IB Lab Report Format Guide
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1.1 Title – Precise and short statement that reflects clearly what the lab is all about.
1.2 Problem/Research question (R.Q.) – this is a clearly written question on the problem at
hand which must include the independent and dependent variables. R.Q. is developed from the
general aim given by the teacher. If living organisms are used in the investigation, both the
common name and binomial/scientific name must be given.
Example: How does increase in water temperature affect the rate of photosynthesis measured
in volume of oxygen produced per minute in Canadian Pondweed (Elodea canadensis)?
1.3 Hypothesis – a tentative answer to R.Q., i.e. prediction on the effect of manipulating
independent variable on dependent variable that is based on known facts. Hypothesis must be
explained using information gained through preliminary research of the topic. You can’t do a
good lab without reading on the current state of knowledge on the concept(s) you want to
experiment on. In research, we stand on the shoulders of the giants in order to look tall! All
literature referred to (books, journals, websites, newspapers etc) must be cited and referenced.
1.4 Variables – anything in an experiment that can be changed and influence its outcome(s).
List the independent, dependent and all controlled variables. Each controlled variable
mentioned should be addressed in the procedure explaining how it will be maintained at
constant level or monitored during the experiment if it cannot be manipulated.
1.5 Materials, Apparatus and Reagents – A listing of all requirements (materials, apparatus
and reagents) used in the experiment. Specific sizes of equipment or apparatus, such as 100 ml
graduated cylinder or 50 ml beaker, should be stated. Solutions used and their precise
concentrations and volume should also be listed. The model and manufacturer of any complex
apparatus should be clearly stated.
1.6 Procedure/Method – The procedure should be in numbered steps. It is preferred that it be
written in passive voice i.e. no use of words such as “I”, “we”, “they”, “you” etc. The procedure
should describe: how the independent variable is manipulated; how the controlled variables are
maintained at constant value(s) i.e. how they are going to be kept constant throughout the
experiment and how sufficient relevant data will be collected. Relevant data means it pertains
directly to the research question or the hypothesis. The data collected must be shown to be
adequate so as to allow some sort of analysis involving statistics and/or graphing. There should
be included an adequate data range (5) and an adequate number of data values within each
range (5). Any standard methods i.e. measurement techniques used in the experiment should
be cited in text, fully referenced in a footnote or in the bibliography.
A diagram, picture or a photo of experimental set-up maybe included if it helps in explaining the
procedure. Such diagrams, pictures or photos should be annotated to illustrate how the
variables are specifically involved in the procedure.
2.1 Raw data – actual quantitative (numerical measurements of the variables) and associated
qualitative (descriptive observations) data collected during the experiment. Quantitative raw
data should be presented in a table. The data table should have: a clear title that includes the
independent and dependent variable; columns that are clearly annotated with a heading (the
independent variable is always on the left hand of the table); units are clearly stated along with
the uncertainty of measurements; and the same level of precision (number of decimal places)
used for all recorded values. Significant digits in the data and the uncertainty in the data must
be consistent. Do not split a data table between pages. If absolutely necessary, due to large
volumes of data, include title and complete column headings on the second page. Table(s)
should be numbered in a systematic manner (e.g. table 2.1, 2.2 etc).
IB Lab Report Format Guide
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2.2 Data processing – involves, for example, combining and manipulating raw data to
determine the value of a physical quantity (such as adding, subtracting, squaring, dividing), and
taking the average of several measurements and transforming data into a form suitable for
graphical representation. In this section give an explanation of the manner you have chosen to
process your raw data. Justification should be given as to how the processing will allow the
hypothesis or research question to be adequately fulfilled. One example showing how you
actually transfer one piece of raw data into processed data using the explanation in this section
should be included. If your processing utilizes a graphical approach, explain how.
2.3 Presentation of Processed Data – decide upon a suitable method for presentation of your
processed data such as spreadsheet, table, graph, chart, flow diagram etc. Use clear,
unambiguous headings for all tables, charts or graphs used. If a graph(s) is/are used be certain it
is properly done including: appropriate scales, labelled axes with units, and accurately plotted
data points with a suitable best-fit line or curve. Remember to take into account the
uncertainties associated with the raw data. A suitable best fit line or a curve and error bars should
be used for treating uncertainties. All graphs(s) should be numbered in a systematic manner
(e.g. graph 2.1, 2.2 etc).
3.1 Conclusion – a clear restatement of determined numerical quantity (e.g. population,
optimum pH, optimum temperature etc), or a statement of the relationship found between the
independent variable and dependent variable. Analyse the presented processed data; this may
include comparisons of different graphs/tables or descriptions of general trend shown in graphs.
Justify your conclusion by giving a biological explanation to the results obtained. Compare your
results to already known and accepted value of a physical quantity from the scientific literature.
This may help to establish validity of the results. Be certain to cite and reference any literature
that you refer to. Remember, a hypothesis can only be supported or refuted by the data
collected but it cannot be proven!
3.2 Evaluation of Experimental Design and procedure - Comment on major weakness of the
investigation (sources of error and limitations) and how they affected the accuracy, validity and
reliability of data collected. Do not include your personal mistakes. Discuss the processes, use of
equipment (precision and accuracy of the measurements) and time management. Do error bars or
statistical analysis indicate valid, reliable data? Stick to major weaknesses, sources of error and
limitations but do not give an overly long list of trivial points.
3.3 Suggestions for Improving the investigation – suggest realistic ways of improving your
investigation based on the weaknesses, sources of errors and limitations identified in part 3.2
above. Specifically mention modifications that need to be done on experimental design,
techniques, and the data range. Specify how your modifications will improve the reliability,
accuracy and validity of the results.
4.1 References – a list of all other peoples’ work that you have referred to and cited in your
work (such as textbooks, websites, journals, magazines etc) in preparing for your lab and when
writing the lab report. Literature review must be done when writing sections 1.3, 1.6 and 3.1 of
your lab report. Use the Chicago referencing style for both your in text citation and referencing.
For guidance on citation and referencing visit http://library.curtin.edu.au/ and follow the following
links: study and research tools; referencing; Chicago Author - Date
IB Lab Report Format Guide
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Internal Assessment Criteria
Design (D)
Levels/marks
Aspect 1
Defining the problem
and selecting variables
Complete/2
Partial/1
Not at all/0
Aspect 2
Controlling variables
Aspect 3
Developing a method
for collection of data
Formulates a focused
Designs a method for the Develops a method that
problem/research
effective control of the
allows for the collection of
question and identifies the variables.
sufficient relevant data.
relevant variables.
Formulates a
problem/research
question that is
incomplete or identifies
only some relevant
variables.
Designs a method that
makes some attempt to
control the variables.
Develops a method that
allows for the collection of
insufficient relevant data.
Does not identify a
problem/research
question and does not
identify any relevant
variables.
Designs a method that
does not control the
variables.
Develops a method that
does not allow for any
relevant data to be
collected.
Data collection and processing (DCP)
Levels/marks
Aspect 1
Recording raw data
Complete/2
Partial/1
Not at all/0
Aspect 2
Processing raw data
Aspect 3
Presenting processed
data
Records appropriate
Processes the quantitative
quantitative and
raw data correctly.
associated qualitative raw
data, including units and
uncertainties where
relevant.
Presents processed data
appropriately and, where
relevant, includes errors
and uncertainties.
Records appropriate
quantitative and
associated qualitative raw
data, but with some
mistakes or omissions.
Processes quantitative
raw data, but with some
mistakes and/or
omissions.
Presents processed data
appropriately, but with
some mistakes and/or
omissions.
Does not record any
appropriate quantitative
raw data or raw data is
incomprehensible.
No processing of
quantitative raw data is
carried out or major
mistakes are made in
processing.
Presents processed data
inappropriately or
incomprehensibly.
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Conclusion and evaluation (CE)
Levels/marks
Aspect 1
Concluding
Complete/2
Partial/1
Not at all/0
Aspect 2
Evaluating
procedure(s)
Aspect 3
Improving the
investigation
States a conclusion, with Evaluates weaknesses
justification, based on a
and limitations.
reasonable interpretation
of the data.
Suggests realistic
improvements in respect
of identified weaknesses
and limitations.
States a conclusion based Identifies some
on a reasonable
weaknesses and
interpretation of the data. limitations, but the
evaluation is weak or
missing.
Suggests only superficial
improvements.
States no conclusion or
Identifies irrelevant
the conclusion is based on weaknesses and
an unreasonable
limitations.
interpretation of the data.
Suggests unrealistic
improvements.
Manipulative Skills (MS) – is assessed summatively over the whole course
Levels/marks
Complete/2
Partial/1
Not at all/0
Aspect 1
Aspect 2
Aspect 3
Following instructions*
Carrying out
techniques
Working safely
Follows instructions
accurately, adapting to
new circumstances
(seeking assistance when
required).
Competent and
Pays attention to safety
methodical in the use of a issues.
range of techniques and
equipment.
Follows instructions but
requires assistance.
Usually competent and
Usually pays attention to
methodical in the use of a safety issues.
range of techniques and
equipment.
Rarely follows instructions Rarely competent and
Rarely pays attention to
or requires constant
methodical in the use of a safety issues.
supervision.
range of techniques and
equipment.
IB Lab Report Format Guide
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Personal skills (PS) - assessed once only and this will be during the group 4 project.
Levels/marks Aspect 1
Complete/2
Partial/1
Aspect 2
Self-motivation and
perseverance
Working within a team
Approaches the project
with self-motivation and
follows it through to
completion.
Collaborates and
communicates in a group
situation and integrates
the views of others.
Completes the project but Exchanges some views
sometimes lacks selfbut requires guidance to
motivation.
collaborate with others.
Lacks perseverance and
motivation.
Not at all/0
Aspect 3
Self-reflection
Shows a thorough
awareness of their own
strengths and
weaknesses and gives
thoughtful consideration to
their learning experience.
Shows limited awareness
of their own strengths and
weaknesses and gives
some consideration to
their learning experience.
Makes little or no attempt Shows no awareness of
to collaborate in a group their own strengths and
situation.
weaknesses and gives no
consideration to their
learning experience.
The maximum mark for each criterion is 6 (representing three “completes”).
D
× 2 = 12
DCP × 2 = 12
CE
× 2 = 12
MS
×1=6
PS
×1=6
This makes a total mark out of 48.
The marks for each of the criteria are added together to determine the final mark out of 48 for
the IA component. This is then scaled at IBCA to give a total out of 24%.