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                                            IDENTIFYING THE CONTEXT

Identifying the context (6)
The environmental issue is the overarching reason for your lab. (Think is it in the book). EVERYTHING IS LINKED BACK HERE! 

Large ideas could include but are not limited to: 

  • increased use of fossil fuels 

  • desertification

  • eutrophication of water due to farming techniques

  • loss of biodiversity 

  • overpopulation/ urbanization

  • overconsumption of groundwater

Research Question:  

  • Should arise from a broader area of environmental interest (the context), so that in conjunction with evaluating the research process and findings of your study, you will be able to discuss the extent to which the study applies to the environmental issue that interests them at a local, regional or global level (the application)The research questions is clearly stated and precisely formulated.

  • Explain the broader issue and then distill this to create a focused research question

  • Has relevance to a broader issue but is at a meaningful scale for the time frame investigated

  • Is it testable?

  • Does it contain both independent and dependent variables?

  • Is it focused and clear (do people know exactly what you are trying to do without asking questions)?

  • The research question includes the scientific name of the organism, if relevant (Genus species).

  • The research question can be used to formulate a hypothesis predicting the relationship between the DV and IV.

The discussion should lead you to develop creative thinking and novel solutions or to inform current political and management decisions relating to the issue. For example, if you carry out a study on the impact of wind turbines that have been erected in the vicinity of your school, you may suggest solutions for the erection of wind turbines in other areas based on your findings.

Whatever you choose, should have a local or global connection somewhere specific that you are looking for. 
Example: Urbanization of the Dallas, TX, USA metro area is causing and increasing demand for water. 

Warnings: Narrow your focus from overly broad issues to something specific to a country or local connection. 

  • Broad: Climate Change

  • More Focused: The destruction of the Trinity River Deciduous Forest in Dallas, TX, the USA due to urbanization.


  • Broad: Air pollution

  • More focused: Use of coal plants in Lima, Peru and their energy choices ​

WHY?!  Specific, clear, know what you are going to do without reading it, independent and dependent variables are clear. 


  • Explain everything the reader would need to know before doing the investigation?

  • Explain the science behind the investigation? The Why and how of it working?

  • Cite your sources (in text and work cited)?

  • Explain how science is connected to your investigation research idea?

  • The background sets the research question into context.

  • Justify the connection between your study and the bigger problem that was the stimulus for your investigation

  • Background information provides sufficient information about the environmental context

  • Appropriate and relevant background correctly described and explained.

  • Citations relevant to the research question are used.

  • Background information is used to form a hypothesis.

Environmental Issue:

  • Identify an environmental issue in relation to your RQ (Should be done first!)

  • Discuss the environmental issue in the context of your Research Question

  • Develop a range of arguments within the focus of the issue

  • Explain how the issue is connected to your Research Question

Local/Global Connection:

  • Provide the reader with an understanding of how the RQ and issue are connected to a local and or global environmental issue

  • Clearly explain how these connections are relevant to your RQ

  • Provide enough background information for the reader to understand these connections

If you are using any living organisms, or products from living organisms, such as seeds from a certain plant, give the most precise name you can and give the scientific name if possible (e.g. Phaseolus vulgaris for kidney beans).

The second and third in a series from Science Sauce about Choosing Your Topic and Writing Your Report

Identifying the context

You need to state explicitly why you have selected the research question chosen, and your personal interest in the topic.


This criterion assesses the extent to which you have developed appropriate methods to gather data that is relevant to the research question. The data could be primary or secondary, qualitative or quantitative, and may utilize techniques associated with both experimental or social science methods of inquiry.

Here, the emphasis is on the development of the methodology of the investigation. ESS allows for a broad range of studies that could be scientific or social-science based. The criterion has been designed to allow for the assessment of a wide range of types of study. So, for example, when justifying the choice of the sampling strategy, this could mean explaining the method of sampling recipients in a questionnaire, but could also mean the selection of the number of repeats and the control of variables in a laboratory test. The important idea is that the methodology is appropriate to the focused research question, that there is sufficient data generated to lead to a conclusion, and that the rationale is explained clearly.

​Many ESS studies will involve ethical or safety considerations. You must address this, where necessary, paying attention to the IB animal experimentation policy (which includes guidelines on working with human subjects).


Data Collection Ideas

·       Values and Attitude Surveys and Questionnaires

·       Interviews

·       Fieldwork

·       Ecosystem Modelling

·       Models (physical, software, mathematical)

·       Field Manipulation Experiments

·       Lab Work

·       EIAs

·       Secondary Data (must use unique data)

·       Qualitative and Quantitate Data

·       A Combination of any of the above

Reference the video below from Science Sauce

Planning (6)

Although not required by the IB Organization, for many investigations it is appropriate for you 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.” 

Not investigations will have a hypothesis. However, they help you focus your ideas. Be sure that your hypothesis is related directly to your research question

Also, justify your hypothesis. This should be a brief discussion (paragraph form) about the theory or ‘why’ behind the hypothesis and prediction.  Be sure the hypothesis is related directly to the research question and that the manipulated and responding variables for the experiment are clear. 


·       IV correctly identified with units and levels, including how the levels were chosen.  

·       Minimum of five levels of IV over a suitable range (unless comparing populations or correlating variables without manipulation).

·       DV (as directly recorded and/or calculated) correctly identified with units.

·       Important CV identified, with the potential impact of each discussed.  Validity measures and/or control group are not misunderstood as a CV.

·       List or photo of apparatus and materials including size, graduation, and uncertainty.

·       Reference to preliminary trials, if completed.

·       Method to change and measure IV fully detailed (including tools, units, and uncertainty).

·       Method for measuring DV fully detailed (including tools, units, and uncertainty).​

·       Sufficient repeats of DV measurement to ensure reliability and allow for statistics (5 for SD, ​10 for T-test, 20+for correlation).

·       The collection of data from other students or sources is explained and referenced.

·       If sampling only a portion of a population, including the method for ensuring the sample was randomly selected.

·       The method for maintaining and measuring CV is detailed (including tools, units, and uncertainty).​

·       The method includes validity measures to ensure experimental measurements are valid and consistent.​

·       The method is clear, specific, and easily replicated as described.​

·       Full citation of a published protocol (or elements of), if used.

Make a list of materials needed. 

·       Be as specific as possible (example:  “50 mL beaker instead of ‘beaker’). 

·       A well-labeled diagram or photograph of how the experiment is set up may be appropriate.

·       Be sure the diagram includes a title and any necessary labels.

State or discuss the method (procedure) that was used in the experiment. 

·       should be in the form of a step-by-step direction. 

·       provide enough detail so that another person could repeat your work by reading the report! 

·       you don’t have to go into detail about standard, well-understood actions. If a standard technique is used, it should be referenced.

·       if something is done in the procedure to minimize an anticipated error, mention this as well.  (Example:  “Carefully cutting plant stem underwater to reduce the effect of air on transpiration rate.”) 

·       clearly state how to collect data.  What measuring device was used, what data was recorded, and when? Or what qualitative observations were looked for (such as color change)?

·       must allow the collection of sufficient relevant data.  As a rule, the lower limit is five measurements or a sample size of five. Very small samples run from 5 to 20, small samples run from 20 to 30, and big samples run from 30 upwards. Obviously, this will vary within the limits of the time available for an investigation.

“Control of variables” refers to the manipulation of the independent variable and the attempt to maintain the controlled variables at a constant value.

·       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 and monitored. ​

·       if using a known experimental protocol, you must explain how you modified the standard method to make it your own. 

Justification of Sampling:

·       Justify your method

·       Indicate why you choose to collect data the way you did

·       Verify that the data is random and unbiased (specifically in survey data)

·       Indicate how you made sure to collect sufficient and relevant data

Safety, Ethics and Environmental Issues:

·       ​Safety issues fully considered (including human consent forms if needed).

·       Ethical issues fully considered (including animal experimentation policy if needed).

·       Environmental issues fully considered (such as reduction of waste and disposal of chemicals).

·       List any safety precautions that must be taken during the lab, including personal and environmental concerns. 

·       Many ESS studies will involve ethical or safety considerations. You must address this, where necessary, paying attention to the IB animal experimentation policy (which includes guidelines on working with human subjects), and should write about their strategies for upholding safety and/or ethical standards in the report.

Risk Assessment Forms










In line with the poster Ethical practice in the Diploma Programme, the following guidelines exist for all practical work undertaken as part of the Diploma Programme.

·       No experiments involving other people will be undertaken without their written consent and their understanding of the nature of the experiment.

·       No experiment will be undertaken that inflicts pain on or causes distress to humans or live animals.

·       No experiment or fieldwork will be undertaken that damages the environment.

Find out more in Animal Experimentation


Survey research involves the collection of information from a sample of individuals through their responses to questions.. It is an efficient method for systematically collecting data from a broad spectrum of individuals and educational settings

One important point when using surveys and questionnaires is to have some quantitative data. One way of doing this is to have responses that are open-ended and then to categorize them into groups according to the investigation. 

Must be:
- A set of questions specifically designed to address a particular issue
- A printed form that participants complete themselves.
- A printed form that the interviewer completes or Online 
- Delivered via email.
- Must be given to a statistically valid number of participants (minimum 30 people).
- Can be used to collect standardized data. The survey consists of eight questions. All are either multiple-choice (participants were only allowed to choose one option), or free-response question (no word limit)

Things to consider:

·       How much data do you need to collect? A general rule of thumb is that a minimum of thirty surveys are needed for investigating a correlation; at least thirty (ideally fifty) surveys per independent variable - so if gender was the independent variable then you would need 30 females and 30 males completing the surveys.

·       What is the question you are trying to answer? What is your independent variable? What data will help answer your question?

·       What type of data will be more meaningful and allow you the ability to analyze the data statistically? Questions allowing an answer on a scale of 1-5 or 1-10 are generally better than yes/no questions.

·       How will you avoid bias in your data and how will you cope with "no response"?

·       Will you trial your questions? How might you do this and refine your questions?

·       How will you encourage people to participate in your survey?

·       How will you allow participants to know your scale of reference, e.g. 1 is bad, 5 is good or 1 disagrees, 5 strongly agrees?

·       What tool will you use for your survey?

·       What ethical considerations do you need to make?

Here is a great link in how to design surveys - Survey Research

Secondary Data Bases

​It is possible to use databases as the source for IA investigations, though this would need to be carefully managed. A challenge with using informatics/databases in IA work will be generating quality questions that can be explored effectively. However, this must be a unique analysis.

It is important that you consult relevant and reliable sources in your research. You need to evaluate all the sources that you use for your secondary research.

Example of how you treat secondary data
My investigation of the research question was held in the following ways:

1.    An analysis of secondary data from a variation of reports and books regarding xxx data, number of xxx, year span, economic value, social value, impact data, etc. Collected data that will be looked at will range from 1xxxx - XXXX.

2.    All the following data will be regarding countries and regions in xxx, mostly focusing on countries such as XXXX.

3.    From all the data gathered I will be able to produce my graphs (referencing the data found) and be able to make connections and links between XXXX and the number of XXXX, and the loss of XXXX.


World Bank
Search on this database for data on global issues and banking. The World Bank Data is an open data initiative of the World Bank group that collects statistical data that are essential to help alleviate poverty.


One World in Data​
Search on this database for global issues data such as poverty, disease, hunger, climate change, war, existential risks, and inequality.


Shows estimated current numbers based on statistics and projections from the most reputable official organizations such as United Nations Population Division, World Health Organization (WHO), Food and Agriculture Organization (FAO), International Monetary Fund (IMF), and World Ban


​​Learn what life is really like behind income statistics.


Inequality Facts
Data on inequalities -- income, wealth, global, health, gender, racial economic inequality.


Global Refuge Agency
Data about refugees, displaced communities, and stateless people.


ILO Statistics and Database
Statistics about labor around the globe such as employment and unemployment, child labor, wage, occupational injuries, etc.


UNESCO Atlas of the World's Languages in Danger
Data on world languages. The websites include an interactive map that shows different languages in a specific country.


World Demographics
Data on world population, sex ratio (males vs. females), population pyramid, population by broad age group, age structure and sex (all age groups), median age, dependency ratio, fertility rate, life expectancy, infant and children under 5 mortality, urbanization and population density.


WTO Data
Statistical data related to WTO issues. (WTO is an intergovernmental organization that is concerned with the regulation of international trade between nations.)


Data, information, and researches about global education, women in science, research,


Global Economic and Financial Data
IMF data for GDP growth, inflation, unemployment, payments balances, exports, imports, external debt, capital flows, commodity prices.


State of Global Air
Raw data and other resources on air pollution and health data.


World Health Organization
​Data related to the world and country-specific public health and medicine.


Data about agriculture production, emission, economy, land use, and forestry


Agriculture Market Database
World and country-specific supply and demand data of commodities -- maize, wheat, rice, and soybean.


Global Food and Agriculture Data
Statistics on water resources and management, fishery and aquaculture, food consumption behavior, domestic animals, and GMO  plants.


US Climate Map and Data
Data snapshot and search data set on US climate


USDA Nutrients DataBase
An integrated data system that provides expanded nutrient profile data and links to related agricultural and experimental research.


NOAA Climate and weather databases
Statistical analysis on climate and weather


Global water information system, known to be the most quoted source on global water statistic


Global Drinking Water Statistics
Global statistics on drinking water, water sanitation, and health


Sustainable Development Goals
SDG Tracker that measures the progress of the UN Sustainable Development Goals


Global Invasive Species Database
Database about alien and invasive species that negatively impact biodiversity. 


Global Footprint Network Open Data
Data related to ecological footprint.


World Tourism Statistics
Tourism statistics for all the countries and regions around the world. Data includes inbound, domestic and outbound tourism, as well as on tourism industries, and employment.


UN Environment Programme World Conservation Monitoring Centre
Data and knowledge-based tools to help understand how we depend on and impact biodiversity


Information on a country's geography, people, and marine and coastal resources. In addition, it includes quantitative statistics on various geographic and socio-economic parameters


UCN Red List Summary Statistics
Summary statistics of threatened species


Facts and Figures on Biodiversity
Descriptive statistics on current world biodiversity.


CITES Endangered Species Database
​Centralized portal for accessing key information on species of global concern.


World Tropical Forest Loss
Summarize statistics of global forest loss.


International Energy Agency Data and Statistics
Data related to energy such as supply and consumption, import/export, waste, and carbon emission. Data available can be filtered by energy type i.e. natural gas, coal, etc


EBSCO - Green File
A bibliographic database of information about environmental concerns.


IRENA Statistics
Statistics on renewable energy


Resilience Alliance
An international, multidisciplinary research organization that explores the dynamics of social-ecological systems and resilience and tipping points 


Environmental Data Initiative (EDI) 
Contains data and metadata from publicly funded research. Data can be searched through their portal.


Measurement Precision

Unless there is a digital display, always measure to one digit beyond the smallest unit of CERTAIN measurement of the tool.  For example, if you use a ruler that can accurately measure to the tenth of a centimeter, your measurement would be to the hundredth of a centimeter.  The number of significant digits should reflect the precision of the measurement.

There should be no variation in the precision of raw data. The same number of digits past the decimal place should be used.  For data derived from processing raw data (i.e., means), the level of precision should be consistent with that of the raw data.







You may need to estimate the degree of precision sometimes especially with stopwatches. Digital stopwatches are said to be accurate to 0.01s but human reaction time is only +/-0.1s.

For electronic probes, you may have to go to the manufacturer's specifications (on their web site or in the instructions manual).

All measurements have uncertainties and are only as accurate as the tool being used. For general purposes, the accuracy of a measurement device is one half of the smallest measurement possible with the device.  To determine uncertainty:

·       Find the smallest increment of measurement on your measurement device

·       Divide it into two

·       Round to the first non-zero number

So, for example, the rulers in class measure to the millimeter (0.10 cm).  Therefore, the ruler’s measurement uncertainty is +/- 0.05 cm.  ​

The numerical value of a ± uncertainty value tells you the range of the result. For example, a result reported as 1.23 ± 0.05 means that the experimenter has some degree of confidence that the true value falls between 1.18 and 1.28.

·       Mass of a penny on a centigram balance:  3.12g (+/- 0.05g) 

·       Temperature using a typical lab thermometer:  25.5°C (+/-  0.5°C) 

Experimental uncertainties should be rounded UP to one significant figure. Uncertainties are almost always quoted to one significant digit and we round up because it’s better to suggest higher uncertainty than to imply there is less uncertainty.

·       Wrong: ± 12.5 mL

·       Correct: ± 20 mL

The measurement should have the same number of digits (decimal places) as the uncertainty. It would be confusing to suggest that you knew the digit in the hundredths (or thousandths) place when you admit that you were unsure of the tenths place. 

·       Wrong: 1.237 s ± 0.1 s

·       Correct: 1.2 s ± 0.1 s 

​Just as for units, in a column of data students can show the uncertainty in the column heading and don’t have to keep re-writing if for every measurement in the table. 

The system of units used in science is called the International System of Units (SI units).  In the table below are some of the more common SI units













The following example shows different ways to express the same unit. 

·       Oxygen consumption (milliliters per gram per hour)

·       Oxygen  consumption (ml/g/h)

·       Oxygen  consumption (ml g-1 h-1)


Planning Rubric










The fourth in a series of videos from Science Sauce focusing on where to get your Data












The sixth in a series of videos from Science Sauce focusing on your Planning


·       Many students lose marks for not knowing the difference between independent, dependent, and controlled variables. You need to clearly identify these variables in your report: the terminology is not compulsory, and some students refer to the

variable that they will manipulate and that which will respond and those that will be held constant. The concepts of ‘control’ and ‘control variables’ are often confused: control variables are required for a fair test, where only one variable is changed

(the independent variable) and the rest kept the same (the control variables).


The dependent variable is the one you are measuring. A ‘control’ refers to an experiment where the independent variable is removed so that the scientist can see what happens when the factor that they think is having the effect is taken away – this proves that the independent variable is the one having the effect rather than other factors. In ecological IAs, it may not be possible to control other variables as you will be working out-of-doors where conditions vary: in these investigations, you need to say that you will monitor other variables that may affect your dependent variable.

·  When explaining your sampling method, you must outline how those samples are to be selected, ensuring that there is no significant bias. You need to be able to develop a method that results in a ‘fair’ test or one in which reasonable attempts have been made to remove bias. For example, a practice that includes a sampling of quadrats (pages 135–136) should include some description of how these are to be selected.


It is not sufficient simply to indicate that quadrats were selected randomly – the method to ensure randomness should be outlined. If you are comparing the germination of plants under different salinity conditions, for example, the method should indicate how temperature, moisture, and other variables are being controlled in order to ensure that the results are comparable.

·    Most students succeed in obtaining data that are relevant to the question or topic that is being studied but lose marks by collecting data insufficient in quantity. Normally, five is the minimum number of samples required per site, treatment, repetition, and so on. For example, if you are measuring changes in the rate of oxygen release with respect to light intensity in Elodea, it would be expected that you would take at least five readings for each light intensity.



Lack of sufficient data can have knock-on effects for other marking criteria; for example, if only a single measurement is collected per treatment, the data does not lend itself for processing and by extension is not suitable for the presentation of processed data. When carrying out ecological fieldwork, time constraints can be problematic, and it is appreciated that in these cases you may need to collect fewer than five samples or transects. In such cases, three may be acceptable, but you need to explain in your report about the time constraints you encountered.

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