Introduction to Sociology

Fictional sample for demonstration. Silver Oak University and Prof. Adeyemi are fictional, used to showcase thecoursemaker.com. No real institution, course, or person is implied or endorsed. The discipline's real founders and theorists (Durkheim, Marx, Weber, Du Bois, and others) are named factually as the subject matter.
Showcase note: this course is configured in adaptive-learning mode (the default), and the policies below describe that configuration. The sample folder also ships a traditional variant of every discussion and assignment for side-by-side comparison, plus a weekly Sociology-in-Action / Data & Observation Workshop on every instructional week.

Course Description

Introduction to Sociology is a one-semester, lower-division survey of the systematic study of human society. We follow the natural arc of the discipline — the sociological imagination & the three theoretical perspectives → research methods & reading social data → culture & socialization → social interaction, groups & deviance → stratification & global inequality → race, gender & the axes of inequality → the major institutions → social change & movements — and at each step we lead with the plain-language idea before the terminology. You will learn to see the general in the particular, to run a social phenomenon through structural-functionalism, conflict theory, and symbolic interactionism, and to read and evaluate the social data that sociology runs on.

The emphasis throughout is on understanding, evidence, and application, not memorizing definitions. We draw examples from your own life and community, reference the discipline's classic studies and founders accurately, and use a weekly AI-tutor tutorial and a weekly Sociology-in-Action / Data & Observation Workshop as low-stakes places to practice the discipline's two signature moves: applying theory, and reading the data. No prior sociology experience is assumed.

Learning Objectives

By the end of the course, you will be able to:

1. Apply the sociological imagination and the three major theoretical perspectives (structural-functionalism, conflict theory, symbolic interactionism) to interpret social phenomena, distinguishing private troubles from public issues.
2. Describe and evaluate sociological research methods and interpret social data, distinguishing correlation from causation and identifying sampling and measurement bias.
3. Analyze culture and socialization — values, norms, symbols, subcultures, ethnocentrism vs. cultural relativism, the agents of socialization, and the social development of the self.
4. Explain social structure, groups and organizations, and deviance and social control, including functionalist, conflict, and interactionist explanations of deviance.
5. Analyze social stratification, class, and global inequality, comparing functionalist and conflict theories and modernization vs. dependency/world-systems perspectives.
6. Analyze race and ethnicity, sex and gender, and other axes of inequality as socially constructed, reasoning from documented evidence rather than anecdote or stereotype.
7. Explain the major social institutions — family, education, religion, the economy and work, and politics.
8. Analyze social change — demography, urbanization, collective behavior, and social movements — and the forces that drive it.

Student Learning Outcomes (SLOs)

• SLO A — Sociological theory & analysis. Apply the sociological imagination and the major theoretical perspectives to interpret social phenomena and institutions.
• SLO B — Evidence & data literacy. Locate, read, and evaluate sociological evidence and social data — including the distinction between correlation and causation — and reason from evidence rather than anecdote or stereotype.

Required Materials

There is no required textbook, and you will pay nothing for course materials. Readings, videos, and the data-portal sources used in the weekly workshops are delivered as links to external resources posted in each weekly module. The reading load is intentionally light and is meant to support, not replace, the in-class work.

You will need:

• A device with a web browser and internet access.
• Access to one approved AI chatbot for the weekly Lecture Tutorials, the adaptive-learning Discussions and Assignments, and the AI-critique moment in each weekly Workshop (see the AI-Use Policy below).

Grading

Your course grade is the weighted total of the groups below. Weights sum to 100%.

Attendance is tracked at every session but is not weighted (see the Attendance Policy).

Letter-Grade Scale

Late & Make-Up Policy

• Late penalty: 10% per day. Submitted work loses 10 percentage points of its earned score for each day (or part of a day) it is late.
• Quizzes, the Midterm, and the Final are time-bound. Make-ups are arranged only for documented emergencies — contact Prof. Adeyemi as early as possible, ideally before the due date.
• Practice exercises are ungraded and exist for your benefit; the late penalty does not apply to them.
• If something serious is getting in the way of your work, reach out early. It is almost always easier to arrange support before a deadline than to repair a grade after it.

AI-Use Policy

This course uses AI as a learning partner for several activities, and it draws a clear line for everything else. Read this section carefully.

Approved chatbots

You must use one of these three approved AI chatbots:

• Gemini
• Claude
• ChatGPT

The free tier of any of these is sufficient. You may pick whichever you prefer.

AI in this course (adaptive-learning activities)

This course uses an approved chatbot — Gemini, Claude, or ChatGPT (free tier is fine) — as part of several activities. Your Lecture Tutorials, Discussions, Assignments, and the AI-critique step of each weekly Workshop are adaptive-learning activities you complete with the chatbot:

• Weekly Lecture Tutorials — work through the week's ideas in conversation, then submit the conversation share link and your Completion Summary.
• Discussions — think a question through in a real-time dialogue with the chatbot, then post the AI-generated summary plus your chat share link to the discussion board (and reply to peers).
• Assignments — work AI-posed problems with a chatbot coach that grades and teaches you as you go, then submit the coach's self-scored report (the line beginning STUDENT'S SCORE:) plus your chat share link.
• Sociology Workshops — after you read the data or run the observation yourself, bring in the chatbot to analyze it, then catch its mistakes (the AI-critique moment): overgeneralization or stereotyping, confusing correlation with causation, or a fabricated statistic or study.

For all of these, the share link is part of your submission — treat the conversation as your work, keep it on-topic, and do your own thinking.

Permitted vs. not permitted

• AI may be used on your coursework — the Lecture Tutorials, Discussions, Assignments, the weekly Workshops, and the ungraded Practice Exercises. (For the adaptive activities above, working with the chatbot is the activity.)
• AI may not be used on the Quizzes, the Midterm, or the Final — these are closed to AI and must be entirely your own work, unless an item explicitly says otherwise.

A discipline-specific habit: the tool drafts, you judge

Sociology runs on evidence, and chatbots are unreliable narrators of evidence — they invent statistics, fabricate plausible-sounding "studies," misattribute theories, overgeneralize about groups, and slide from correlation to causation. Every week you will practice catching exactly these errors. The skill the course is building is not "use AI" or "avoid AI" — it is to verify every figure, study, and attribution against the source and to never let a correlation masquerade as a cause.

Disclosure

The adaptive activities (tutorials, discussions, assignments, workshops) need no separate disclosure — the share link already documents your AI use. If you use an AI tool to help you think about any other graded work, add a one-line note stating which tool you used and how.

Alignment with academic integrity

Using AI as described here is encouraged and fully consistent with the integrity standard below. The violations are fabricating or doctoring a chat you submit, and using AI on the closed assessments (Quizzes, Midterm, Final). When in doubt, ask before you submit.

Attendance Policy

This is an in-person course that meets twice a week, and the in-class work — the three-perspective walkthroughs, read-the-data moments, think-pair-share, and the technology-and-AI-critique moments — is where much of the learning happens.

• Attendance is tracked at every session. It is not part of your weighted grade, but a strong attendance record is expected and consistent absence will show in your performance.
• Arrive on time, stay for the full session, and engage professionally with your classmates and instructor.
• If you must miss a session, notify Prof. Adeyemi in advance when possible and review the module materials to catch up. You remain responsible for any content, announcements, and due dates from a missed class.

Academic Integrity

You are expected to do your own work and to represent it honestly. Cheating, plagiarism, unauthorized collaboration, and submitting another's work — human or AI — as your own are violations of academic integrity and will be handled according to university policy, which may include a failing grade on the work or in the course. Collaboration is welcome where an assignment invites it; when in doubt about what is allowed, ask first. Holding to this standard is what makes your grade — and your degree — mean something.

A note on course content: Sociology studies society honestly, which means several topics in this course — race and ethnicity, class and poverty, gender and sexuality, deviance and crime — are personally and politically charged. We approach them as a science: we lay out the competing theoretical perspectives and the evidence fairly, we report well-documented facts plainly, and we make room for reasoned disagreement about how to interpret them. You are expected to engage classmates' views with respect even where you disagree. The goal is sharper thinking and better evidence, not a required conclusion.

Accessibility: Silver Oak University is committed to equal access. Students who need accommodations should contact the campus disability services office to arrange them; notify Prof. Adeyemi early in the term so supports can be in place. (Placeholder — institutions should insert their official accessibility, Title IX, and integrity statements here.)

Course Schedule — Fall 2026 (16 Weeks)

Term runs Aug 31 – Dec 18. Campus holidays: Labor Day (Sep 7), Veterans Day (Nov 11), Thanksgiving (Nov 26–27). Week 16 is reserved for finals. Dates are the Monday of each week.

Practice exercises and a Lecture Tutorial are part of every week's module; the table lists the graded touchpoints. The schedule may be adjusted with advance notice; changes will be announced in the course.