Principles of Physics II Laboratory — PHYS 2212L
Course Details for Fall 2025
University of North Georgia’s College of Science & Mathematics
Department of Physics & Astronomy
Course Instructor
email: sarah.formica@ung.edu
Hours: MWF 10:00–11:00 AM
Hours: by appointment, book your appointment here.
Office Hours
Booking an Appointment
Respect for Diversity
I recognize that there is a vast untapped intellectual resource in all groups underrepresented in physics. For this reason, I am committed to making physics more accessible to everyone. It is my intent that students from all diverse backgrounds and perspectives be well served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength and benefit. It is my intent to present materials and activities that are respectful of diversity: gender, sexuality, ability, age, socioeconomic status, ethnicity, race, and culture. Your suggestions are encouraged and appreciated. Please let me know ways to improve the effectiveness of the course for you personally or for other students or student groups.
Course Catalog Description
Laboratory to accompany PHYS 2212. This course is a laboratory investigation of the fundamental laws of electricity, magnetism, optics, and modern physics. Corequisite: PHYS 2212. (1 credit hour)
Required Texts and Materials
All course materials will be accessed through UNG’s eLearning system, also known as D2L (Desire 2 Learn).
All labs will be completed in person using materials provided in the lab room. You are also welcome to bring in and use additional materials, such as your own smartphone apps or interesting items to investigate.
Learning Objectives
This lab is intended to be an introduction to experimental physics and to teach critical thinking through experimentation. We can think of critical thinking as always answering the question:
How do we know what to trust and what to do?
The objectives for this course fall under five big themes summarized as objectives. By the end of this course, you should be able to:
- Collect data and revise an experimental procedure iteratively and reflectively
- Evaluate the process and outcomes of an experiment quantitatively and qualitatively
- Extend the scope of an investigation whether or not results come out as expected
- Communicate the process and outcomes of an experiment
- Conduct an experiment collaboratively and ethically
Each experiment focuses on developing and applying tools of experimental physics to extend our understanding of physical behavior and how we model it through basic principles. Experiments will often critically assess the conceptual and experimental basis for physical models and their applicability or limitations in specific situations.
The purpose of this lab program is NOT to demonstrate or reinforce concepts typically found in a textbook, but rather to teach skills and tools used in experimental science to assess how well the physical world may be modeled by those or other concepts. Although lab activities may draw upon concepts and principles from other parts of the introductory physics courses, you should NOT expect a close connection to that material.
The goal is to understand how we know, not what we know.
What You Will Do In and Out of Lab
Lab work will take place during the lab period, along with short, individual homework activities. Instructions for each lab unit are available in D2L. In many cases these instructions may be rather general, affording you creative freedom to devise your own specific procedures.
You will be expected to attend your registered lab section as per the course schedule. You will be assigned to a group of three students for the semester. The lab instructor will be available during these sessions to answer questions, brainstorm ideas, and provide suggestions and feedback. You are always encouraged to consult with other groups in your lab section for ideas.
The typical schedule will be as follows:
Outside of lab: Complete and submit homework activity before the next lab meeting except when otherwise noted.
Before lab: Read over the lab instructions.
During lab: Follow the lab instructions and work with your group to:
- Familiarize yourself with the equipment and physical system.
- Work with your group to design and conduct an experiment to evaluate the given research question.
- Reflect on your process as you go and conduct additional investigations that build from and extend your methods and results.
- Document your activities and findings and answer the lab manual questions in your lab notes.
- Check-in regularly with your lab instructor.
- Submit your lab notes in D2L by the end of the session.
- Clean up your lab space and put all equipment away.
If you are unable to attend your lab section on a given day, please contact your lab instructor as soon as you are aware of the conflict or become ill. Your lab instructor will make arrangements for you to complete the lab individually with a negotiated deadline
Assignments
Homework: On each lab day, you will complete a short homework assignment designed to help you analyze data and reflect on the broader role of experimentation in physics and STEM. These assignments will be submitted through D2L.
Lab notes: Throughout the lab, your group will work together to answer the questions in the in-lab assignment and conduct your investigation. You will submit your group’s answers to the questions, notes about your methods, and data analysis through D2L.
How Groups Will Work Together in Lab
You will be expected to work together on the lab materials during your scheduled lab session. Only one person will need to submit your group’s responses by the end of the lab period, indicating each of the group members when prompted.
Keep track of note taking responsibilities: Each group member should select a text color for their contributions to the lab notes over the course of the semester. Specify which color is yours in the lab notes and try to maintain the same color over the course of the semester. You may often have one person type most of the lab notes for the week if they are the lab notes organizer – that is okay, just make sure that the lab notes organizer role rotates throughout the semester.
You will have flexibility to coordinate how your group works together. It is very important that every member of your group has the opportunity to try out the various activities involved in the lab (such as documenting your group’s process, collecting data, and analyzing the data). There are a few ways you can consider doing this:
Assign and rotate roles each session: In some cases, it may be easier for different team members to be responsible for different aspects of the lab. Regardless of the assigned role, each group member should participate in shared responsibilities such as contributing ideas, using experimental equipment, and making decisions.
Share or take turns with the equipment: Whenever possible, all group members should have the opportunity to handle the experimental set up and collect data. This could mean having multiple people managing the equipment together or taking turns. You may also consider setting up multiple versions of the experimental set up and collecting data simultaneously, such that part of the investigation is about comparing results between set ups.
Parallel Process: Whenever possible, make sure all group members have a task to do to help move the group’s progress forward. No one should ever be waiting on someone else to complete a task before they can work on their own task. For example, someone can always be updating lab notes and responses, setting up analysis code or spreadsheets, or setting up their own version of the experiment.
Examples of Roles in Group Work
Principal Investigator (PI): The PI makes sure that everyone has something to do and a way to contribute to the group’s progress. The PI works to establish an environment where all group members are comfortable and encouraged to share their ideas and contribute to the collaboration. If there are disagreements, the PI facilitates the discussion. The PI constantly pushes the team forward at a fast pace, encourages quality decision-making, and supports effective collaboration. This person is not the boss of the group and should not be taking over or assigning tasks. Instead, they should be overseeing the group progress to make sure everyone is being productive and that the group is functioning well.
Reviewer #2: Reviewer #2 constantly takes a step back to critically look at the research design or execution and suggest areas for improvement. Reviewer #2 is responsible for questioning all decisions to keep the group ethical and rigorous. Often this role slows down the progress of the group due to the skepticism required.
Science Communicator: The Science Communicator is responsible for keeping track of everything that the group does. The Science Communicator needs to keep an outside perspective in mind when contributing to decisions within the group. If results need to be presented, the Science Communicator is responsible for organizing this presentation. NOTE: they should not be the only one writing or presenting – they are just responsible for making sure what is written and presented is understandable to people within and outside the collaboration. Anyone within the group may be recording and should be presenting, regardless of their assigned role.
Data analyst: The Data Analyst is responsible for overseeing the decisions related to analyzing the data. The Data Analyst should make sure the group has considered how they will analyze their data before they collect it and that data is being plotted and analyzed as it is collected. NOTE: they should not be the only ones analyzing the data – they are just responsible for making sure the analysis is being proactively considered.
Theorist: The Theorist is responsible for considering the theoretical motivations for the experiment or interpretations of the data. They should actively consider how the theory relates to the experimental design, possible limitations of models being investigated, and multiple explanations for results.
What Goes in the Lab Notes?
The in-lab assignment will always ask you to document your group’s decisions, experiments, data, and analysis. You should be keeping track of these as you work in the lab, rather than summarizing them at the end. Learning how to keep and use a lab notebook is an explicit learning goal in the course . Why?
Modeling Professional Lab Notebook practices: Lab notebooks are regularly used in experimental work to document the details of an investigation. A scientist or engineer may refer back to the lab notes between days in the lab to pick up where they left off, when writing a more formal manuscript to recall why they conducted the experiment a particular way, or when working on a similar project to help troubleshoot a problem they may have already solved. For work that may result in a patent or contentious “who did it first” debate, each notebook entry is time stamped, and pages are never removed from the book. Lab notes should NEVER be deleted or erased – only added to and extended. If you realize later that something you wrote is incorrect, it helps to have a record of how you realized it was incorrect, so you (or someone looking at your notes later) can avoid or resolve the same issue.
Saving you time and effort: Summarizing your activities after the fact can be more work than jotting them down as you go. Practically speaking, think of your lab notes as a stream of consciousness. Lab notes are NOT a formal report. They do not need to be in full sentences. They can be bullet points. They should not take up a lot of time. They should be quick notes that document what you were doing and why you were doing it at several time points throughout the lab. Do not leave it to the end!
(Un)Grading
The grading system used in this course is probably vastly different from that of any other course you have taken. The grading system is actually not grading at all; it is even called ungrading or going gradeless by educators who implement it.
Research has informed us that descriptive feedback, rather than letter grades or scores, leads to higher learning gains and that using grades in an attempt to improve performance is not effective. There is evidence that grades encourage competition over cooperation, suppress creativity, foster a fear of failure, and reduce interest in learning. If you are curious, this review article discusses research related to grades: Teaching More by Grading Less (or Differently).
Much of this is confirmed by other researchers like Carol Dweck, whose book Mindset introduced the world to the concept of growth mindset, and Daniel Pink, whose book Drive argued that extrinsic rewards and punishments actually stifle creativity, higher-order thinking, and intrinsic motivation.
It is my hope to engender the dispositions of growth mindset and intrinsic motivation in my students,
so I want to eliminate any practices that work against students developing them.
In this lab, after you turn in work for an assignment, you will receive written and/or verbal feedback about what you did well and what you can do to improve. You will also reflect on your work and your learning goals each week. Throughout the lab course, you will have opportunities to assess your own work, to make improvements in response to feedback, and to elicit and receive new feedback — all of which has been shown to aid students in becoming more engaged and effective learners.
Learning Goals
You will collect evidence that demonstrates your learning and achieving of the course learning objectives. Each Learning Objective has specific learning goals that you can use to guide your collection of evidence.
Objective 1: Collect data & revise the experimental procedure
Decide which data to collect, including:
- which variables to change/vary and how to change them,
- which variables to control and how to control them, or
- which variables to measure.
Decide how to measure data, including:
- how much data to collect (including number of trials, range of each variable, frequency/spacing of data collection) to obtain desirable uncertainty in measured values or calculated parameters,
- what equipment to use, or
- determine ways to reduce sources of uncertainty, systematics, or mistakes.
Make predictions about expected measurements, data, and results by:
- choosing a model to test from theory or predictions,
- performing order of magnitude estimations,
- checking units and dimensions,
- consulting previous data and results, or
- collecting preliminary, pilot data.
Use the predictions about expected data, uncertainties, and systematics to:
- consider spacing and frequency of data,
- quantify systematics or design tests to quantify them, or
- identify where the main effect might be.
Objective 2: Evaluate the process and outcomes of an experiment
Analyze data using computational methods including (but not limited to) working with software such as spreadsheets, Matlab, or Python.
Decide how to analyze the quality of the measurements, which involves:
- identifying and distinguishing possible sources of uncertainty, either from the measurement model or physical model,
- distinguishing instrumental uncertainty from random uncertainty,
- determining how to quantify those sources of uncertainty (e.g. through standard deviation or standard uncertainty of the mean of repeated measurements or instrumental precision), or
- propagating measurements uncertainties through calculations that use the measurements.
Compare pairs of measurements by determining the degree to which uncertain measurements are statistically distinguishable.
Describe how the least-squares method provides a measure of the best-fit (conceptual understanding).
Compare data to a model quantitatively by:
- plotting data and model on traditional x-y plots including appropriate representations of uncertainty,
- linearizing data via semi-log or log-log plots,
- performing linear and non-linear weighted least-squares fits,
- plotting residuals, and/or
- interpreting the outcomes of the analyses.
Reflect (and respond appropriately) throughout the data collection process by:
- plotting as data are collected, and
- evaluating the methods and data (e.g. checking uncertainty, systematics, or mistakes, monitoring constraints and feasibility, interpreting and making sense of results).
Objective 3: Extend the scope of an investigation
Draw inferences from analyses conducted (e.g. the degree to which data agree or disagree with a model or to other data).
When data and results do not come out as expected:
- Determine plausible explanations for the disagreement (e.g. assumptions or approximations in the models, measurement mistakes, or issues with equipment),
- Test whether the results are repeatable or reproducible under the same conditions,
- Check whether the results are repeatable or reproducible with improved precision or measurement quality,
- Isolate and test components of the system (troubleshoot), and
- Design new experiments/tests to explore other explanations for the disagreement.
When data and results do come out as expected:
- Test whether the results hold with higher levels of accuracy and precision (improve the quality of measurements), or
- Extend the scope of the experiment to check if there is “new” physics at these levels.
Objective 4: Communicate the process & outcomes of an experiment
Describe the experimental goals, process, data, results, and conclusions in a lab notebook including:
- Justification for all decisions made, and
- Supplementing, rather than replacing content when changes are made.
Use previous notes in their lab notebooks to inform design of future experiments.
Explain the experiment, broader context, and uniqueness of the investigation in a more formal format such as a final report, oral presentation, or poster.
Present conclusions, claims, and outcomes as arguments that are supported by and follow coherently from evidence (data).
Objective 5: Conduct an experiment collaboratively and ethically
Brainstorm with their group to construct a diverse set of ideas when making decisions.
Share experimentation responsibility with other group members (i.e. rotate roles, allow others to lead).
Provide positive and constructive feedback when evaluating peers’ work.
Consider issues of scientific ethics when analyzing data including:
- Dealing with data and results that do match predictions or expectations.
- Dealing with outliers,
- Dealing with data and results that do not match predictions or expectations, and
- Dealing with data and results that do match predictions or expectations.
Final Course Grade
Your final grade in this lab course will be determined based on the skills you learn, the learning goals you achieve, and the competencies that you demonstrate. Throughout the course, you will develop a body of work that will help you to self-assess your learning and make an honest appraisal of your effort and progress in the course.
You will be afforded the agency to evaluate and examine your own learning and suggest your grade in the course.
At the end of the lab course you will propose your final grade in a paper or presentation that provides evidence from your body of work throughout the course for why you believe your suggested grade is fair.
Final Presentation Options
(Choose one)
We can meet via Zoom for a final exit interview during which you will present an organized presentation with evidence to support your proposed final grade. I will provide feedback on your assessment and discuss your grade suggestion with you. Together, we will work toward an agreed upon grade, though I reserve the right to veto a suggested grade. This presentation must be no longer than 20 minutes.
You can prepare and record a 20-minute video presentation with evidence to support your proposed final grade and submit this video presentation to D2L. I reserve the right to veto a suggested grade.
You can propose your final grade in a paper that provides evidence from your body of work throughout the semester for why you believe your suggested grade is fair. This paper has a page limit of 3 pages, single spaced, 12 point font, 1 inch margins. This paper will be submitted to D2L. I reserve the right to veto a suggested grade.
Attendance Policy
Since you will work in groups each week, every group member must be present for each lab meeting. You should consider missing a day of lab equivalent in severity to missing an exam! If you miss a lab due to an excused absence, you must complete the lab experiment during an agreed-upon make-up date and time.
To qualify for this make-up day, proper documentation must be provided for the absence to be considered “excused” by University policy (See Student Handbook §3.7.1). Make sure to notify your instructor of any anticipated absences well in advance.
Missing a total of three labs, regardless of the nature of the absences, will result in a failing grade for this lab course.
Academic Honesty
You are expected to uphold the highest standards of academic honesty and integrity in this course. All work you submit should reflect your own understanding, effort, and voice. Cheating, plagiarism, and any form of misrepresentation—whether through copying others’ work, using unauthorized sources, or misusing AI—undermine both your learning and the integrity of our academic community.
I support the ethical and thoughtful use of Artificial Intelligence (AI) tools as part of the learning process. When used appropriately, AI can help you brainstorm, clarify concepts, revise writing, or explore new ideas. However, like any tool, its value depends on how it’s used.
If you choose to use AI tools, you are responsible for:
- Ensuring your work reflects your own ideas and comprehension,
- Acknowledging any AI assistance (e.g., “I used ChatGPT to help outline my response”),
- Avoiding any use of AI that misrepresents your learning or bypasses the intent of the assignment.
Using AI to replace your own thinking or effort – especially on graded work – will be treated as a violation of academic integrity.
If you’re unsure whether a certain use of AI is appropriate, please ask. Ethical use of AI is not just about avoiding dishonesty – it’s about engaging responsibly with powerful tools in ways that support your growth and uphold the values of this academic community.
Note: I used ChatGPT to help draft and revise this policy statement. This is one example of how AI can be used transparently and responsibly in support of meaningful work
Physics Education Research at UNG 