IA Check # 2—HELPFUL HINTS

Materials: Make a list of ALL materials used in the experiment

• The sizes of glassware such as beakers, flasks, etc.

• The concentration of chemicals (eg hydrochloric acid, 2.0 M).

• The amount of each solution or material (eg 200 mL/ g)

• Brand name of materials

• If using plants, make sure to identify the common and SCIENTIFIC NAME

Procedure:

Before writing your methodology, ask yourself if your planning will result in sufficient numerical data so that techniques of analysis such as standard deviation can be used. One of the most important parts of your methodology is to make sure that you will be able to collect as large a sample of data as possible for each range of variable that you have chosen.

You will need to test each of your levels of IV a total of 5 times each—as well as your control being tested 5 times [ATLEAST]. This will ensure enough data was used to formulate a conclusion and will help ensure results are valid.

Ex: Continuing with our example of light intensity’s effect on photosynthesis’ oxygen production, you would run your entire lab a minimum of 5 times to gather enough data.

  1. You should have a drawing or picture of the apparatus, which is annotated. It must be LABELED- to tell what each item is AND what it is being used for. You may add a photograph, but it also needs annotation. A diagram of how you set-up the experiment may be appropriate, especially for more complicated experiments. Be sure your diagram follows the rules for lab drawings (i.e. have clear labels, make the diagram large enough to see and understand, etc.).
  1. Then you need to write out what the procedure actually is. DO NOT write this as a narrative, it should be a numbered, step-by-step list.DON’T LEAVE OUT ANY STEPS. Do not assume anything. Write this as if the person is a student in middle school and doesn’t know how to do a lab. Be Specific about measurements, don’t say get some water, say HOW MUCH. The procedure is a directions list. Someone should be able to read them and repeat your lab EXACTLY as you did it. EXPLAIN EVERYTHING.
  1. Make sure to tell us how you plan on collecting your data and HOW TO MEASURE COLLECTED DATA

●Have you clearly described how the IV is integrated into the steps? The dependent variable? All the controlled variables?

●If glassware is going to be heated, think of what you might need when moving it once it is hot, such as metal tongs.

●If the experiment involves cutting something, do not forget to mention the scalpel (if necessary)

●For chemical solutions, you must be precise about the concentration (in % or moles per litre) as well as the volume (in mL).

●Think about materials to transport things: the manipulation of liquids will probably require the use of pipettes or syringes, the manipulation of powdered chemicals will require a spatula, and if you need to weigh the powder, how will you put it on the balance? Did you ask for a balance?

●If you ask for any electronic probes (for temperature, light, humidity, etc.), be sure to ask for an interface for connecting them to the computer or a data-logging device that does not require a laptop

●Thermometers come in three forms: glass, electric, and probes. Be sure to state which ones you need.

●If an experiment needs to be saved overnight from one lesson to the next, did you ask for a tray or box to keep the samples in? Are they labeled?

(Damon, McGonegal, Tosto, & Ward, 2014)

Personal Engagement:

For your IA- You will have to explain how you have modified a standard method and made it your own design. Is your personal approach and engagement with this investigation obvious to the reader?

Exploration: Aspect #3:

Safety and Ethical Consideration: Show full awareness of the significant safety, ethical, or environmental issues that are relevant to the methodology of the investigation. If there are no ethical concerns, then include that information. You may also want to include medical information if safety is breeched.

Analysis: Aspect #1:

There are two types of data that can help shape research questions in the sciences: quantitative and qualitative data. While quantitative data focuses on the numerical measurement and analysis between variables, qualitative data examines the social processes that give rise to the relationships, interactions, and constraints of the inquiry.

  1. Qualitative Data: Write out your observations/ descriptions during the lab. What do you see? These are descriptions of things that cannot be expressed in numbers. Be as specific as possible. NOT NUMBERS. For example if comparing temperature change, you might compare what materials appeared to get hotter at a faster rate than others. Etc.

●Drawings, diagrams, annotated photos

  1. Quantitative Data:(Raw Data Table) Show your data that you collected in an organized form. Make sure the table is properly labeled. . You may have done the experiment with other people, and even if you have the same data, you will not have the same presentation. Include units in the headings and uncertainties in the headings/ OR footnotes of each table.
  2. No need to include a raw data graph.

●Give the table a number and a title (e.g. Table 2: Pea seed characteristics).

●Set up the rows and columns in a neat and orderly way to facilitate interpretation, e.g. values that have been measured using the same tool, such as a thermometer, should be aligned in the same column.

●In the headings of each column, put three things: the name of what was measured, the appropriate units, and the degree of precision

●As a rule of thumb, the degree of precision is half the smallest unit that the apparatus can measure. For example, if a ruler has a 1 mm scale the precision can be expressed as +/-0.5 mm. The degree of precision may also be found on the measuring device itself or in documentation.

●Put only numbers in each box (cell) of the table, no units, and be sure to have only one value in each box of the table. Do not include uncertainty symbols +/- or (approx symbol) in the cells with the new raw data. One exception is a negative sign: this is allowed with the raw data.

●The number of decimal point should be in accordance with the degree of precision, e.g. if a thermometer is precise to +/-0.5(degree symbol)C, then all the numbers in the column should end in .0 or .5 and not have anymore or any fewer decimal places after the decimal point. (even for 0.0).

●Align the decimals, even when there are negative signs in front of some of the number

Analysis: Aspect #2:

  1. Processed Data In any lab report you must have both raw and processed data included. Decide how you are going to process the data (percent changes, mean, standard dev, rates, chi square, t test etc.). In separate data tables, you need to show the result of your data processing. Again, DON’T SHARE HOW YOU ARE GOING TO PROCESS THE DATA WITH ANYONE. When you take the data and do something (mathematical) to it, like find averages, slopes, changes, standard deviations, etc. this is processing the data. Make sure you include a sample problem using actual raw data from your lab. Make sure you process the raw data CORRECTLY!

IA Check #2 Checklist

  • Methodology

Are the experimental groups and control groups evident and clearly labeled?
Does the control group differ from the experimental group(s) only by the independent variable? –Everything else should stay constant
Are the independent and the dependent variables quantitative? Can we measure it?
Is the IV set up so there are at least 5 intervals of measured data? Ex: Gathered information at least 5 different times
Are there at least 5 levels of the independent variable—or 5 samples in the experimental group?
Are all constants (controlled variables) clearly stated and explained? What stays the SAME for each trial?
  • Are regular measurements of controlled variables included? Ex: if temperature is said to be constant- then regular measuring of the temperature is necessary

Is your procedure listed and clearly written? (Should be able to repeat. Like a recipe Details!)
Does your procedure include information about HOW TO gather data? What tools will be used, and how
Is there a clear picture or diagram of the experimental apparatus? Include labels.
Are all materials used clearly and precisely listed? (exact sizes of containers and concentrations of solutions must be stated- brand names etc—All details available) Be specific!
Does report show full awareness of significant safety, ethical or environmental issues? Include needed treatment if breeched.
Analysis (Aspects 1/2/3)
  • Selection of data to collect

Are both qualitative (visual observations- things that can’t be measured) & quantitative (measurements) data collected?
Will data collected directly address research question?
Is the data accurately collected?
  • Recording of data

Is the raw data presented in a table with an appropriate title and in the proper format?
Are all parts of tables presented clearly labeled? All axes clearly labeled.
Is the precision of the measuring device(s) used included with each table? (This includes + the smallest division of the device.) Unit of measure is usually found on the device. Ex: Smallest unit on standard triple beam balance is .1g.
Are all uncertainties presented?
  • Processing of data

Is the raw data properly processed? This may include statistical tests, percent change, or simple means. (Just subtraction alone is not sufficient)—Calculate things like % change/Standard D/ Means etc
  • Are TOTAL percent changes included (if used)- Make sure to process your data in a way that allows a graph to show any trends (if available) to be apparent.

Descriptor / IA RUBRIC GRADING SHEET
Methodology / Limitedly considers factors that influence reliability and sufficiency of the data for the RQ / ☐ / Somewhat considers factors that influence reliability and sufficiency of the data for the RQ / ☐ / Completely considers factors that influence reliability and sufficiency of the data for the RQ / ☐
Awareness of the safety, ethical, or environmental issues / Limited / ☐ / Some / ☐ / Full / ☐

*If most of your ticks are in the left-hand column, you cannot be given more than 2 marks for this criterion. If most of your ticks are in the middle column, you will be given a 3 or a 4. If most of your ticks are in the right-hand column, you will receive a 5 or a 6 for the criterion.

Descriptor / IA RUBRIC GRADING SHEET
Raw data / Insufficient relevant raw data have been collected to support a conclusion / ☐ / Incomplete relevant raw data have been collected to support a conclusion / ☐ / Sufficient relevant raw data have been collected to support a detailed and valid conclusion / ☐