IB Chemistry IA Checklist Design (D)

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Taken from blogs.bethel.k12.or.us/aweyand/files/2010/11/ia-checklist.doc IB Chemistry IA Checklist Design (D) Aspect 1: Defining the problem and selecting variables Report has a title which clearly reflects what is being done in this experiment Research question Research question includes IV and DV A focused problem or a specific research question is identified and described in enough detail for the reader to understand the aim of the experiment. A clear hypothesis is stated (not necessary when trying to measure already known value.) If there is a prediction, it should be quantitative. Make a sketch graph now; focuses the design later. Variables The independent variable, dependent variable, and all variables that are controlled in the experiment are mentioned. IV is quantitative DV is quantitative Variables must be described sufficiently to permit replication (copying) of this experiment. Aspect 2: Controlling variables Method for controlling variables The IV is discussed including how it will be manipulated and the level of the precision (sig figs). The method for the effective control of the variables is described. Described how the CVs are maintained at constant values; (if known, identify sig figs). Materials Indicate all the apparatus and materials used, including the volumes of tubes and cylinders, the concentrations of solutions, and the model and manufacturer of any complex apparatus. Diagram of equipment set-up

Annotate this diagram to show how variables were involved especially controlled variables. Do not just label the equipment. Additional diagrams are ok. Procedure Procedure may be in numbered steps or paragraphs. If you use a standard procedure in your method, reference it using MLA1, APA2, or Council of Biology Editors format3 (note: CBE/CSE format is most commonly used in science papers). Aspect 3: Developing a method for data collection Independent variable is tested at minimum 5 increments (or intervals or levels ) An adequately broad data range is considered. Data across a spectrum of independent variable ranges should be considered when necessary. Minimum 5 trials per IV increment The data gathered enables the aim/ research question/ hypotheses to be adequately addressed. Each piece of data collected is relevant to fulfill the aim/research question/hypotheses. State how the results will be presented, with reason. Describe any calculations that will need to be completed, giving formulas where appropriate. Method is described thoroughly and is clearly understandable to the reader. Procedure addresses safety concerns: appropriate safety precautions are described. 1 See instructions and examples of MLA format on the web at: http://owl.english.purdue.edu/owl/resource/557/01/ 2 See instructions and examples of APA format on the web at: http://owl.english.purdue.edu/owl/resource/560/01/ 3 See instructions and examples of CBE/CSE format on the web at: http://writing.wisc.edu/handbook/doccbe_nameyear_intext.html

Data collection and processing (DCP) Aspect 1: Recording raw data There are many fine points to include here but they are VERY important to get full marks! Raw Data Data is collected independently. Data is primarily quantitative (numerical) Data must include qualitative observations. (This may provide inspiration in the conclusion and especially the evaluation later.) Raw data recorded in suitable format(s) Table organization Includes descriptive title (or information can be adequately stated in table headers; table may have double headers) for any table, graph, etc. that is used. Column & row headers identical to graph axes labels (if table is source of graph data) IV on left column uses specific terms (ie. NaCl instead of salt; volume instead of amount; length instead of size) tables not split between pages cells contains only one value tables arranged vertically (usually) tables show grid lines Table numbers uncertainty in headers after units. Absolute uncertainties expressed to 1 sig fig. align decimals all values in a column must end at the same decimal place uses significant figures mean contains one more digit than significant figures in values percentage or relative uncertainties should have 2 sig figs Table units units in column headings, not in cells units after "/" no parentheses use SI units - according to IB Variable that is measured or recorded is clearly stated (e.g. in the column heading in a table). Units for every variable. Uncertainty of measurements based on significant digits in the column headings. The same level of precision (number of decimal places) is used for all the items of a variable.

Processed Data Aspect 2: processing raw data Suitable manner to process the raw data is used (this may involve a mathematical processing, statistical analysis, or transforming the data into a suitable graphical representation). All of the raw data has been completely processed. Example calculations provided for substantial processing (ie. don t need to demonstrate sum, mean or standard deviation, but linear regression if used, for example should be shown. The raw data has been processed correctly (correctly using significant figures and uncertainty values). Aspect 3: presenting processed data Suitable format in which to present the processed data is used. There are clear headings for all tables There are clear titles for all graphs Any graphs have appropriate scales, labelled axes with units and accurately plotted data points with a suitable best-fit line or curve if necessary. All the processing stages up to the final result can be followed easily (explanations are clear where necessary). The final results are shown expressed to the correct number of significant figures. The uncertainties and errors of raw data have been taken into account and the work toward this end is shown. (For addition and subtraction, add absolute uncertainties. For multiplication and division, add relative or percentage uncertainties.) Graphing Graph data sourced from single table column & row headings same as graph axes include simple title like "NaCl concentration vs. transmittance" graph is large (whole page is ideal) simple scale (usually 1,2 or 5 times a multiple/power of 10) [scale does not have to start at zero] Graphing the X-axis IV Labels Units uncertainty (after units, like: mass / g / ± 0.01 ) quantitative variable intervals proportional SI units (according to IB)

Graphing the Y-axis DV (even if it is time!) Labels Units uncertainty (after units, like: mass / g / ± 0.01 ) quantitative variable intervals proportional SI units (according to IB) Conclusion & Evaluation (CE) Aspect 1: Concluding Conclusion Is there a clear pattern in your processed data? A conclusion, which is based on a reasonable interpretation of the data, is made. Different graphs are compared or trends in graphs are made explicit. If any hypotheses are being tested, it is stated whether the data supports these hypotheses. Actual processed data used in conclusion (e.g. quote your data!) A justification is given for my conclusion. Reasons for the observed trends in data are written explicitly. Experimental groups are compared with control groups. If an already known and accepted value is being measured, values have been compared with that in a textbook or other reference, in order to assess the validity of the result. Percentage error is mentioned in this case. Any literature/references used is fully referenced using MLA, APA or Council of Biology Editors format. Aspect 2: Evaluating procedure Evaluation The design and method of the investigation have been evaluated. Including discussion of the replicates and sample size used. The precision of the study is evaluated. Measurement errors are analyzed to evaluate the accuracy of measurements. Instrument errors are analyzed (including possibility of calibration errors - when appropriate) to evaluate the accuracy of measurements. Random error is evaluated. Random variations in samples that are uncontrollable should be mentioned. Each error is explained thoroughly and clearly: How might each have impacted the results? Aspect 3: Improving the investigation Improvements All improvements are based on the weaknesses and limitations identified in aspect 2. The specific errors mentioned are the ones corrected. Modifications to the experimental technique are appropriate to correct errors mentioned. All proposed modifications are realistic (they are actually variables that can be controlled). All proposed modifications are clearly explained.

Authenticity and academic integrity All sources of information have been cited in-text All sources have been included in the correct order in the bibliography Citation is consistent and correct throughout (using MLA, APA or Council of Biology Editors format.) Student has shown teacher only one draft and has submitted second draft for assessment Teacher has only assessed final draft Teacher has confirmed that student s work is their own Basic design borrowed from Hilton High School (via IBO-OCC) with constructive feedback from Stephen Tyler, BIS Additions by David Byrum, Julie Cook and Nicole Sabet at Ruamrudee I.S. Further modified by Mrs. Weyand