Course Description
Quantitative and qualitative methodologies of mass communication research, with emphasis on the research process, concepts and issues of research design, and methods of data collection. Topics introduced include measurement, sampling, focus groups and interviewing, survey and experimental design, and data analysis.
Athena Title
Mass Comm Research
Equivalent Courses
Not open to students with credit in JRMC 8010E
Prerequisite
Permission of department
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Course Objectives
By the end of this course, students should have learned: - To define and explain the importance and value of research - To differentiate between different types of research (qualitative and quantitative, primary and secondary, cross- sectional and longitudinal) - To explain the steps associated with conducting research - How theory and research are intertwined with each other - How to collect secondary research on a topic - How to collect primary data on a topic, including through surveys, experiments, content analysis, interviews, focus groups, and field studies - To explain the advantages and disadvantages of the different research approaches covered in class (surveys, experiments, content analysis, interviews, focus groups, and field studies) - How to work with SPSS to analyze quantitative data - How to interpret statistical analyses of quantitative data in SPSS - How to build a report from your analyses that can be easily understood by audiences unfamiliar with research Learning Objectives for specific modules follow below: Module 1 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Access course materials. 2. Differentiate ways to communicate with instructor. 3. Read how grade will be assessed this semester. Module 2 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Explain the importance and value of research. 2. Explain the key attributes of research. 3. Define research. 4. Differentiate between the various types of research. 5. Explain how communication research evolved alongside media. 6. Recognize and be able to define key research that were outlined in the lectures. 7. Explain the research process. 8. Be able to use iPoll for finding survey questions and datasets. Module 3 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Explain the differences between positivism and naturalism as research paradigms. 2. Define theory. 3. Explain how theory fits into the research process. 4. Describe the steps of the research process. 5. Be able to write hypotheses and research questions. 6. Be able to use Web of Science to gather secondary research on a given topic. 7. Differentiate between concepts, variables, and attributes. 8. Define concept explication. 9. Conduct a meaning analysis of a concept. 10. Differentiate between the different levels of measurement. Module 4 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Explain reliability, why it is important, and the various tests associated with it. 2. Explain the process by which we measure average inter-item reliability (we’ll do this when we get to our Excel work). 3. Explain validity, why it is important, and the various tests associated with it. 4. Explain why ethics are important for understanding research and how we determine the ethics of our work. 5. Explain the key ethical questions we should ask ourselves as we design and collect our data. Module 5 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Explain the importance of sampling. 2. Define key sampling terms. 3. Differentiate between probability and non-probability sampling and identify the specific types of sampling that fall within those two categories. 4. Explain frequency distributions and their importance to sampling. 5. Explain the logic behind sampling. 6. Calculate a sample error for samples of different sizes. 7. Explain what diminishing returns mean in the context of sampling. Module 6 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Identify and explain the problems that can plague polling and survey research. 2. (Constructively) criticize survey questions written by others. 3. Define what a survey is and identify the advantages and disadvantages of collecting data with surveys. 4. Explain the major considerations related to organizing a survey instrument and writing survey questions. 5. Recognize the strengths and weaknesses of different survey question formats. 6. Explain the advantages and disadvantages of different survey delivery systems (online, telephone). 7. Explain what a response rate is and how to maximize it. Module 7 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Define what an experiment is and explain the advantages and disadvantages of the methodology. 2. Explain the steps for running a successful experiment. 3. Explain the differences associated with different experimental designs. 4. Define and explain the threats to the internal and external validity of an experiment. 5. Explain causality as it relates to experiments and how we achieve it. Module 8 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Explain the differences between qualitative and quantitative research. 2. Explain the differences when working with qualitative and quantitative data. 3. Define what an ethnography/field study is, explain the the steps with running one, and explain its advantages and disadvantages. 4. Define what an interview is, explain the steps with running one, and explain its advantages and disadvantages. 5. Define what a focus group is, explain the the steps with running one, and explain its advantages and disadvantages. Module 9 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Define what a content analysis is and when we might use one. 2. Explain the steps associated with running a content analysis, including what takes place at each. 3. Explain the advantages and disadvantages associated with running a content analysis. 4. Explain how advances in technology, including the growth of social media, have changed how researchers approach the content analysis methodology. Module 10 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Log into the virtual lab (and find other locations on campus that have SPSS access). 2. Explain how to open data in SPSS and interpret the different windows of information in the software program. 3. Run and interpret a frequency in SPSS (and know when it is important and appropriate to do so). 4. Recode variables in SPSS (and know when it is important and appropriate to do so). 5. Create indices in SPSS (and know when it is important and appropriate to do so). Module 11 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Run a reliability test in SPSS (and know when it is important and appropriate to do so). 2. Run a crosstab in SPSS (and know when it is important and appropriate to do so). 3. Run a correlation in SPSS (and know when it is important and appropriate to do so). 4. Run a t-test in SPSS (and know when it is important and appropriate to do so). 5. Run an ANOVA in SPSS (and know when it is important and appropriate to do so). Module 12 Learning Objectives: Upon successful completion of this module, you should be able to: 1. Run a crosstab with two independent variables in SPSS (and know when it is important and appropriate to do so). 2. Explain the best ways of presenting data for lay audiences.
Topical Outline
1. Course introduction 2. Why we research the way we do 3. Theory and measurement 4. Reliability and validity 5. Sampling 6. Surveys 7. Experiments 8. Qualitative data (field studies, interviews, and focus groups) 9. Mid-term examination 10. Content analysis 11. Data analysis I: Opening SPSS and basic frequencies, recodes, and indices 12. Data analysis II: Reliability, crosstabs, correlations, t-tests, and ANOVA 13. Data analysis III: Complex crosstabs/Report writing 14. Work on final project 15. Thanksgiving break 16. Final project (feedback and presentations)
Public CV