MC 451 · Fall 2026

Research Methods in Mass Media

You will run a real content analysis from question to published paper: build the codebook, draw the sample, code the data, test the relationship, and publish a White Paper at a public address anyone can open.

Start here: your first week

You do not have to read this whole page today. Do these five things and you are current.

  1. Read the Week 1 row of the schedule so you know what the first two sessions are.
  2. Skim how the course works, which is the part of this page most likely to change how you plan your semester.
  3. Sign the Syllabus Contract in Blackboard. It is due at the end of Week 1 and it is worth 25 points.
  4. Look at Week 11 on the schedule now, not in November. It carries 125 points and it is the single most common way students lose ground in this course.
  5. Bookmark this page. It is the live syllabus. A printed copy goes stale; this does not.

Nothing needs to be installed yet. Software comes in Week 2, with a walkthrough.

How to reach me

  • Office hours are the primary support channel. Drop in during the times above in Dunham Hall 1017, or schedule an appointment.
  • Email (aleith@siue.edu) is preferred for time-insensitive and confidential communication, such as grades or accommodations. Expect a response within 24 hours on weekdays.
  • Course discussion (Blackboard) is for student-to-student questions. I participate periodically; bring instructor-directed questions to office hours or email.

In all communication, clearly stated needs save us both time. State what you have tried, what is not working, and what kind of response you are hoping for.

What this course is

MC 451, Research Methods in Mass Media, introduces students to core research methodologies used in mass communication. Students explore quantitative and qualitative research methods, including surveys, experimental designs, content analysis, and in-depth interviews. The course emphasizes the skills necessary for the design, execution, and presentation of research studies while engaging with the professional and ethical principles that guide mass communication research.

Across the semester students complete a two-part content analysis project: a qualitative study that develops coding variables through immersion, and a quantitative study that tests relationships in the coded data. The final deliverable is a professional White Paper, published to GitHub Pages as a Quarto book.

Course objectives and goals, in full

By the end of this course, students will be able to:

  • Understand and apply the principles and laws of freedom of speech and press, particularly within the context of the United States, while gaining a global perspective on freedom of expression, including the right to dissent, monitor power, and petition for redress of grievances.
  • Demonstrate an understanding of the historical role of professionals and institutions in shaping mass communications and critically evaluate their impact on the development of media systems.
  • Recognize and analyze the impact of diversity in mass communications, including but not limited to gender, race, ethnicity, and sexual orientation, within both domestic and global contexts, and appreciate the significance of this diversity in shaping media content and audience reception.
  • Apply ethical principles in conducting and presenting research, ensuring that all research practices adhere to standards of truth, accuracy, fairness, and respect for diversity.
  • Think critically, creatively, and independently in the design and execution of research projects, developing robust research questions and applying appropriate methodologies.
  • Conduct rigorous research, evaluate information using appropriate methods, and communicate research findings clearly, concisely, and in an ethically responsible way.

The course also aims to:

  • Equip students to engage with mass communication research critically, so they can both conduct independent study and assess the research of others.
  • Foster an appreciation for the role of mass communications in reflecting and shaping societal values, particularly concerning diverse populations.
  • Prepare students to apply digital tools and technologies in their research, so they can navigate and contribute to the evolving landscape of mass media research.
  • Develop students’ ability to communicate research findings effectively to both academic and non-academic audiences, using appropriate forms and styles.

How the course works

The course runs in five roles. The Journalist is a throughline, not a stage: a weekly reading journal that runs the length of the term. The other four are sequential, and each hands you the materials for the next. Those four track the textbook’s five parts.

Points by phase, out of 1000
Phase When Points What you hand in
I. The Journalist Weeks 1 to 15 150 Weekly Reading Journal (10 pts per week for 14 teaching weeks, plus 10 pts consistency)
II. The Architect Weeks 1 to 4 125
  • GitHub Profile (25)
  • Syllabus Contract (25)
  • Project Setup (25)
  • Librarian Visit Report (50)
III. The Builder Weeks 5 to 11 250
  • Annotated Manuscript (25)
  • Project Prospectus (25)
  • Topic Selection and RQs (25)
  • Definitions Practice (25)
  • Codebook and Qual Memo (50)
  • Sampling Plan and Pilot (75)
  • CITI Ethics Certification (25)
IV. The Analyst Weeks 11 to 13 225
  • Data Wrangling in R (50)
  • Describing Data in R (75)
  • Inferencing Data in R (100)
V. The Publisher Weeks 15 to 17 250 White Paper (250)
Total 1000

The White Paper (250 points)

The white paper follows IMRaD: Introduction, Methods, Results, Discussion, in that order, with a short abstract in front and references at the close. The structure is a contract with the reader, who knows where to look for the question, the procedure, the finding, and the meaning.

Component Points Full marks means
Introduction 30 States the question and why it is worth asking. The theoretical lens is doing work, not decoration, and it sets up something the study can actually deliver.
Methods 60 Says exactly what was done, in enough detail that another researcher could repeat it: the codebook, the sampling procedure, the reliability check, and the wrangling steps.
Results 50 Reports what was found, plainly and without interpretation: distributions, group means, the test statistic with its degrees of freedom, its p-value, and its effect size. Figures are labelled and captioned.
Discussion 50 Says what the results mean, answers the question the Introduction asked, and states the study’s limits honestly. Effect size is characterised accurately rather than inflated.
Abstract and references 20 The abstract summarises all four sections. References are complete and in APA 7th edition.
Reproducibility and publication 25 The document renders from source with no pasted numbers, and is live at a public address. A paper nobody can open scores nothing.
Reflection 15 One specific paragraph naming what proved harder than expected, where a rule was ambiguous in practice, what the data could not answer, and what a second attempt would change.

The reflection is graded on candor and precision, not on whether the study went well. A researcher who can say exactly where their study is weak is a researcher who understands it.

Grading

Grade Points Percentage
A 900 to 1000 90 to 100%
B 800 to 899 80 to 89%
C 700 to 799 70 to 79%
D 600 to 699 60 to 69%
F below 600 below 60%

Rubrics are checklists. You start at full credit and lose full or partial points for each item that is incorrect or missing. You are welcome to raise point disputes during office hours. In special cases, opportunities to address mistakes for partial credit are provided.

Feedback timeline. Grades with feedback are posted within one week of the due date for most assignments. Find your grades under My Grades in the Blackboard course menu.

Late work. Late submissions (after Friday 11:59 PM) lose 10% of the assignment grade per business day, for up to one week. After one week, the assignment receives a zero unless an accommodation has been arranged in writing before the original due date. Non-emergency extensions must be requested before the deadline. If you are experiencing an emergency, contact me as early as possible; I work with students case by case when contacted proactively, but I cannot extend deadlines retroactively.

Resubmission. Assignments worth 50 or more points may be revised and resubmitted within one week of grade posting. The final grade is the average of the original and the resubmission. For example, a 60% plus an 80% resubmission gives a 70% final grade.

Materials and technology

Textbook. This course uses an Open Educational Resource (OER): From Vibes to Variables: A Field Guide to Open Media Science (3rd Ed.), free and online at aura-lab-siue.github.io/v2v. There is no textbook to purchase. Read it as-is; the optional “Graduate edition” toggle stays off.

Software. All software is free and open-source. Installation guides are on the setup pages.

  • VS Code: your single workspace for writing, R, Quarto, and Git
  • R: statistical computing environment, run inside VS Code
  • Quarto: scientific and technical publishing
  • Git and GitHub: version control and your White Paper

What you need to have. A reliable computer and internet connection are required.

  • A desktop or laptop computer for the R analysis in Phases IV and V; this work cannot be completed on a phone or tablet.
  • A current version of a supported browser (Chrome, Edge, Firefox, or Safari), kept updated.
  • Cloud storage (OneDrive, Google Drive, or similar) for backing up your project.
  • VS Code, R, and Git installed and working by the end of Week 2. The setup pages include a walkthrough.

Technical problems are not an excuse for missed deadlines, but they can often be resolved quickly. See Getting help.

Artificial intelligence

AI coding assistants (for example, GitHub Education Copilot) are permitted in this course as supervised aids, with disclosure. This is a course-specific policy; unless a course states otherwise, SIUE’s default is that AI use is prohibited.

  • Permitted: using AI to remember syntax, scaffold code you understand, or draft prose you then revise, provided you can explain everything you submit and you disclose the assistance.
  • Disclosure is required: when AI shaped work you submit, note in your weekly journal what you used it for and how you checked its output.
  • Not permitted: submitting AI-generated work as your own without disclosure; using AI to fabricate citations, data, or results; or using AI to circumvent a learning objective. These are academic dishonesty.

You are accountable for everything you submit, including whatever role AI played in producing it. See the GitHub Education Copilot guide for how to use it responsibly.

Participation and interaction

Success in this course requires attendance and active participation. Regular engagement with the readings, activities, and discussions is essential.

Regular and Substantive Interaction (RSI) is required under U.S. Department of Education regulations. In this course, RSI takes the form of direct instruction and in-class activities, weekly office hours as a live support channel, substantive instructor participation in discussions, and personalized written feedback on graded work on the timeline above. Your part is to engage on a weekly cadence: read the assigned chapters, participate in class, and submit work on time.

Getting help

You do not need to know how the university is organized to get help from it. Find your situation on the left and start at the office on the right. If you are not sure, ask me and I will point you.

Where to go, by what you need
If you need Start here
A deadline you cannot meet Email me before the deadline. I work with students case by case when contacted early; I cannot extend a deadline that has already passed.
An accommodation for a disability ACCESS, Student Success Center 1203. myaccess@siue.edu, 618-650-3726. You do not need a diagnosis in hand to start the conversation.
Help with the writing itself The Writing Center. Bring a draft at any stage, including a blank page.
Help with the course content My office hours first. Then the Tutoring Resource Center and Supplemental Instruction.
Finding sources Lovejoy Library. Ask for the Mass Communications subject librarian by name; that is what they are there for.
A computer, software, or login problem ITS: 618-650-5500, help@siue.edu. Check ITS System Status first, and search the ITS KnowledgeBase.
To talk to someone about your mental health Counseling and Health Services, Student Success Center 0222, 618-650-2842. Appointments through Cougar Care (SIUE login).
Food, housing, or money to be short Financial Aid and the Kimmel Belonging and Engagement Hub, Morris University Center 2027, 618-650-3180. Tell me too, if it is affecting your work in this course.
To report harassment or discrimination Office of Equal Opportunity, Access, and Title IX Coordination (EOA), Rendleman 3316.
Help choosing courses or a major Academic Advising, and the Career Development Center, 618-650-3708.

Services for students needing accommodations

It is the policy and practice of SIUE to create inclusive learning environments. If aspects of the instruction or design of this course create barriers to your inclusion or to accurate assessment of achievement, please contact Accessible Campus Community and Equitable Student Support (ACCESS) as soon as possible. Register with ACCESS online at siue.edu/access or in person in the Student Success Center, Room 1203. Email myaccess@siue.edu or call 618-650-3726.

Accommodations are not a favor and they are not remedial. Tell me what you need and we will make it work.

Cougar Care

College life can be challenging, and I support students prioritizing their mental health. Counseling is available at the Student Success Center, Room 0222. Make an appointment at cougarcare.siue.edu or call 618-650-2842.

Full list of academic and student services

University policies

Academic integrity

The expectations and academic standards in the Student Academic Code (3C2) apply to all courses at the University, regardless of modality. Plagiarism (the use of another person’s words or ideas without credit) and cheating will not be tolerated and may lead to failure on an assignment, in the class, or dismissal from the University, per the SIUE academic dishonesty policy (3C1). Cite your data sources and collaborators.

Diversity and inclusion

SIUE is committed to respecting everyone’s dignity at all times. Our classroom must be a place where students and instructors feel safe and supported. Systems of oppression permeate our institutions and our classrooms; all students and instructors share responsibility for affirming inclusion, equity, and social justice. Racism, sexism, classism, ableism, heterosexism, xenophobia, and other social pathologies will not be tolerated, and violations will be enforced in line with the SIUE Student Conduct Code. The Kimmel Belonging and Engagement Hub is a resource for students.

Pregnancy and newly parenting

This course follows SIUE’s Newly Parenting Policy (3C15). Students may request accommodations through the Office of Equal Opportunity, Access, and Title IX Coordination (EOA).

Technology and privacy

This course uses Blackboard; review the Anthology Blackboard Privacy Statement for how your data is handled. The course also uses GitHub; review GitHub’s privacy policy before creating an account.

Recordings of class content

Any recordings of class sessions are for the educational use of students enrolled in this course only. Students may not copy, share, or distribute recordings without the written permission of the instructor. Office hours are not recorded, so that conversations about grades, accommodations, or personal circumstances stay private.

Subject to change

All material, assignments, and deadlines are subject to change with prior notice. Watch the course announcements and Blackboard regularly. This page is the live version of the syllabus; if a printed copy and this page disagree, this page is correct.

Weekly schedule

Lecture decks for every session are posted at MC 451 Lecture Decks.

The course runs on a Tuesday / Thursday rhythm: one session teaches a concept, the next applies it to your own project (labs and studios marked). Every assignment is a building block of your final White Paper. Sessions are numbered S1 to S28.

ImportantWeek 11 carries 125 points

Week 11 is the heaviest week of the term. The Sampling Plan and Pilot (75 pts) and Data Wrangling (50 pts) are both due Friday, November 6. That is deliberate: the Sampling Plan is given an extra week so the pilot coding is real work rather than rushed work, and that extra week places it alongside the first R assignment. Plan for it from Week 1, and draft the sampling plan during Week 10.

Week Dates Tuesday Thursday Due
1 Aug 25 / 27 S1 · Orientation: syllabus, the five phases, your project S2 · Ch 1 The Science of Storytelling Syllabus Contract
2 Sep 1 / 3 S3 · Ch 2 The Open Workspace (R, VS Code, Git/GitHub) S4 · Ch 2 project-setup lab GitHub Profile
3 Sep 8 / 10 S5 · Ch 3 Ethics (Belmont, IRB, consent) S6 · Ch 4 Intelligence Gathering, librarian visit Project Setup
4 Sep 15 / 17 S7 · Ch 4 reading & annotating; the literature map S8 · Ch 5 Theory as a Lens Librarian Visit Report
5 Sep 22 / 24 S9 · Ch 5 variables & hypotheses S10 · Ch 6 Research questions Annotated Manuscript · CITI Certification
6 Sep 29 / Oct 1 S11 · Ch 6 the prospectus; pre-registration S12 · Ch 7 Structured Listening; field notes Topic Selection & RQs
7 Oct 6 / 8 S13 · Ch 7 manifest vs. latent; sampling observation S14 · Ch 8 the operationalization gap Project Prospectus
8 Oct 13 / 15 S15 · Ch 8 levels of measurement; reliability & validity S16 · Ch 8 building the codebook [studio] Definitions Practice
9 Oct 20 / 22 S17 · Ch 9 [R] coding the codebook S18 · Ch 9 [R] reading data vs. the codebook; qual memo Codebook & Qual Memo
10 Oct 27 / 29 S19 · Ch 10 The Sample: SRS, stratified, drawing S20 · Ch 10 [R] the pilot; kappa / alpha
11 Nov 3 / 5 S21 · Ch 11 [R] Wrangling the Data S22 · Ch 11 [R] wrangling lab Sampling Plan & Pilot · Data Wrangling [R] · 125 pts, the heaviest week
12 Nov 10 / 12 S23 · Ch 12 [R] Describing: descriptive statistics + graphics S24 · Ch 12 [R] describing lab Describing Data [R]
13 Nov 17 / 19 S25 · Ch 13 [R] Inferential: t-test, ANOVA, regression S26 · Ch 13 [R] inference lab; White Paper assigned Inferencing Data [R]
14 Nov 23–27 Thanksgiving Break, no class
15 Dec 1 / 3 S27 · Ch 14 The Publisher; assemble your paper S28 · White-paper studio: peer review; the reflection
16 Dec 8–12 Work Session: open lab / support
17 Dec 14–18 Finals Week White Paper

Schedule subject to change with notice.