This JupyterBook is the student-facing course reader for ASTR 120: Life in the Universe at East Texas A&M University.
The course explores one of the biggest scientific questions we can ask:
Are we alone in the universe?
The goal of this book is not to prove that life exists elsewhere. Instead, the goal is to understand how scientists approach that question using evidence from astronomy, planetary science, biology, chemistry, geology, physics, and computer science.
A planet in the habitable zone is not automatically inhabited. A molecule associated with life is not automatically proof of life. A strange observation is not automatically evidence of aliens. Scientific claims become stronger when multiple lines of evidence point in the same direction and alternative explanations become less likely.
This JupyterBook was developed from my ASTR 120 course lecture notes and slide materials, which were originally organized around Life in the Universe, 5th edition, by Bennett et al.
The book expands those course materials into a guided, student-facing digital reader with narrative explanations, figures, videos, checkpoint questions, structured review questions, and optional computational examples.
This site is not an official publisher resource and should not be treated as a replacement for the textbook where the textbook is required by the course.
Each chapter introduces major ideas connected to the search for life in the universe. Some sections explain scientific concepts, some focus on evidence, and some include examples, figures, videos, checkpoint questions, or simple calculations.
As you read, focus on four questions:
- What claim is being made?
- What evidence supports the claim?
- What other explanations are possible?
- What evidence would make the claim stronger or weaker?
These questions matter throughout the course. The search for life beyond Earth is exciting because the question is enormous, but the method is careful: claims require evidence, and evidence helps us decide how confident we should be.
Many sections are written as Jupyter notebooks. This means that some pages may include code cells, figures, calculations, or interactive elements.
You can:
- read the notes,
- answer checkpoint questions,
- watch embedded videos,
- run optional Python code,
- modify simple values and rerun calculations,
- open notebooks in Google Colab using the rocket icon at the top of the page,
- and use NotebookLM or other AI tools to help you study.
Python is included as an optional exploration tool. It may be used to repeat a calculation, make a simple graph, or show how changing one value affects another. You are not expected to become a programmer in this course.
You are not expected to be an expert in astronomy, biology, chemistry, mathematics, or programming.
This course is designed for students who are beginning to explore scientific questions about life in the universe. When mathematics appears, it will usually involve basic arithmetic, ratios, unit conversions, or interpreting graphs. When Python appears, the code will be short, commented, and optional unless your instructor says otherwise.
The most important skills are curiosity, careful reading, and a willingness to ask how we know what we claim to know.
AI tools can be useful when they help you learn. They can summarize sections, explain vocabulary, generate practice questions, help compare ideas, or give feedback on your understanding.
A useful AI prompt usually includes three parts:
- Persona — tell the AI what role to take.
- Context — tell the AI what you are studying.
- Task — tell the AI exactly what you want it to do.
For example:
Act as a patient introductory astronomy tutor. I am an ASTR 120 student learning about habitable zones for the first time. Explain what a habitable zone is, why it does not guarantee that life exists, and give me three checkpoint questions to test my understanding.
NotebookLM is especially useful because you can add these course notes as a source. You can ask it to summarize a section, create a study guide, generate review questions, or explain confusing ideas using the notes as its reference.
AI should support your learning, not replace your thinking. If an AI-generated explanation disagrees with the notes, class discussion, or a reliable scientific source, treat that disagreement as something to investigate.
This is the first complete public version of the Life in the Universe JupyterBook. Future updates may include typo corrections, accessibility improvements, refined captions, additional figures or interactives, and revisions based on student feedback.
If something feels unclear, that is useful feedback. Scientific learning often begins with a good question.
If this is your first time using the book:
- Read Who Are These Notes For?
- Skim the Book FAQ
- Read the sections on Science and Evidence, Mathematics and Optional Python, and Learning with AI and NotebookLM
- Open the first chapter and look for the main scientific question it is trying to answer
The course will return to the same habit again and again: identify the claim, examine the evidence, consider alternatives, and decide how confident the evidence allows us to be.