A new direction for the Physics 132 labs

During the Spring 2019 semester, in addition to several changes in the lecture portion of the course, Paul Bourgeois, David Nguyen, and I continued to make changes to the laboratory portion of Physics 132. Motivated by this article from Physics Today, we decided to make our labs much more focused on teaching fundamental data analysis skills as opposed to physics concepts. We also added structural changes to the lab portion to promote in the students a sense of importance and ownership of what we were trying to teach. In general, I think that these changes were, by the end of the semester, positively received and provide a strong way forward for future lab developments in Physics 131 and other courses within our department.

Moving from teaching physics to teaching data analysis skills

The traditional role of the physics 132 lab has been similar to the traditional role of labs throughout the country: providing a way to see physics concepts in action through hands-on activities through a rather prescriptive series of instructions. The philosophy being that such activities help students “believe” what is being taught in lecture and deepen their understanding. The Physics Today article, however, clearly indicates that such activities do not actually improve understanding. A better approach is to teach students to “think like a physicist.”

Another alternative, which we developed with Bonn, is more suitable for large, stand-alone introductory lab courses. The approach involves abandoning the goal of teaching content and instead aiming to teach important aspects of physics thinking for which labs are uniquely effective. Those aspects relate to the process of scientific experimentation, such as formulating hypotheses and testing them by collecting data, figuring out how to improve the quality of data, using data to evaluate the validity of models, and deciding on suitable criteria for such evaluation

N. Holmes, C. Weinman. “Introductory physics labs: We can do better.” Physics Today 71, 1, 38 (2018); https://doi.org/10.1063/PT.3.3816

In Physics 132, we need to take Holmes and Weinman’s suggestion a bit further. We are not trying to create physicists, we have life-science students.

What skills, well suited to the laboratory environment, can we impart to these students that will be useful in their life-science centered careers?

Our answer: understanding data skills

We believe that all students in the sciences need to be able to:

  • Understand that all measurements have uncertainty
  • Quantify uncertainty
  • Understand that uncertainties are both systematic and statistical
  • Compare two independent measurements
  • Interpret a p-value
  • Apply the concepts they often learn in statistics to real data
  • Understand a graph plotted in functions of variables (linearization)
  • String together several different analysis steps together into an analysis chain
  • Have a basic familiarity with using computers to do analysis (in our case, spreadsheets)

Each of our labs now focuses on one or more of these topics adding one more step in the chain until, at the end, students are required as part of a laboratory exam, to string them all together with a new data set.

Benefits of this structure

  1. Data messiness becomes an asset: In a traditional lab focused on reinforcing content, the messiness of student-collected data can be a detriment. Subtle effects you hope students will see can be hidden in the experimental noise. If, however, the lab is focused on data analysis skills, the noise becomes an asset. Students are now focused on the noise and understanding it.
  2. Reduced importance of mastering PASCO or similar data acquisition tools: Our students will never use PASCO again. They may never use an Ohm-meter again. While understanding the fundamentals of the tools is critical to understanding sources of noise and uncertainty, being able to debug the tools of a physics lab is not of critical importance for these students. Thus, the TA can help debug without compromising course goals.
  3. Simple measurements are better: Simpler measurements are less likely to get into problems debugging equipment (see point above). In this lab format, simple data has another asset: understanding sources of uncertainty is more manageable in the time available.
  4. Synchronization between lab and lecture is no longer a goal: If lab is meant to support lecture, a reasonable goal is to have the material presented in both formats simultaneously. However, at UMass, such simultaneity is impossible due to space constraints; we need two weeks to get all 500 132 students through the lab. As a result when trying to synchronize, the inevitable result is that some students are seeing the material in lab before it is presented in lecture while others see it afterwards. This disparity is always a source of frustration for the students. The students for whom the material is seen first in lab feel that the sections later in the cycle have an advantage. If, on the other hand, the point of the lab is data analysis, having the lab after all students have seen the material in class is a benefit: allowing students to not focus on the physics but instead on the data.
  5. Having one week in the lab and one week in a classroom works great: As part of our space constraints, students spend one week in the lab room with equipment and the second in a classroom. These classroom-based sessions used to be (poorly attended) discussions. In a data-analysis centered lab, the first week can be based on collecting data while the second can be on the analysis.
  6. Students can be asked to apply these same skills in a biological context: Since data analysis skills are universal across the sciences, we can find examples from the life-science literature which use these same skills and ask students to use them.

Other structural changes to promote both accountability and the importance of the labs in students’ minds.

A lab final exam

A common observation in Physics 131 is that when using spreadsheets is required, one student, who typically already knows how, does all of the manipulation while others who do not know watch, learning nothing. A related behavior is reflected in the common lab complaint, “I did all of the work, and I don’t feel that it is fair.” Our solution to this problem is a laboratory final exam.

From the “Three Laws of Teaching” described by Ken Heller at University of Minnesota, “Students will learn what you test.” Testing is one of the primary ways we show students what we really think is important. A laboratory final exam, worth a significant portion of the course grade shows our students that these data analysis skills are just as important as the physics content in lecture. Simultaneously, since the lab exam is done individually, each student has an external motivator to learn how to complete the analyses.

A four-part structure embracing a flipped pedagogy and helping to promote transfer

The laboratory exam encourages students to prioritize mastering the laboratory curriculum for the semester as a whole. We also want students to be accountable for each of the other five labs. To accomplish this goal each lab has four parts: pre-lab homework, data collection day, analysis day (done outside the lab in a typical classroom), and transfer homework.

Following a flipped pedagogy similar to the lecture, students are expected to complete some simple reading on the analysis techniques before coming to lab and complete some basic homework problems. At the end of the lab, students are exposed to a similar situation from the life-science literature and asked to apply their knowledge to that context to help promote transfer.

Student reception and further improvements

Midway through the semester, students completed a course evaluation. There was a significant amount of complaint about the lab. Some were the typical complaints that arise when you are developing course materials: grammatical errors, unclear instructions, etc. However, there was also a significant number of negative comments about how the lab did not support what was being covered and tested in lecture. Now, there was not a specific question regarding the lab on the midterm assessment, these were freely given comments to open-ended questions.

By the end of the semester, however, the attitude seems to have shifted. Again in response to open ended questions not directly about the lab, students were commenting about how some of the skills learned in lab were some of the most useful things that they had learned in the course. The assumption is then that, as the semester went on, the fact that the lab was developing a separate skill set from lecture was beginning to catch on and be appreciated. Clearly a questionnaire with more dedicated questions would be useful to truly understand student perception. Also, a more dedicated “marketing” strategy may be helpful in getting students to that point earlier.