Thursday, January 19, 2017

Capstone Experimental Component

Students will be asked to design and perform an original experiment.  The purpose of this experiment was for students to gather data about their topic using their own methods and those learned in science.  
Students will be asked to be as clear as possible, but to be sure that they include all the steps of the scientific method
 (Question, Hypothesis, Design, Test, Record, Analyze, Conclude) 
and all the parts of a standard lab report
(Abstract, Introduction, Methods and Materials, Data, Graphs, Discussion, Works Cited)

How do I know if I have a good experiment?

Do you have a question?
Do you have a hypothesis?
            Hypothesis OK (relational) – I predict that they will be related
            Hypothesis BETTER (directional) – I predict that as this thing increases, the other thing                     will decrease
Do you know what kind of experiment you are doing?
            Case Study
            Survey Research
            Observational Research
            Correlational Research
            Experimental Research
            Cross Cultural Research
            Secondary Analysis
- Do you know the differences?  Scroll down for more info.
Do you know what variables you are working with?
            Independent
            Dependent
            Controlled
Are your results clear?
            Thorough
            Measurable
            Graphs and Tables
            Easy to Understand
Is your Conclusion accurate?
            Controlled
            Related
Is your experiment repeatable?

Stay away from vague data.
Make sure your data has plenty of points.
Does the report explain any uncontrolled aspects of the study?


How do I come up with a good question?

How does this thing affect the other thing?

Sample Experiment questions:

Does music affect on animal behavior?
• Does the color of food or drinks affect whether or not we like them?
• Where are the most germs in your school?
• Does music have an affect on plant growth?
• Which kind of food do dogs (or any animal) prefer best?
• Which paper towel brand is the strongest?
• What is the best way to keep an ice cube from melting?
• What level of salt works best to hatch brine shrimp?
• Can the food we eat affect our heart rate?
• How effective are child-proof containers and locks.
• Can background noise levels affect how well we concentrate?
• Does acid rain affect the growth of aquatic plants?
• What is the best way to keep cut flowers fresh the longest?
• Does the color of light used on plants affect how well they grow?
• What plant fertilizer works best?
• Does the color of a room affect human behavior?
• Do athletic students have better lung capacity?
• What brand of battery lasts the longest?
• Does the type of potting soil used in planting affect how fast the plant grows?
• What type of food allow mold to grow the fastest?
• Does having worms in soil help plants grow faster?
• Can plants grow in pots if they are sideways or upside down?
• Does the color of hair affect how much static electricity it can carry? (test with balloons)
• How much weight can the surface tension of water hold?
• Can some people really read someone else’s thoughts?
• Which soda decays fallen out teeth the most?
• What light brightness makes plants grow the best?
• Does the color of birdseed affect how much birds will eat it?
• Do natural or chemical fertilizers work best?
• Can mice learn? (you can pick any animal)
• Can people tell artificial smells from real ones?
• What brands of bubble gum produce the biggest bubbles?
• Does age affect human reaction times?
• What is the effect of salt on the boiling temperature of water?
• Does shoe design really affect an athlete’s jumping height?
• What type of grass seed grows the fastest?
• Can animals see in the dark better than humans?


The above list is primarily Experimental  What are the other types of experiments?



 Sociological Research: Designs, Methods


Sociologists use many different designs and methods to study society and social behavior. Most sociological research involves ethnography, or “field work” designed to depict the characteristics of a population as fully as possible.
Three popular social research designs(models) are
  • Cross‐sectional, in which scientists study a number of individuals of different ages who have the same trait or characteristic of interest at a single time
    • Example:  How many women have breast cancer?  Researcher would check with many different ages, backgrounds etc. to see what percentages showed up in each area.

  • Longitudinal, in which scientists study the same individuals or society repeatedly over a specified period of time
    • Example:  How does sugar affect health?  Researcher follows a smaller group of people to see how they change over time.

  • Cross‐sequential, in which scientists test individuals in a cross‐sectional sample more than once over a specified period of time
    • Example:  How does height affect success in sports?  Researcher follows several different groups to see how they all change over time.
Six of the most popular sociological research methods (procedures) are the case study, survey, observational, correlational, experimental, and cross‐cultural methods, as well as working with information already available.

Case study research
In case study research, an investigator studies an individual or small group of individuals with an unusual condition or situation. Case studies are typically clinical in scope. The investigator (often a clinical sociologist) sometimes uses selfreport measures to acquire quantifiable data on the subject. A comprehensive case study, including a longterm followup, can last months or years.
On the positive side, case studies obtain useful information about individuals and small groups. On the negative side, they tend to apply only to individuals with similar characteristics rather than to the general population. The high likelihood of the investigator's biases affecting subjects' responses limits the generalizability of this method.

Survey research
Survey research involves interviewing or administering questionnaires, or written surveys, to large numbers of people. The investigator analyzes the data obtained from surveys to learn about similarities, differences, and trends. He or she then makes predictions about the population being studied.
As with most research methods, survey research brings both advantages and disadvantages. Advantages include obtaining information from a large number of respondents, conducting personal interviews at a time convenient for respondents, and acquiring data as inexpensively as possible. “Mail‐in” surveys have the added advantage of ensuring anonymity and thus prompting respondents to answer questions truthfully.
Disadvantages of survey research include volunteer bias, interviewer bias, and distortionVolunteer bias occurs when a sample of volunteers is not representative of the general population. Subjects who are willing to talk about certain topics may answer surveys differently than those who are not willing to talk. Interviewer bias occurs when an interviewer's expectations or insignificant gestures (for example, frowning or smiling) inadvertently influence a subject's responses one way or the other. Distortion occurs when a subject does not respond to questions honestly.

Observational research
Because distortion can be a serious limitation of surveys, observational research involves directly observing subjects' reactions, either in a laboratory (called laboratory observation) or in a natural setting (called naturalistic observation). Observational research reduces the possibility that subjects will not give totally honest accounts of the experiences, not take the study seriously, fail to remember, or feel embarrassed.
Observational research has limitations, however. Subject bias is common, because volunteer subjects may not be representative of the general public. Individuals who agree to observation and monitoring may function differently than those who do not. They may also function differently in a laboratory setting than they do in other settings.

Correlational research
A sociologist may also conduct correlational research. A correlation is a relationship between two variables (or “factors that change”). These factors can be characteristics, attitudes, behaviors, or events. Correlational research attempts to determine if a relationship exists between the two variables, and the degree of that relationship.
A social researcher can use case studies, surveys, interviews, and observational research to discover correlations. Correlations are either positive (to +1.0), negative (to −1.0), or nonexistent (0.0). In a positive correlation, the values of the variables increase or decrease (“co‐vary”) together. In a negative correlation, one variable increases as the other decreases. In a nonexistent correlation, no relationship exists between the variables.
People commonly confuse correlation with causation. Correlational data do not indicate cause‐and‐effect relationships. When a correlation exists, changes in the value of one variable reflect changes in the value of the other. The correlation does not imply that one variable causes the other, only that both variables somehow relate to one another. To study the effects that variables have on each other, an investigator must conduct an experiment.

Experimental research
Experimental research attempts to determine how and why something happens. Experimental research tests the way in which an independent variable (the factor that the scientist manipulates) affects a dependent variable (the factor that the scientist observes).
A number of factors can affect the outcome of any type of experimental research. One is finding samples that are random and representative of the population being studied. Another is experimenter bias, in which the researcher's expectations about what should or should not happen in the study sway the results. Still another is controlling for extraneous variables, such as room temperature or noise level, that may interfere with the results of the experiment. Only when the experimenter carefully controls for extraneous variables can she or he draw valid conclusions about the effects of specific variables on other variables.

Cross-cultural research
Sensitivity to others' norms, folkways, values, mores, attitudes, customs, and practices necessitates knowledge of other societies and cultures. Sociologists may conduct cross‐cultural research, or research designed to reveal variations across different groups of people. Most crosscultural research involves survey, direct observation, and participant observation methods of research.
Participant observation requires that an “observer” become a member of his or her subjects' community. An advantage of this method of research is the opportunity it provides to study what actually occurs within a community, and then consider that information within the political, economic, social, and religious systems of that community. Cross‐cultural research demonstrates that Western cultural standards do not necessarily apply to other societies. What may be “normal” or acceptable for one group may be “abnormal” or unacceptable for another.

Research with existing data, or secondary analysis
Some sociologists conduct research by using data that other social scientists have already collected. The use of publicly accessible information is known as secondary analysis, and is most common in situations in which collecting new data is impractical or unnecessary. Sociologists may obtain statistical data for analysis from businesses, academic institutions, and governmental agencies, to name only a few sources. Or they may use historical or library information to generate their hypotheses.

 If you're having trouble coming up with an experiment, try searching for "Sample of 'Area of Interest' Experiments"



Variables

You won't be able to do very much in research unless you know how to talk about variables. A variable is any entity that can take on different values. OK, so what does that mean? Anything that can vary can be considered a variable. For instance, age can be considered a variable because age can take different values for different people or for the same person at different times. Similarly, country can be considered a variable because a person's country can be assigned a value.
Variables aren't always 'quantitative' or numerical. The variable 'city' consists of text values like 'New York' or 'Sydney'. We can, if it is useful, assign quantitative values instead of (or in place of) the text values, but we don't have to assign numbers in order for something to be a variable. It's also important to realize that variables aren't only things that we measure in the traditional sense. For instance, in much social research and in program evaluation, we consider the treatment or program to be made up of one or more variables (i.e., the 'cause' can be considered a variable). An educational program can have varying amounts of 'time on task', 'classroom settings', 'student-teacher ratios', and so on. So even the program can be considered a variable (which can be made up of a number of sub-variables).
An attribute is a specific value on a variable. For instance, the variable sex or gender has two attributes: male and female. Or, the variable agreement might be defined as having five attributes:
  • 1 = strongly disagree
  • 2 = disagree
  • 3 = neutral
  • 4 = agree
  • 5 = strongly agree
Another important distinction having to do with the term 'variable' is the distinction between an independent and dependent variable. This distinction is particularly relevant when you are investigating cause-effect relationships. It took me the longest time to learn this distinction. (Of course, I'm someone who gets confused about the signs for 'arrivals' and 'departures' at airports -- do I go to arrivals because I'm arriving at the airport or does the person I'm picking up go to arrivals because they're arriving on the plane!). I originally thought that an independent variable was one that would be free to vary or respond to some program or treatment, and that a dependent variable must be one that depends on my efforts (that is, it's the treatment). But this is entirely backwards! In fact the independent variable is what you (or nature) manipulates -- a treatment or program or cause. The dependent variable is what is affected by the independent variable -- your effects or outcomes. For example, if you are studying the effects of a new educational program on student achievement, the program is the independent variable and your measures of achievement are the dependent ones.
Finally, there are two traits of variables that should always be achieved. Each variable should be exhaustive, it should include all possible answerable responses. For instance, if the variable is "religion" and the only options are "Protestant", "Jewish", and "Muslim", there are quite a few religions I can think of that haven't been included. The list does not exhaust all possibilities. On the other hand, if you exhaust all the possibilities with some variables -- religion being one of them -- you would simply have too many responses. The way to deal with this is to explicitly list the most common attributes and then use a general category like "Other" to account for all remaining ones. In addition to being exhaustive, the attributes of a variable should be mutually exclusive, no respondent should be able to have two attributes simultaneously. While this might seem obvious, it is often rather tricky in practice. For instance, you might be tempted to represent the variable "Employment Status" with the two attributes "employed" and "unemployed." But these attributes are not necessarily mutually exclusive -- a person who is looking for a second job while employed would be able to check both attributes! But don't we often use questions on surveys that ask the respondent to "check all that apply" and then list a series of categories? Yes, we do, but technically speaking, each of the categories in a question like that is its own variable and is treated dichotomously as either "checked" or "unchecked", attributes that are mutually exclusive.



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