Research Process Step One – Conceptualization of Objectives Step Two – Measurement of Objectives Step Three – Determine Sampling Technique Step Four – Determine Data Collection Design Step Five – Collect and Analyze Data Step Six – Develop Graphs and Charts to Present Data. Step Seven – Write a Report – Reporting Results

Proposition Intervention Observable Changes Dependent Variable Independent Variable

Identify Independent and Dependent Variables Identify Independent and Dependent Variables Independent Independent Intervention Strategies Intervention Strategies Dependent Dependent Change Resulting from Intervention Change Resulting from Intervention Develop Reliable and Valid Indicators of these Measurements Develop Reliable and Valid Indicators of these Measurements Reliable – Indicator provides consistent measurement across time Reliable – Indicator provides consistent measurement across time Valid – Indicator provides accurate measurement Valid – Indicator provides accurate measurement

Hypothesis Use of fertilizer Greater yield of crops Independent Variable Dependent Variable

Concept Indicator Concept Indicator Use of Fertilizer # of bags of fertilizer used per acre of crop

Concept Indicator Concept Indicator Crop Yield # of bales of hay per acres

Indicator Indicator Indicator Indicator # of bags of fertilizer per acre Increases # of bales of hay per acres

Non-Random Sample – for Descriptive Statistics Convenience Sample Snowball Sample Theoretical Sample Random Sample – For Inferential Statistics

Non-Random Sample Convenience Sample – Select units that are convenient (i.e., the nearest fields of crops) Snowball Sample – Have one farmer refer you to another who will refer you to another etc. Theoretical Sample – Your theory states that this fertilizer only works for innovative farmers so you select only innovative farmers as your experimental group.

Random Sample This type of sample should be used when You want to publish in a peer-reviewed journal You want to generalize to the population Every unit (field or farmer) in your population has an equal probability of being selected for your study.

Random Sample Make a list of all the farmers in your county who plant this crop. Assign a number to each farmer Place numbers in a bin/hat and blindly draw out the number of farmers you need for your study.

Qualitative Case Studies Gather detailed information from one or a small group of individuals. Intensive Interviews/Focus Groups In-depth Understanding of Subjects Disadvantage – Bias of interviewer can impact interpretation of results. Participant Observation Watch ongoing process Disadvantage – Hawthorne Effect – People act differently when they know they are being observed Content Analysis Study materials objects (e.g., content of fields themselves)

Qualitative Case Studies - Tell Farmer Brown’s story about his experience with fertilizer. Intensive Interviews/Focus Groups Sit down with individual farmers and asked open-ended questions, or sit down with a group of farmers and “focus” the open-ended questions on fertilizer and crop yield. Participant Observation Spend a summer as a farmer who uses fertilizer and live amongst farmers who use fertilizer. Content Analysis Study the content of fields that have been fertilized – measure amount of grain/hay grown per square inch etc.

Quantitative Laboratory Experiment Study experimental and control groups in a laboratory situation Field Trials Structure a experiment out in the field/community Surveys Construct questionnaires and mail/read to farmers. Secondary Use information collected by someone else

Quantitative Laboratory Experiment Plant small plots of land in a laboratory. Half of them would be fertilized and the other half would not. Field Trials Select farms that are fertilized and compare those to ones that are not. Surveys Use survey questions to ask farmers how satisfied they are with fertilizer and to report how much it has improved their crops. Secondary Find old records that contain information about fertilizers and crop yield

Field Trials Data is collect literally “out in the field” or the community Laboratory Experiment Data is collected in a laboratory setting Different Types of Experiments One shot post-test One group pre- and post-test Classical Experimental design Experimental and Control Groups – Pre- and Post-tests

Year 1 and 2 are crop yields before fertilizer; year 3 is crop yield after fertilizer One Group Pre and Post Tests

Surveys Self reported attitudes and behavior Develop survey instrument (see power point on the development on survey instrument – have link here) Mail out survey Face to face survey On-line survey Telephone survey Collect data Analyze data

Descriptive Statistics Mean Median Mode Standard Deviation Inferential Statistics (Relationships) Statistical Significance Chi Square

Should Include the Following: Should Include the Following: Introduction Introduction Literature Review Literature Review Methods Section Methods Section Results Results Discussion – Summary and Conclusion Discussion – Summary and Conclusion References/Appendix References/Appendix

Dr. Carol Albrecht Assessment Specialist USU Ext (979)