ib chemistry practical guide (from uwcsea...

IB CHEMISTRY Internal Assessment

STUDENT GUIDE

INTERNAL ASSESSMENT (IA)

Introduction

The Internal Assessment (IA) consists of an interdisciplinary project, a mixture of short- and long-term investigations (such as practicals and subject-specific projects). Student work is internally assessed by the teacher and externally moderated by the IBO. The performance in IA at both higher level and standard level is judged against assessment criteria each consisting of achievement levels 0–3.

IA Time Allocation

Higher level students are required to spend 60 hours, and SL students 40 hours, on practical activities (excluding time spent writing up work). These times include 10 to 15 hours for the group 4 project. Only 2–3 hours of investigative work can be carried out after the deadline for submission of work to the moderator and still be counted in the total hours for the practical scheme of work.

Criteria and Aspects

There are eight assessment criteria which are used to assess the work of both higher level and standard level candidates. planning (a)—Pl (a) planning (b)—Pl (b) data collection—DC data processing and presentation—DPP conclusion and evaluation—CE manipulative skills—MS personal skills (a)—PS (a) personal skills (b)—PS (b)

Each candidate must be assessed at least twice on each of the eight criteria. The two marks for each of the criteria are added together to determine the final mark out of 48 for the IA component. This will then be scaled at IBCA to give a total out of 24%.

Each of the assessment criteria can be separated into two or three aspects. Descriptions are provided to indicate what is expected in order to meet the requirements of a given aspect completely (c) and partially (p). A description is also given for circumstances in which the requirements are not satisfied, not at all (n)

IB Chemistry Internal Assessment

Name:_________________________________________________________ Date(s):_____________________ Number of Hours:___________Title of Experiment: _______________________________________________ Topic:_____________________________________________________

Criteria Aspect Matrix LevelPlanning A Identifies a focused problem or

research question

C P N

Relates the hypothesis or prediction directly to the research question and explains it

C P N

Selects the relevant independent and controlled variables

C P N

ccc 3 cpn 1ccp 2 cnn 1ccn 2 ppn 1cpp 2 pnn 0ppp 1 nnn 0

Planning B Selects appropriate materials

C P N

Describes a method that allows for the control of the variables

C P N

Describes a method that allows collection of sufficient relevant data

C P N


Data Collection Records appropriate raw data (qualitative and/or quantitative), including units and uncertainties where necessary

C P N

Presents raw data clearly, allowing for easy interpretation

C P N

cc 3 pp 1cp 2 pn 0 cn 1 nn 0

Data Processing and Presentation

Processes the data correctly

C P N

Presents processed data appropriately, helping interpretation and, where relevant, takes into account errors and uncertainties

C P N


Conclusion and Evaluation

Gives a valid conclusion based on the correct interpretation of the results, with an explanation where appropriate, compares results with literature values

C P N

Evaluates procedure(s) and results including limitations and errors

C P N

Identifies weaknesses and states realistic suggestions to improve the investigation

C P N


Manipulative Skills Is competent and methodical in the use of techniques and equipment, and pays attention to safety issues

C P N

Follows the instructions accurately, adapting to new circumstances (seeking assistance when required)

C P N


Personal Skills (A) Collaborates with others, recognizing their needs, in order to complete the task

C P N

Expects, actively seeks and acknowledges the views of others

C P N

Exchanges ideas with others, integrating them into the task

C P N


Personal Skills (B) Approaches the investigation with self-motivation and follows it through to completion

C P N

Pays considerable attention to the authenticity of the data and information, and the approach to materials (living or non living)

C P N

Pays attention to the environmental impact of the investigation

C P N


IB Chemistry IA Student Guide

Laboratory Report Format

Typed Report essentials(Top-left) Name Topic

(Top-right) Date( month/ day/ year) Number of Hours

(Center) Title of Experiment

Planning (A) Research Question Hypothesis Variables

Planning (B) Materials/ Apparatus Procedure Diagram of set-up

Data Collection Observations Data Table

Data Processing and Presentation Calculations Graphs Diagrams

Conclusion and Evaluation Conclusion Evaluation of procedure Weaknesses and realistic suggestion to improve experiment

By glapinid and SHenderson2

Samantha Smith February 2, 2005Stoichiometry 2 hours

HYDRATESProblem:Hypothesis:Variables:Materials/ Apparatus:Procedure:Data and Observations:Calculations:Graphs:Diagrams:Conclusion and Evaluation:


PLANNING A

Aspects CommentsIdentifies a focused problem or research question.

Expect an open-ended problem from the teacher Use the title "research question” Do not just repeat the teacher’s title Indicate what specific aspect of the general problem you will be investigating

Relates the hypothesis or prediction directly to the research question and explains it, quantitatively where appropriate.

Hypothesis is a testable statement that predicts the relationship of the independent and dependent variables.

It should be specific and detailed using scientific knowledge. This should be quantitative if you're hypothesis calls for it. ( For higher level, you may be

expected to go into quantitative details) Usually in the form “if y is done, then z will occur” It should be as long as is needed.

Selects the relevant independent and controlled variables.

Independent variable- is the variable that you change Dependent variable- is the variable that responds to what you have already changed

Controlled variables- are the variables that remain the same, the things that you fix in order to maintain a fair test.

SAMPLE- Planning A



The requirements for all aspects of this criterion are fully satisfied. The level of achievement for all aspects is complete.



PLANNING B

Aspects CommentsSelects appropriate apparatus or materials. Include a comprehensive list of everything that you use- apparatus, chemicals, reagents etc.

Your list must include units, uncertainty, sizes and accurate concentrations Draw a detailed diagram of any setup

Describes a method that allows for the control of the variables.

Write the details of a procedure in chronological order – number list or paragraph form. State precisely how you will vary the independent variable State how you are going to measure or observe the dependent variable Indicate how many replicates will be made. It is also important to outline why one approach is taken versus another, if appropriate

Describes a method that allows for the collection of sufficient relevant data

State clearly and exactly what you will do so that any other student could follow your plan State what number and range of measurements you will use Include how many different and suitable readings you need

Take into account the fact that you are trying to collect precise and reliable data

SAMPLE- Planning B



There is no apparatus listed, but the diagram is well labeled. The level of achievement for aspect 1 is complete. The volume and concentration of the acid, the volume of water, and the size of the plates are not mentioned. The level of achievement for aspect 2 is partial. Concentration values should be calculated, and the changes should be carried out so that the volume (and hence the surface exposed to the electrolyte) does not increase. There is no mention of the number of different concentrations to beused, or the number of repeat readings. The level of achievement for aspect 3 is partial.



DATA COLLECTION

Aspects CommentsRecords appropriate raw data (qualitative and/or quantitative), including units and uncertainties where necessary.

Record ALL relevant data and observations Include quantitative data (e.g, measurements of temperature, mass, volume, absorbance, pressure

– all with the appropriate units) Include qualitative observations (e.g. “the final color at the endpoint was a faint pink”, “during the

reaction, the bromine water changed from being a bright yellow to solution of no color”). Report any changes in procedure or unusual conditions. All data recorded should be to the greatest possible number of significant figures that the accuracy

of the equipment allows.

Consider uncertainties and errors in your measurements and deal with it properly ( See Appendix A)

Presents raw data clearly, allowing for easy interpretation

Make sure that someone else could understand exactly what your data means. Do not include deductions/ interpretations/inferences, although you may find it easier to present

deductions and interpretations alongside the observations. If you do this, you must clearly label the deductions.

Your presentation should be methodical and logical. All tables, and graphs should be clearly identified and labeled.



SAMPLE- Data Collection (Qualitative)

Appropriate qualitative raw data is recorded, but the candidate should also record the colour of the “crusty deposit”, and the colour of the alcohols. The data is clearly presented and it is easily interpreted. The requirements for all aspects of this criterion are fully satisfied. The level of achievement is complete.



SAMPLE- Data Collection (Quantitative)

Appropriate qualitative and quantitative raw data is recorded, including units and uncertainties. Presentation is well organized and easy to interpret. The requirements for all aspects of this criterion are fully satisfied. The level of achievement is complete.



DATA PROCESSING AND PRESENTATION

Aspects CommentsProcesses the data correctly Always process and show your results mathematically in some way (eg. use averages or

calculations with appropriate formula to process your results) Include analysis of any errors (See Notes on Appendix A) which have been stated in your data

collection. Convert tabulated data into a graphical form. Convert drawings into diagrams

Presents processed data appropriately, helping interpretation and, where relevant, takes into account errors and uncertainties

Quality of layout should be orderly and easy to follow Use of proper scientific conventions in tables, graphs, etc

Label appropriate bar charts, histograms, pie charts or line graphs (using lines of best fit whenever relevant).



SAMPLE- Data Processing and Presentation (Qualitative)

This DPP is clear, concise, and correct. Uncertainties are indicated. Raw data has been reduced to an easily-interpreted form. Unnecessary and irrelevant items have been omitted. The choice of format is highly appropriate because it makes it easy to spot patterns (eg the Rate pattern and the pH pattern).

Reaction of Metals with Water

SAMPLE- Data Processing and Presentation (Quantitative)



The requirements for all aspects of this criterion are fully satisfied. The average volume of the titrant in the second titration should be 0.0406 dm3, and not 0.0405 dm3. Also, exclusion of the first trial should be stated and justified. The level of achievement is complete.



CONCLUSION and EVALUATION

Aspects CommentsGives a valid conclusion based on the correct interpretation of the results, with an explanation where appropriate, compares results with literature values

This is where you draw conclusions about the experiment as it relates to your aim and hypothesis Use detailed scientific knowledge to explain a valid conclusion given the evidence available from

your results. Compare your results with information from books or other sources and indicate the reference Try to identify trends or patterns in the results to backup your conclusion. Explain how your results support or don’t support your original hypothesis if appropriate.

Calculate percentage error ( See Appendix A) Evaluates procedure(s) and results including limitations and errors

Explain how the equipment might you used and/or the school environments have limited the accuracy of your results.

State how the weaknesses in your method might have contributed to incorrect results. Clearly state if the systematic errors are larger or smaller than the random errors and if the

experimental result is within the random errors range. ( See Appendix A)

Identify all the main systematic errors and if possible give some evidence for them. (Do not give trivial errors as this indicates that you are not evaluating the procedure).

Identifies weaknesses and states realistic suggestions to improve the investigation

Include improvements could you make to your plan to overcome the weaknesses you have identified

State what further investigations would you suggest to test your conclusions or even extend the inquiry



SAMPLE 1- Conclusion and Evaluation

The level of achievement for aspects 1 and 2 of conclusion and evaluation is complete.

Melting/freezing point of para-dichlorobenzene

Melting point = boiling point = 55.0 ± 0.5°C

Literature value of melting point of para-dichlorobenzene = 53.1°C (Handbook of Chemistry and Physics).

The fact that % difference > % uncertainty means random errors alone cannot explain the difference and some systematic error(s) must be present.

Melting point (or freezing point) is the temperature at which the solid and the liquid are in equilibrium with each other: . This is the temperature at which there is no change in kinetic energy (no change in temperature), but a change in potential energy. The value suggests a small degree of systematic error in comparison with the literature value as random errors alone are unable to explain the percentage difference.

Evaluation of procedure and modifications:

i. Duplicate readings were not taken. Other groups of students had % uncertainty > % difference, ie in their case random errors could explain the % difference, so repeating the investigation is important.

ii. The thermometer—how accurate was it? It should have been calibration. In order to eliminate any systematic errors due to the use of a particular thermometer, calibration against the boiling point of water (at 1 atmosphere) or better still against a solid of known melting point (close to the sample) should be done.

iii. The sample in the test tube was not as large as in other groups. Thus the temperature rises/falls were much faster than for other groups. A greater quantity of solid, plus use of a more accurate thermometer (not 0.5°C divisions, but the longer one used by some groups), would have provided more accurate results.



SAMPLE 2- Conclusion and Evaluation

Sources of accepted values should be indicated. Percentage errors could be calculated, and the similarity of values considered. An explanation of exothermicity is not needed unless required by the aim. There should be a more specific explanation of errors, including the direction of systematic errors. The relevance of the high rate could be explained, along with how to obtain better measurements of the maximum temperatures. The level of achievement for aspect 1 is partial. The level of achievement for spects 2 and 3 is complete.

Heats of Neutralization



APPENDIX A

ERRORS/ UNCERTAINTIES OF MEASUREMENTS

It is impossible to perform a chemical analysis that is error free or without uncertainty. In everyday usage “error” means a mistake, but in science an “error” is anything that contributes to a measured value being different than

the “true” value.

Significant Figures/Digits

digits in a measurement that are certain, plus one digit that is an estimate follows certain rules:

o Non-zero digits are always significant. o Any zeros between two significant digits are significant. o A final zero or trailing zeros in the decimal portion ONLY are significant.

Web Exercises on Determining Uncertainties: http://antoine.frostburg.edu/cgi-bin/senese/tutorials/sigfig/index.cgi



TYPES OF ERRORS:1. Random errors

related in taking measurements on imperfect tools (balances, cylinders, etc) can be estimated and the degree of error can be calculated. are related to insufficiently controlled variations in experimental conditions Affect precision, but not accuracy Cannot be eliminated

2. Systematic error Usually are related to improper experimental design or adjustment of experimental apparatus. Sometime related to a particular method. These errors systematically distort the observations. do not affect precision, and can, in theory, be eliminated.

Examples : Sticking or leaking gas syringes. Calibration errors in pH meters. Stop clock running low. Changes in external influences such as temperature and atmospheric pressure affect the measurement of gas volumes, etc. Personal errors such as reading scales incorrectly. Unaccounted heat loss. Liquids evaporating.

AccuracyAccuracy can be expressed as a percent error, if the true value is known.

DEALING WITH UNCERTAINTIES (use of simple calculator or online calculator)


WHEN MULTIPLY OR DIVIDING, ADD THE PERCENTAGE UNCERTAINTIES, CONVERT THE TOTAL % UNCERTAINTY BACK TO AN ABSOLUTE

UNCERTAINTY


Absolute and Relative Uncertainty

A. Absolute uncertainty is an expression of the uncertainty of a measurement. Usually, it is plus-or-minus the last digit = absolute uncertainty. For example, 10.20 g ==> implies that the measurement is +/- 0.01 g so, Absolute uncertainty = +/- 0.01 g

B. Relative uncertainty = (absolute uncertainty)/measurement. For example, 10.20 g ==> absolute uncertainty = +/- 0.01 g relative uncertainty = (0.01 g)/10.20) x 100 = 0.09803 % = 0.001%

Multiple Readings If more than one reading of a measurement is made, then the uncertainty increases with each reading. For example:

Trial Volume of acid1 10.0 +/- 0.1 cm3

2 10.0 +/- 0.1 cm3

3 10.0 +/- 0.1 cm3

Total 30.0 +/- 0.3 cm3

So the rule is : WHEN ADDING OR SUBTRACTING UNCERTAIN VALUES,

ADD THE ABSOLUTE UNCERTAINTIES

If a set of data is multiplied or divided, convert the absolute uncertainties to percentage uncertainties and add them together. When finished,

convert the total uncertainty back to an absolute uncertainty: eg. number of moles = concentration x volume

= (0.53 +/- 0.05 mol.dm-3) x (0.50 + 0.01 dm3) = (0.53 +/- 9% mol.dm-3) x (0.50 +/- 2% dm3) = 0.265 +/- 11% mol. = 0.265 +/- 0.029 mol = 0.27 +/- 0.02 mol

UNCERTAINTY CALCULATOR



Assume that you wish to use the ideal gas law to calculate the pressure of a gas:

Start up the applet (http://www.colby.edu/chemistry/PChem/scripts/error.html) and then type the formula into the Equation box, without the equal sign as follows:

After pressing [calculate], the Variables window will be displayed:

Then type in the values for the various parameters and their uncertainties. For example, you would type in 0.53 for n and 0.02 for the Uncertainty for n. The program also has available a table of constants and their uncertainties. Click the mouse in the R Value box, then click on the [Constants] button. The constants window will be displayed, as shown.

Clicking on the check box for the line that reads "R =0.08205783" will automatically enter the value and its uncertainty in the Variables window. After you type in the values for T and V the Variables window should appear.



Now if you click on the [Calculate] button the final result and its uncertainty will be displayed:

Your final pressure would be 1.282 atm with an uncertainty of ±0.057.

RESOURCES



http://occ.ibo.org Chemistry Guide, Internal Assessment

http://occ.ibo.org Chemistry Resource by Ruth Sanderson

http://occ.ibo.org Chemistry Resource by Julie Sykes

http://antoine.frostburg.edu/chem/senese/101/measurement/index.shtmlhttp://www.sbuniv.edu/~ggray/CHE3345/chp5.htmlhttp://home.comcast.net/~christylthomas/aplaberrors.pdf#search='types%20of%20errors%20chemistry ' http://www2.truman.edu/~jmccormi/LabManual/StatisticsFundamentals_files/StatisticsInChemistry.pdf#search='types%20of%20errors%20chemistry ' http://www.sciencegeek.net/Chemistry/chempdfs/ch02sigs.pdf#search='RULES%20chemistry%20significant%20figures'http://dbhs.wvusd.k12.ca.us/webdocs/SigFigs/SigFigRules.htmlhttp://www.colby.edu/chemistry/PChem/scripts/error.html


http://dbhs.wvusd.k12.ca.us/webdocs/SigFigs/SigFigRules.html

http://www2.truman.edu/~jmccormi/LabManual/StatisticsFundamentals_files/StatisticsInChemistry.pdf#search='types%20of%20errors%20chemistry

http://www2.truman.edu/~jmccormi/LabManual/StatisticsFundamentals_files/StatisticsInChemistry.pdf#search='types%20of%20errors%20chemistry

http://home.comcast.net/~christylthomas/aplaberrors.pdf#search='types%20of%20errors%20chemistry

http://www.sbuniv.edu/~ggray/CHE3345/chp5.html

http://antoine.frostburg.edu/chem/senese/101/measurement/index.shtml

http://occ.ibo.org/

http://occ.ibo.org/

http://occ.ibo.org/

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