Research paper and ppt

Planning Your Research Project

Research Design

• Design = Overall structure for the study

 The procedures the researcher follows

 The data the researcher collect

 The data analyses the researcher conducts

Planning a General Approach

• Think broadly about the problem as arising out of a particular area

• Are you studying

• People

• Things

• Records

• Thoughts & ideas

• Dynamics & energy

Planning a General Approach

Think about the kinds of data you need to address your problem

 Do you need/can you find participants

 Do you have the right equipment and skills

 Do you know how to interpret the data and draw conclusions from them

Research Planning: Selecting a Particular Research Methodology

• Planning

 Determining the general approach to a study

 May be similar across disciplines

• Methodology

 The techniques one uses to collect and analyze data

 May be specific to a particular academic discipline

The Nature and Role of Data in Research

• Data are pieces of information that help form a bigger picture

• Data are transient — what is true at any point in time may not be true at another point in time

The Nature and Role of Data in Research

• Data may be primary or secondary

 Primary data are closest to the truth (the source)

 Secondary data are derived from primary data

• Distorted by interpretations and communication

Planning for Data Collection

• What data are needed

• Where are the data located

• How will the data be obtained

• What limits will be placed on the nature of acceptable data

• How will the data be interpreted

Linking Data and Methodology

• Quantitative methods

 Involve collecting numerical data

• Qualitative methods

 Involve collecting textual or image-based data

• Mixed methods

 Use both quantitative and qualitative methods in the same study

•

To Determine an Approach, First Ask Yourself These Questions:

• What is my purpose?

• What is the nature of the process?

• What are the data like/how are they collected?

• How are data analyzed?

• How are the findings communicated?

Also Consider These Issues:

• Your comfort with the assumptions of the qualitative tradition

• The audience for your study

• The nature of the research question

• The extensiveness of the related literature

• The depth of what you want to discover

• The amount of time you have available for conducting the study

Also Consider These Issues:

• The extent to which you are willing to interact with the people in your study

• The extent to which you feel comfortable working without much structure

• Your ability to organize and draw inferences from a large body of information

• Your writing skills

Select a Research Methodology

• Action research

• Case study

• Content analysis

• Correlational research

• Design-based research

• Developmental research

• Ethnography

• Experimental research

• Ex post facto research

• Grounded theory research

• Historical research

• Observation study

• Phenomenological research

• Quasi-experimental research

• Survey research

Considering the Validity of Your Method

• Validity of the research project is defined as its

 Accuracy

 Meaningfulness, and

 Credibility

Internal Validity

• The extent to which the design and data of a research study allow the researcher to draw accurate conclusions about cause-and-effect and other relationships within the data

Researchers must take precautions to eliminate other possible explanations for the results

Strategies to Increase Internal Validity

• A controlled laboratory study

• A double-blind experiment

• Unobtrusive measures

• Triangulation

External Validity

• The extent to which:

 results of a research study apply to situations beyond the study itself

 conclusions can be generalized

Strategies to Increase External Validity

• Conduct the study in a real-life setting

• Use a representative sample

• Replicate the study in a different context

Increasing Validity in Qualitative Research

• Triangulate

 Compare multiple data sources

• Spend time in the field

• Analyze outliers and contradictory instances

• Use thick description

Increasing Validity in Qualitative Research

• Acknowledge and address personal biases

• Seek respondent validation

 Take conclusions back to participants to evaluate

• Seek feedback from others

Measurement

• Limiting the data of any phenomenon— substantial or insubstantial— so that those data may be interpreted and, ultimately, compared to a particular qualitative or quantitative standard

Measurement

• Limiting the data of any phenomenon— substantial or insubstantial— so that those data may be interpreted and, ultimately, compared to a particular qualitative or quantitative standard

 Substantial = have physical substance.

 Insubstantial = exist only as concepts, ideas, opinions, feelings, or other intangible entities.

Measurement

• Limiting the data of any phenomenon— substantial or insubstantial— so that those data may be interpreted and, ultimately, compared to a particular qualitative or quantitative standard

 transformed into new discoveries, revelations, and enlightenments.

Measurement

• Limiting the data of any phenomenon— substantial or insubstantial— so that those data may be interpreted and, ultimately, compared to a particular qualitative or quantitative standard

 norms, averages, conformity to expected statistical distributions, goodness of fit, accuracy of description

Measurement: Example

Measuring interpersonal dynamics in a small group

• Ask each person: Who do you like most, who do you like least, and who evokes neutral feelings

• Allow the researcher to identify patterns and draw conclusions

Scales of Measurement

• A scale specifies the categories of measurement

• Scales ultimately dictate the statistical procedures (if any) that can be used in processing numerical data

Nominal Scale

• Measures data by assigning names or dividing into discrete categories  Boys, girls  North of Main Street, South of Main

Street

• Statistical procedures  Mode  Percentage  Chi-square test

Ordinal Scale

• Rank-order data as more/higher or less/lower

• Think in terms of greater or less than

• Elementary, high school, college, or graduate education

• Unskilled, semiskilled, or skilled labor

• Statistical procedures = median, percentile rank, Spearman’s rank-order correlation

Interval Scale

• Equal units of measurement

• Zero point established arbitrarily

• Fahrenheit (F) and Celsius (C) scales

• Rating scales, such as surveys, assumed to fall on interval scales

• Statistical procedures = means, standard deviations, Pearson product moment correlations

Ratio Scale

• Equal measurement units (similar to interval scale)

• Absolute zero point (0 = total absence of the quality being measured)

• Distance

• Ratio = can express values in terms of multiples and fractional parts

Summary & Comparison

• Nominal scale: One object is different from another

• Ordinal scale: One object is bigger or better or more of anything than another

• Interval scale: One object is so many units (e.g., degrees, inches) more than another

• Ratio scale: One object is so many times as big or bright or tall or heavy as another

Validity & Reliability of Measurement

• Validity = the extent to which a measurement instrument measures what it is intended to measure

• Reliability = the consistency with which a measurement instrument yields a certain result when the entity being measured hasn’t changed

Validity of Measurement Instruments

• Face Validity

 Is extent to which an instrument looks like it measures a characteristic

 Relies on subjective judgment

• Content Validity

 Is extent to which a measurement instrument is a representative sample of the content area being measured

Validity of Measurement Instruments

• Criterion Validity

 The extent to which the results of an assessment correlate with another, related measure

• Construct Validity

 The extent to which an instrument measures a characteristic that cannot be directly observed but is assumed to exist (such as intelligence)

Determining Validity

• Table of specifications

 The researcher constructs a two- dimensional grid listing the specific topics and behaviors that reflect achievement in the domain.

• Multitrait-multimethod approach

 Two or more different characteristics are each measured using two or more different approaches. The two measures of the same characteristic should be highly related.

Determining Validity

• Judgment by a panel of experts

 Several experts in a particular area are asked to scrutinize an instrument to ascertain its validity for measuring the characteristic in question

Reliability

• Reliability is the consistency with which a measuring instrument yields a certain result when the entity being measured hasn’t changed.

• Instruments designed to measure social and psychological characteristics (insubstantial phenomena) tend to be even less reliable than those designed to measure physical (substantial) phenomena.

Determining the Reliability of a Measurement Instrument

Determining the Reliability of a Measurement Instrument

• Interrater reliability

 the extent to which two or more individuals evaluating the same product or performance give identical judgments

• Test-retest reliability

 the extent to which a single instrument yields the same results for the same people on two different occasions

Determining the Reliability of a Measurement Instrument

Determining the Reliability of a Measurement Instrument

• Equivalent forms reliability

 The extent to which two different versions of the same instrument yield similar results

• Internal consistency reliability

 The extent to which all of the items within a single instrument yield similar results

Enhancing Reliability and Validity

• Goals: Reduce error, reduce bias

• Strategies for increasing reliability:  Standardize the procedures

 Establish clear criteria

 Train the researchers well

• Strategies for increasing validity:  Consult the literature

 Share drafts

 Conduct pilot studies

The Value of a Pilot Study

Pilot study: a brief exploratory investigation before the main study to

• Try out particular procedures, measurement instruments, or methods of analysis

• Determine the feasibility of the study

• Identify what approaches will and will not be effective in solving the overall research problem

Ethical Issues Ethical Issues

• Participants must be protected from harm

 Benefits to participants must outweigh risks

 Participants should be debriefed

Ethical Issues Ethical Issues

• Participation must be voluntary and informed

 Individuals know what they are being asked to do

 Individuals can decline without penalty

 Individuals know they can withdraw at any time without penalty

Ethical Issues Ethical Issues

• Participants have a right to privacy

 Data and information about participants are confidential

• Identifiable data should not be shared (even in class) without written consent

 Names should be coded to ensure anonymity

Ethical Issues Ethical Issues

• Researchers must be honest

 Data should be trustworthy

 Reports should be complete and accurate

 Contributors should be credited

Ethical Issues Ethical Issues

• Research must be reviewed before data collection begins

 Institutions maintain an IRB (review board) and sometimes IACUC

• Scholars and researchers across disciplines

• Review proposals to assess risks and ensure that participants’ rights are honored

Ethical Issues Ethical Issues

• Researchers are expected to adhere to professional code of conduct within their field

• Visit the homepage of your own professional organization to learn more