<\/h3>\r\nSample is randomly assigned to<\/h3>\r\none of the groups below:<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nMeasure DV<\/h3>\r\n<\/td>\r\n\r\nIntroduce IV<\/h3>\r\n<\/td>\r\n\r\nMeasure DV<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nExperimental Group<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"![\"magnifying](\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images-archive-read-only\/wp-content\/uploads\/sites\/1496\/2016\/03\/15190936\/magnifying-glass-189254_1280-150x150.png\")
We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
one of the groups below:<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nMeasure DV<\/h3>\r\n<\/td>\r\n\r\nIntroduce IV<\/h3>\r\n<\/td>\r\n\r\nMeasure DV<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nExperimental Group<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
Measure DV<\/h3>\r\n<\/td>\r\n\r\nIntroduce IV<\/h3>\r\n<\/td>\r\n\r\nMeasure DV<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nExperimental Group<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
Introduce IV<\/h3>\r\n<\/td>\r\n\r\nMeasure DV<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nExperimental Group<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
Measure DV<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nExperimental Group<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
Experimental Group<\/h3>\r\n<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
X<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
X<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
X<\/h3>\r\n<\/td>\r\n<\/tr>\r\n\r\n\r\nControl Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
Control Group<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
X<\/h3>\r\n<\/td>\r\n\r\n-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
-<\/h3>\r\n<\/td>\r\n\r\nX<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
X<\/h3>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe major advantage of the experimental design is that of helping to establish cause and effect relationships.\u00a0A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting. I hope this brief description of experimental design helps you appreciate both the difficulty and the rigor of conducting an experiment.\r\n\r\nCase studies\u00a0<\/strong>involve exploring a single case or situation in great detail.\u00a0Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation.\u00a0Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation.\u00a0And they often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment.\u00a0Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions.\u00a0However, the findings from case studies cannot be\u00a0generalized<\/strong>\u00a0or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison.\u00a0(Read \u201cThe Man Who Mistook His Wife for a Hat\u201d by Dr. Oliver Sacks as a good example of the case study approach.)\r\n\r\nSurveys<\/strong>\u00a0are familiar to most people because they are so widely used.\u00a0Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online.\u00a0A survey involves asking a standard set of questions to a group of subjects.\u00a0In a highly structured survey, subjects are forced to choose from a response set such as \u201cstrongly disagree, disagree, undecided, agree, strongly agree\u201d; or \u201c0, 1-5, 6-10, etc.\u201d\u00a0Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many independent and dependent variables in a relatively short period of time.\u00a0Surveys typically yield surface information on a wide variety of factors, but may not allow for in-depth understanding of human behavior.\u00a0Of course, surveys can be designed in a\u00a0number of ways.\u00a0They\u00a0may include\u00a0forced choice<\/strong>\u00a0questions and\u00a0semi-structured questions<\/strong>\u00a0in which the researcher allows the respondent to describe or give details about certain events.\u00a0One of the most difficult aspects of designing a good survey is wording questions in an unbiased way and asking the right questions so that respondents can give a clear response rather that choosing \u201cundecided\u201d each time.\u00a0Knowing that 30% of respondents are undecided is of little use!\u00a0So a lot of time and effort should be placed on the construction of survey items.\u00a0One of the benefits of having forced choice items is that each response is coded so that the results can be quickly entered and analyzed using statistical software.\u00a0Analysis takes much longer when respondents give lengthy responses that must be analyzed in a different way.\u00a0Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices.\u00a0However, they are based on\u00a0self-report<\/strong>\u00a0or what people say they do rather than on observation and this can limit accuracy.\r\n\r\nSecondary\/Content analysis\u00a0<\/strong>involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices or preferences.\u00a0There are a number of data sets available to those who wish to conduct this type of research.\u00a0For example, the U. S. Census Data is available and widely used to look at trends and changes taking place in the United States (go to\u00a0http:\/\/www.census.gov\/<\/a>\u00a0and check it out).\u00a0There are a number of other agencies that collect data on family life, sexuality, and many other areas of interest in human development (go to\u00a0http:\/\/www.norc.uchicago.edu\/<\/a>\u00a0or\u00a0http:\/\/www.kff.org\/<\/a>\u00a0and see what you find.).\u00a0The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study.\r\n\r\nContent analysis<\/strong>\u00a0involves looking at media such as old texts, pictures, commercials, lyrics or other materials to explore patterns or themes in culture.\u00a0An example of content analysis is the classic history of childhood by Aries (1962) called \u201cCenturies of Childhood\u201d or the analysis of television commercials for sexual or violent content.\u00a0Passages in text or programs that air can be randomly selected for analysis as well.\u00a0Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.\r\n\r\nDevelopmental designs<\/strong>\u00a0are techniques used in life span research (and other areas as well).\u00a0These techniques try to examine how age, cohort, gender, and social class impact development.\u00a0Cross-sectional<\/strong>\u00a0research involves beginning with a sample that represents a cross-section of the population.\u00a0Respondents who vary in age, gender, ethnicity, and social class might be asked to complete a survey about television program preferences or attitudes toward the use of the Internet.\u00a0The attitudes of males and females could then be compared as could attitudes based on age.\u00a0In cross-sectional research, respondents are measured only once.\u00a0This method is much less expensive than longitudinal research but does not allow the researcher to distinguish between the impact of age and the cohort effect.\u00a0Different attitudes about the Internet, for example, might not be altered by a person\u2019s biological age as much as their life experiences as members of a cohort.\r\n\r\nLongitudinal<\/strong>\u00a0research involves beginning with a group of people who may be of the same age and background, and measuring them repeatedly over a long period of time.\u00a0One of the benefits of this type of research is that people can be followed through time and be compared with them when they were younger.\u00a0A problem with this type of research is that it is very expensive and subjects may drop out over time.\u00a0(The film 49 Up is a example of following individuals over time. You\u00a0see how\u00a0people change physically, emotionally,\u00a0and socially through time.) What would be the drawbacks of being in a longitudinal study? What about 49 Up? Would you\u00a0want to be filmed every 7 years? What would be the advantages and disadvantages? Can\u00a0you imagine why some would continue and others drop out of\u00a0the project?\r\n\r\nCross-sequential<\/strong>\u00a0research involves combining aspects of the previous two techniques; beginning with a cross-sectional sample and measuring them through time.\u00a0This is the perfect model for looking at age, gender, social class, and ethnicity.\u00a0But it the drawbacks of high costs and attrition are here as well.","rendered":"We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\n
Observational studies<\/strong>\u00a0involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play at a park, or behind a one-way glass while children are at play in a laboratory playroom.\u00a0The researcher may follow a check list and record the frequency and duration of events (perhaps how many conflicts occur among 2 year olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.).\u00a0The researcher may be a participant or a non-participant.\u00a0What would be the strengths of being a participant?\u00a0What would be the weaknesses?\u00a0Consider the strengths and weaknesses of not participating.\u00a0In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. What people do and what they say they do are often very different.\u00a0A major weakness of observational studies is that they do not allow the researcher to explain causal relationships.\u00a0Yet, observational studies are useful and widely used when studying children.\u00a0Children tend to change their behavior when they know they are being watched (known as the Hawthorne effect<\/strong>) and may not survey well.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\nThree conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n
The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\nThe\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\nThe\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\nA basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n
We have just been looking at models of the research process and goals of research.\u00a0The following is a comparison of research methods or techniques used to describe, explain, or evaluate.\u00a0Each of these designs has strengths and weaknesses and is sometimes used in combination with other designs within a single study.<\/p>\nExperiments<\/strong>\u00a0are designed to test\u00a0hypotheses<\/strong>\u00a0(or specific statements about the relationship between\u00a0variables<\/strong>)\u00a0in a controlled setting in efforts to explain how certain factors or events produce outcomes.\u00a0A variable is anything that changes in value. Concepts are\u00a0operationalized<\/strong>\u00a0or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study.\u00a0For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of\u00a0marital satisfaction.\u00a0What is something measurable that would indicate some level of marital satisfaction?\u00a0Would it be the amount of time couples spend together each day?\u00a0Or eye contact during a discussion about money?\u00a0Or maybe a subject\u2019s score on a marital satisfaction scale.\u00a0Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction.\u00a0What do you think?\u00a0These are the kinds of considerations researchers must make when working through the design.<\/p>\n Three conditions must be met in order to establish cause and effect.\u00a0Experimental designs are useful in meeting these conditions.<\/p>\n The\u00a0independent and dependent variables must be related<\/strong>.\u00a0In other words, when one is altered, the other changes in response.\u00a0(The independent variable is something altered or introduced by the researcher.\u00a0The dependent variable is the outcome or the factor affected by the introduction of the independent variable.\u00a0For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.)<\/p>\n The\u00a0cause must come before the effect.<\/strong>\u00a0Experiments involve measuring subjects on the dependent variable before exposing them to the independent variable (establishing a baseline).\u00a0So we would measure the subjects\u2019 level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels.\u00a0(Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these designs.)<\/p>\n The\u00a0cause must be isolated.\u00a0<\/strong>The researcher must ensure that no outside, perhaps unknown variables are actually causing the effect we see.\u00a0The experimental design helps make this possible.\u00a0In an experiment, we would make sure that our subjects\u2019 diets were held constant throughout the exercise program.\u00a0Otherwise, diet might really be creating the change in stress level rather than exercise.<\/p>\n A basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the\u00a0experimental group or the control group<\/strong>.\u00a0The experimental group is the group that is going to be exposed to an\u00a0independent variable\u00a0or condition the researcher is introducing as a potential cause of an event.\u00a0The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable.\u00a0After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred.\u00a0If so, we are in a better position to suggest that the independent variable<\/strong> caused the change in the dependent variable<\/strong>.\u00a0The basic experimental model looks like this:<\/p>\n