Bio 111 | Session 2

Class reminders and logistics

• The instructor mentions hearing difficulties and uses this slide for your convenience.

• Topic today: the scientific method.

• Team meetings: next Tuesday on Teams.

• Seating requests: an announcement will be posted today; you must inform the instructor before 02:00 today. After that, teams will be formed and the instructor won’t do extra work for 15–20 minutes per person who ignored announcements.

• Browser tip: do not use Safari for Canvas; Chrome or Edge work better with Canvas and related tools.

• Password help: if you don’t know your passwords, visit Six Tech for assistance.

• EdgeRealm setup: if you can’t get on EdgeRealm, there’s a process to configure your computer; visit the computer help center in the basement of the library if needed.

• Lab flow registration: if you haven’t registered yet, do it; there are assignments due before your lab.

• Lab timing caveat: if your lab is on Monday, the instructor is not guaranteed to help on Sunday night. Personal plans may be in place; plan ahead.

• One class time for everyone: this is to manage 200 students; individualized teaching isn’t feasible.

• Seating chart location: Canvas; submit seating needs by 2:00 PM.

• Learning objectives: shown on slides; found in Canvas within the module (a page for learning objectives). They’re also included in skeletal notes so you can see them while taking notes.

• Study guide notes: this is your study guide; reading with a purpose means focusing on objectives rather than trying to read every detail in the book.

• Reading strategy: yes, you should take notes while reading, but keep the learning objectives in mind to guide what’s important.

Learning objectives and study guidance

• Objectives reside in Canvas, module section; skeletal notes include them for quick reference.

• Reading with purpose means identifying what is essential to understand and will be tested; not every detail in the book is covered in class.

• This slide is presented as a study guide to help you focus your reading and note-taking.

Characteristics of life and viruses

• Opening activity: discussion on whether viruses are alive; a brainstorm of life characteristics is facilitated by the instructor.

• Official list of life characteristics (as gathered in the session):

  • Reproduce

  • Eliminate or manage waste products

  • Consume/metabolize food

  • Homeostasis (maintain internal environment within narrow limits)

  • Examples: body temperature, blood pressure, blood sugar, hormone regulation

  • Grow

  • Be made of cells (unicellular or multicellular; bacteria are unicellular)

  • Evolve (at the population level; offspring with advantageous traits survive)

  • Die (not immortal; death is part of life)

  • Use energy

  • Gas exchange for cellular metabolism

  • Respond to stimuli

  • Genetic program (pass on genetic information to the next generation)

  • Organelles inside cells (little “organs” inside cells)

• Viruses and life: most biologists say viruses are not alive because they are not made of cells, cannot maintain a stable state on their own, cannot grow, and cannot make their own energy; they hijack host cells to replicate and adapt, which makes them more like androids than true living organisms.

• Significance: the distinction between living and non-living agents influences how we study them and how we think about biology from foundational principles to applied research.

The scientific method: overview and rationale

• Science is not a mere collection of facts; it is a way of looking at the world that emphasizes falsifiability.

• Key difference from religion: science requires the possibility to falsify a claim; you must be able to design experiments that could disprove a hypothesis.

• Core sequence of the scientific process (general outline):

  • Exploration and curiosity: ask questions, observe, read, and be skeptical of new claims.

  • Formulate a hypothesis or a model: proposed explanation that has a justification based on prior knowledge.

  • Make predictions: outcomes expected if the hypothesis is true; predictions should be grounded in the hypothesis.

  • Conduct experiments and make observations: gather data; control variables when possible.

  • Interpret data and assess results: determine whether the hypothesis is supported or refuted; use this to narrow or rule out ideas.

  • Develop and refine theories: a theory is a well-supported explanation that survives extensive testing across many scientists and disciplines over long periods of time (e.g., gravity).

  • Communication: publish results, discuss experiments, and share findings to allow replication and critique.

• If a hypothesis is supported by evidence, it gains credibility; if not, it can be falsified or revised.

• Distinction between hypothesis, prediction, and theory:

  • Hypothesis: a proposed explanation for an observation, backed by reasoned justification.

  • Prediction: an expected outcome of an experiment based on the hypothesis.

  • Theory: a robust, well-supported framework that explains many observations and experiments over time.

• Example linkage to online information and how science differs from misinformation: the need for controlled experiments and verifiable data instead of anecdotal claims.

• Practical relevance: understanding the scientific method helps you evaluate claims critically in everyday life and in future research.

Case study: chickens, egg production, and feed controversy

• Observation used in discussion: in late fall and winter, some chickens lay fewer eggs; after switching feeds (often after noticing reduced laying), some report increased egg production.

• Common interpretation in social media: Tractor Supply feed is bad for egg production.

• Instructor’s assessment of the claim: the observation alone does not establish a hypothesis because the proposed explanation (why Tractor Supply feed would affect laying) is not specified in terms of mechanism or nutrients.

• What’s missing: a proper investigation that tests whether feed type truly affects egg production under controlled conditions.

• Types of investigations:

  • Controlled experiments: involve a treatment group and a control group, with all other variables held constant to isolate the effect of the independent variable.

  • Observational studies: collect data without controlling all variables; more natural settings but harder to infer causation due to confounding factors.

• Example: designing a study on the effect of fertilizer on tulips to illustrate controlled vs observational approaches.

• In the chicken scenario, a proper experiment would be designed as follows:

  • Hypothesis (proposed explanation): Chickens fed Tractor Supply feed lay fewer eggs due to lower calcium and protein content, compared to a different feed with higher nutrients.

  • Independent variable: type of feed (feed category or nutrient content).

  • Dependent variable: number of eggs laid by the chickens.

  • Controlled variables and design considerations:

  • Use the same strain/breed and similar age of chickens.

  • Keep housing, environment, and daylight exposure consistent.

  • Control day length (cycle lighting) to account for seasonal effects on laying.

  • Decide between free-range vs caged, and standardize water access.

  • Possible confounding factors: daylight length (seasonality), molt cycles, breed differences, age, housing conditions, random variation in individual chickens, other dietary components besides calcium and protein.

  • Predictions based on the hypothesis: if Tractor Supply feed has fewer essential nutrients, then the group on that feed should lay fewer eggs than the control group under otherwise identical conditions.

  • If results show no difference or opposite results, re-evaluate hypothesis, nutrient content, or other variables.

• Key definitions from the discussion:

  • Independent variable: the variable deliberately changed or controlled (the feed type).

  • Dependent variable: the outcome measured (number of eggs laid).

  • Confounding factor: an uncontrolled variable that could influence the outcome, leading to misleading conclusions.

• Seasonal considerations and additional factors mentioned:

  • Daylight length tends to be longer in summer (higher egg production) and shorter in winter (lower production).

  • Molting and energy allocation during growth of feathers can reduce egg production.

  • Genetic factors, breed differences, and age influence baseline laying patterns.

• The instructor emphasizes: always distinguish between observation, hypothesis, prediction, and investigation; the most important part of scientific reasoning is understanding why a chosen answer is correct, not just selecting the correct option.

• Summary takeaway from the case study:

  • Observation alone is not enough to conclude causation.

  • A well-designed investigation (controlled experiment or robust observational study) is required to test the hypothesis and rule out confounding factors.

  • Clear definitions of variables and accounting for seasonality are essential for credible conclusions.

Experimental design: variables, controls, and confounding factors

• Key components of a controlled experiment:

  • Independent variable: what you change (e.g., feed type).

  • Dependent variable: what you measure (e.g., eggs laid).

  • Controls: conditions kept constant across groups (environment, housing, water, lighting, age, etc.).

  • Treatment vs. control groups: one group receives the experimental treatment, the other does not.

  • Confounding factors: any other variable that might influence the outcome, which you attempt to minimize or randomize away.

• Observational studies vs controlled experiments:

  • Observational: you observe natural conditions without manipulating variables; easier to conduct but weaker for establishing causality due to potential confounders.

  • Controlled experiments: deliberately manipulate the independent variable while keeping other factors constant; stronger for establishing cause-effect relationships.

• Practical example from the chicken discussion:

  • If aiming to test feed quality, you could design two groups of chickens of the same breed and age, housed identically, with the only difference being the feed type.

  • Common controls to consider: daylight exposure, temperature, water availability, space, and management practices.

• Confounding factors explained:

  • A confounding factor is a variable other than the one being studied that influences the outcome, potentially leading to erroneous conclusions.

  • Examples: seasonality, changes in sunlight, molt cycles, breed differences, or other dietary components not accounted for.

• How to strengthen a study:

  • Randomize assignment of chickens to treatment groups to distribute unknown confounders evenly.

  • Increase sample size to reduce random variability and improve statistical power (not explicitly quantified in the transcript but a standard practice).

  • Clearly define the nutrients or feed characteristics being tested rather than attributing effects to an undefined feed difference.

• Outcome framing for exams and assignments:

  • You should be able to identify independent and dependent variables in a described experiment.

  • You should distinguish between hypotheses and predictions.

  • You should recognize whether a claim has been tested via observation, controlled experimentation, or remains an untested assumption.

How this ties into course structure and study practices

• The professor connects these concepts to broader course goals for the semester: understanding how all biological processes work and how to evaluate evidence.

• The class will revisit experimental design through upcoming assignments:

  • In-class and team quizzes will require arguing why a particular answer is correct, which reinforces understanding of reasoning rather than memorization.

  • An observational experiment will be discussed on Tuesday (the interactive PowerPoint and a master gardeners talk titled “Why you might want to soil your undies”).

• Homework and resources:

  • Review the interactive PowerPoint and complete the associated activities before Tuesday’s discussion.

  • Ensure you’ve accessed the PowerPoints and resources uploaded by the instructor; some might be posted after the instructor returns to the office.

• Recap of where to find materials:

  • Canvas module contains learning objectives and the skeletal notes; the learning objectives appear on slides and are included in the skeletal notes for easy reference.

  • The course emphasizes using the objectives to guide reading and note-taking, not merely reading everything in the textbook.

• Final practical tips:

  • The most important skill is being able to explain why you chose a particular answer in an assignment or quiz, not just selecting it.

  • Online discussions and sharing ideas should be constructive and focused on evidence-based reasoning.

  • The instructor plans to post the PowerPoints after returning to the office; check back for updates.

Quick reference: key terms and definitions

• Hypothesis: a proposed explanation for observations, supported by a reasoned justification.

• Prediction: an expected outcome of an experiment based on the hypothesis.

• Theory: a well-supported explanation that has withstood extensive testing and scrutiny over time.

• Independent variable: the variable deliberately changed in an experiment (e.g., feed type).

• Dependent variable: the outcome measured (e.g., eggs laid).

• Confounding factor: an uncontrolled variable that could influence the results and lead to incorrect conclusions.

• Observation vs. investigation:

  • Observation involves noticing and recording phenomena.

  • Investigation involves designing experiments or structured data collection to test hypotheses and explore explanations.

• Seasonality: biological processes that vary with seasons, such as day length affecting egg production in chickens.

• Homeostasis: maintaining internal conditions within narrow limits (e.g., body temperature, blood pressure, blood sugar).

• Cellular requirements for life: cells, organelles, genetic program, energy use, growth, and reproduction.

• Viruses: generally not considered alive because they lack cellular structure and cannot independently maintain homeostasis, grow, or produce energy; they replicate by hijacking host cells.

Observations about course logistics and next steps

• Remember to submit seating requests by 02:00 today; 2 PM deadline is strict.

• If you’re having technical issues (EdgeRealm, Canvas, passwords), seek help promptly.

• Ensure you’ve registered for lab flow and complete assignments before lab time; plan ahead since instructor availability may be limited on Sundays.

• Review the module’s learning objectives in Canvas and use them as the primary guide for studying, in addition to reading the textbook.

• Prepare for upcoming discussions and team quizzes by understanding not just the answers but the reasoning behind them.

• PowerPoints and interactive materials will be uploaded after the instructor returns to the office; check Canvas announcements for updates.