Introduction to Biology

Fictional sample for demonstration. Silver Oak University and Prof. Castellano are fictional, used to showcase thecoursemaker.com. No real institution, course, or person is implied or endorsed.

Course Description

General Biology I is the first semester of the majors' biology sequence, and the gateway course for biology, pre-health, and allied-health students. It builds the cell-and-molecular foundation the rest of the sequence is built on. We move along the natural arc of the subject — the process of science → the chemistry of life → macromolecules → cells & membranes → energy, enzymes & metabolism → cell division → inheritance → DNA & gene expression → gene regulation & biotechnology — and at each step we lead with the plain-language idea before the mechanism, then trace structure to function and the order of every process.

The emphasis throughout is on thinking like a scientist and reading biology's mechanisms and figures. Most of the course is conceptual and diagram-rich, but biology also has real quantitative pockets — pH, surface-area-to-volume, the mitotic index, and especially the probability and ratios of genetics — and we work those by hand with every step shown. A weekly lab is where the science gets done: you'll form a hypothesis, manipulate a variable, collect data on a free simulation or a simple at-home protocol, and interpret what you find. A weekly AI-tutor tutorial gives you a low-stakes place to practice — and to catch the chatbot's biology mistakes, a habit this course returns to every week.

A note on scope. This is the cell-and-molecular first semester. Evolution, biodiversity, and ecology belong to General Biology II and are not covered here — though natural selection runs through the course as the unifying lens that ties the genetics weeks together.

Learning Objectives

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

1. Describe the core practice of science in biology — the characteristics of life, the scientific method, controlled experimental design, and the difference between a hypothesis and a theory — and explain evolution's role as biology's unifying theme.
2. Explain the chemistry of life — atomic structure, chemical bonds, the emergent properties of water, and pH — and relate the structure of the four classes of biological macromolecules to their functions.
3. Compare prokaryotic and eukaryotic cell structure, relate eukaryotic organelles to their functions, and explain how substances cross the plasma membrane by passive and active transport.
4. Explain how cells obtain and transform energy — thermodynamics, ATP, and enzyme action — and trace the overview-level pathways of cellular respiration and photosynthesis.
5. Describe the eukaryotic cell cycle and mitosis, contrast mitosis with meiosis, and explain how meiosis and sexual reproduction generate genetic variation.
6. Apply the principles of inheritance — probability, monohybrid and dihybrid crosses, and extensions of Mendel (incomplete/co-dominance, linkage, sex linkage, pedigrees) — to predict the outcomes of genetic crosses.
7. Explain the structure and replication of DNA and how genes are expressed through transcription and translation (the central dogma).
8. Describe how gene expression is regulated, how mutations arise and affect organisms, and how foundational biotechnology tools are used to study and manipulate DNA.

Student Learning Outcomes (SLOs)

• SLO A — Scientific reasoning. Apply the process of science — form hypotheses, design and critique controlled experiments, and interpret biological data — to evaluate claims about living systems.
• SLO B — Structure-function & energy flow. Connect biological structures to their functions and trace how matter and energy move through cells and across levels of biological organization.

Required Materials

There is no required textbook, and you will pay nothing for course materials. Readings are delivered as links to external resources posted in each weekly module, and the weekly labs use free virtual simulations or simple, low-cost at-home protocols (also linked). The reading load is intentionally light and is meant to support, not replace, the in-class work, the labs, and the practice.

You will need:

• A device with a web browser and internet access.
• Access to the free virtual labs / simulations used in the weekly labs — PhET, HHMI BioInteractive, LabXchange, and Learn.Genetics — plus a virtual microscope (all free and linked in the modules).
• A few inexpensive household items for the at-home lab weeks (e.g., a clear cup, salt, dish soap; the specific list is in each lab).
• A basic calculator for the genetics and quantitative weeks (your phone's calculator is fine).
• Access to one approved AI chatbot for the weekly Lecture Tutorials, adaptive activities, and the lab AI-critique moment (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).

Per-item points: quizzes 10 · discussions 20 · assignments 100 · labs 50 · midterm & final 100 each.

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. Castellano as early as possible, ideally before the due date.
• Labs build on the week's objective and are best done in the lab session or the same week; if you must miss lab, contact Prof. Castellano about a virtual make-up.
• 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 requires you to use AI as a learning partner on your coursework, and it draws a clear line for the closed assessments. 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)

Your Lecture Tutorials, Discussions, Assignments, and the AI-critique step of each weekly Lab 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 — solve AI-posed biology problems and scenarios 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.
• Labs — after collecting your data, you'll ask the chatbot to interpret it, then catch its mistakes — a standing habit in this course, because chatbots routinely mis-order process steps, confuse mitosis with meiosis, garble genetics ratios, and mislabel structures.

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, Labs, 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. Quizzes and exams are built from auto-gradable items and are meant to confirm that you understand the biology.

Disclosure

The adaptive activities (tutorials, discussions, assignments, labs) 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 with two lectures and one lab each week, and the in-class work — worked examples, think-pair-share, the lab investigations, and the 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 the lab in particular is hard to make up — 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. Castellano 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.

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. Castellano 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. Exam weeks (8 & 16) carry no weekly lab. The schedule may be adjusted with advance notice; changes will be announced in the course.