Open-minded Caring Risk-takers Balanced Reflective * the B learner profile This process will challenge your thinking skills more than you can imagine. We need to emphasize again and again; all of this work is about you growing as a student. In addition, we invest valuable time into lab experiences because we all LIKE doing lab experiments! Hands-on learning opportunities are engaging and rewarding. Laboratory experiments are about thinking and doing and thinking some more. “l hear and forget. See and I remember. Do and understand,” Confucius see page 32 for more Confucius quotes The International Baccalaureate program values the laboratory as an integral part of learning chemistry.
Your lab portfolio will comprise 24% of your official 18 grade. Your teachers also value the lab and designate of each marking period grade to be based on your lab experiences. So, lab is BIG. B has designated particular criteria to be included in a formal lab report, and each criterion has distinct aspects that will be evaluated. Not all lab reports in B Chemistry Will be “formal” lab reports, and not all “formal” lab reports Will be assessing all of the designated criteria. We Will pace the expectations of the course to keep your workload manageable. We do appreciate your time. This Guide will help you understand the B requirements and maximize your learning.
Page 2 Specific Points Graded for Each Lab Report Criteria Design: D L] Defining the Problem (I Controlling variables Z] Developing a method for collection of data Data Collection and processing: DC? Z] Recording Raw Data Processing Raw Data Presenting Raw Data Conclusion and Evaluation: CE Z] Concluding Evaluating Procedure(s) Z] Improving the Investigation Design Aspect I Defining the Problem Levels Complete Partial None Formulates a focused problem / research question and identifies the relevant variables Formulates a problem / research question that is incomplete or identifies only some relevant variables. Does not identify a problem / research question and does not identify any relevant Aspect 2 Controlling Variables Designs a method for the effective control of the variables.
Aspect 3 Developing a Method for Collection of Data Develops a method that allows for the collection of sufficient relevant data. Designs a method that makes some attempt to control the insufficient relevant data. Designs a method that does not control the variables. Develops a method that does not allow for any relevant data to be collected. Aspect 1: Defining the Problem Only a few experiments in B Chemistry will require you to create your own research problem. Usually the labs you will be asked to do will already have clearly specified research questions and procedures. But when you design your own experiment, the first step is to recognize the nature of the problem before you.
When the Design criterion is assessed, you will be given an open- ended problem or a general aim tooth lab such that your inquiry is guided. For example, the research question might be presented to the whole class in the tort of “Investigate the Volume of a Drop”. You will need to recognize that certain factors will influence the volume of a drop. This is the nature of the problem. You will form a research question that is specific and relevant to your individual experiment. Gore the experiment “Investigate the Volume of a Drop”, your research question could be Determine how the size of the opening of the dropper affects the volume of a drop Of water’.
Page 3 Your current understanding Of science theories provides a background for your research question. Relevant theory needs to be presented. (e. G. , What do you know about water that makes you to wonder about how the size of the opening could affect the volume of a drop of water? You could discuss surface tension, intermolecular bonds, adhesive and cohesive forces, capillary action, and other physical properties of water. ) Your understanding of theory impacts the research question you choose. You might be asked to formulate a hypothesis (prediction) in light of any independent variables that have been chosen. Such a hypothesis must contain more than just an expected observation.
It must also include a proposed relationship between two or more variables, or at least an element tot rational explanation tort an expected observation. Often a hypothesis is for-annulated in a statement; y is done, then z will occur Answering the “because” in this hypothesis is an important part of the criteria being evaluated. The known theory is presented in the beginning of a lab report to substantiate your hypothesis as seasonable. Theory supports the “because” in your hypothesis. In addition to your research question, theory also relates to your explanation of your hypothesis. Theory used by a curious mind is the foundation of experimentation.
Your hypothesis will relate two variables that might have an effect on each other. Other variables that might affect the outcome are also mentioned, even if they are not to be specifically investigated. Three Types Of Variables in an Experiment 1) The independent variable is the variable you set or determine. Hence this variable stands independently in your experiment. You set this variable. ) The dependent variable is the variable that responds to the independent variable. Hence this variable is dependent on the independent variable in your experiment. 3) The controlled variables are all of the reasonable potential variables that you are keeping constant or unchanged throughout the duration of the experiment.
You try very hard to control all of these variables to be unwavering while you gather data. Aspect 2: Controlling the Variables You will then need to design a method that allows you to control these variables. “Control of variables” refers to the manipulation of the independent variable and he attempt to maintain the controlled variables at a constant value. The method should include explicit reference as to how the control of variables is achieved. The method should be clearly described in sufficient detail so that it could be reproduced by someone else from the information given. It is conventional to write sequential, numbered steps to communicate a procedure.
Your designed procedure must guarantee that the independent variable remains independent, the dependent variable remains dependent, and the controlled variables truly remain constant. Be specific in the listing Of required supplies. Materials and equipment needed in the investigation are to be designated by quantity and size (i. E. 3 – ml beakers) and chemicals designated by quantity and concentration (i. E. , 25 ml of 1. 0 molar hydrochloric acid or 10 grams of iron filings). The experimental set-up and measurement techniques are to be described. A labeled drawing of your set-up and / or protocol is often helpful and highly recommended. Page 4 Numbered steps in your procedure should be clear and specific to allow for the replication of your experiment by another person.
The conscious effort to keep controlled variables constant should be evident in your procedure. Your procedure also should be appropriate to the level of uncertainty needed. For example, don’t use a beaker to dispense a precise volume of liquid. On the other hand, don’t use the analytical balance that masses to 0001 gram when only an approximate mass is needed, (Think! ) You can allow for the collection of sufficient data by having a large enough range of values for your independent variable and having repeated trials. Specify and justify any assumptions underlying the procedure. Think through potential problems in advance, and demonstrate in your lab report your plan to master these difficulties.
Aspect 3: Developing a Method for Collection of Data In the design of your method of data collection, you need to pay attention to the need of sufficient, relevant data The definition of “sufficient relevant data” depends on the context. The planned investigation should anticipate the collection Of sufficient data so that the aim or research question can be suitably addressed and an evaluation of the reliability of the data can be made. Example considerations When assessing sufficiency Of data could be the following: The plan includes the duplication of data collected in multiple trials (at least 2-3 arils). D When planning the levels Of the independent variable values, S is the minimum number when practical. L] If a trend line is to be plotted through a scatter graph then at least 5 data points are needed.
D When doing iterations, the plan should show appreciation of the need for a trial run and repeats until consistent results are obtained. Data Collection and Processing Aspect 1 Recording Raw Data Records appropriate quantitative and associated qualitative raw data, including units and uncertainties where relevant. Qualitative raw data, but with some mistakes or omissions. Does not record any appropriate quantitative raw data or raw data is incomprehensible. Processes the quantitative raw data correctly, Presents processed data appropriately and, where relevant, includes errors and uncertainties. Processes quantitative raw data, but With some mistakes and/or omissions. Appropriately, but With some mistakes and/or omissions.
No processing of quantitative raw data is carried out or major mistakes are made in processing. Inappropriately or incomprehensibly. Page 5 Aspect I: Record Raw Data Data collection skills are important in accurately recording events and are critical to scientific investigation. Data collection involves all quantitative and qualitative raw data, such as tabulated measurements, written observations, or drawn specimens. Raw data is the actual data measured. This Will include associated qualitative data. The term “quantitative data” refers to numerical measurements of the variables associated with the investigation. Associated qualitative data are considered to be those observations that would enhance the interpretation of results.
Qualitative data is defined as those observed with more or less unaided senses (color, change of state, etc. ) or rather crude estimates (hotter, older, blue, finely powdered, etc. ), whereas quantitative data implies numerical observations, i. E. , actual measurements. Both types of data are important and required. Students will not be told how to record the raw data, The design and formatting tot the data tables are evaluated aspects of collecting data. Designing a data table in advance of the experiment is confirmation that you know what data is relevant to collect during the experiment. Never erase original recorded data-?-instead neatly cross out the error with a single line. Raw data must be presented for grading.
Raw data is the unaltered measurements and observations you record during the course of the experiment on the original paper you took in the lab. Your teacher will initial your paper. This raw data sheet is the only data sheet to include in your lab report. In other words, do not recreate a more legible format of the data sheet for your lab report. Plan ahead and make your original data table appropriate for easy interpretation. Uncertainties are associated With all raw data and an attempt should always be made to quantify uncertainties. For example, when students say there is an uncertainty in stopwatch measurements because Of reaction time, they must estimate the magnitude of the uncertainty.
Within tables of quantitative data, columns should be clearly annotated With a heading, units and an indication of the uncertainty of measurements. The uncertainty need not be the same as the manufacturer’s stated precision of the measuring device used if your use of the instrument reflects a different precision. Significant digits in the data and the uncertainty in the data must be consistent. This applies to all measuring devices. The number of significant digits should reflect the precision of the agreements. There should be no variation in the precision of raw data, For example, the same number tot decimal places should be used it the measuring device is consistent.
The level of precision for calculated results should be consistent with the precision of the raw data. The recording of the level of precision would be expected from the point where the students take over the manipulation. For example, you will not be expected to state the level of precision in the concentration of a solution prepared for you, The following points should be included in data collection: 1. Data tables are always required. All data is tabulated for organization. 2. Only original, raw data tables are evaluated. Do not re-copy your data. 3. Give an identifying title on the data table. More comprehensive experiments have multiple data tables.