method/Procedure State the procedure that you are going to use in the experiment.  This should be in the form of a list of step-by-step directions.  Provide enough detail so that another person could repeat your work by reading your report!     If you do something in your procedure to minimize an anticipated error, mention this as well.  In your method, clearly state how you will collect data.  What measuring device will you use, what data will you record, and when?  Or what qualitative observations will you look for (such as color change) and what will you do when you see this happen?

Planning Aspect 3: Developing a Method for Collection of Data Multiple Trials The procedure must allow collection of sufficient relevant data.  The planned investigation should anticipate the collection of sufficient data so that the aim or research question can be suitably addressed and an evaluation of the reliability of the data can be made.   As a rule, the lower limit is five measurements, or a sample size of five. The data range and amount of data in that range are also important.