Using lab notebooks to examine students’ engagement in modeling in an upper-division electronics lab course

We demonstrate how students’ use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students’ written work and to identify how students’ model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students’ model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.

Figure 1

Diagram of the Modeling Framework for Experimental Physics.

Figure 2

Voltage divider circuit for Activity 1 (a version of this, without the measurement device shown, was included in the students’ prelab). Resistors $R_1$ and $R_2$ were both either 1 or $10\mathrm{M}\mathrm{\Omega }$, depending on the version of the circuit being tested. The measurement device is depicted with the input resistance labeled $R_{\mathrm{in}}$. Everything in the box is internal to the measurement device.

Figure 3

Photometer circuit for Activity 2. The photodiode students used to detect the room light is visible at the bottom left and is in a reverse-biased configuration. The op-amp portion of the circuit is set up as a transimpedance amplifier.

Figure 4

Voltage-controlled electromagnet circuit used for Activity 3. The component labeled “A” is the ammeter used to measure the current through the coil and the component labeled “V” is the voltmeter used to measure the gate to source voltage.

Figure 5

Coding results for the four parts of Activity 1. The top (bottom) two diagrams show the coding results for the $1\mathrm{M}\mathrm{\Omega }$ ($10\mathrm{M}\mathrm{\Omega }$) circuit measured with the DMM. The results for the oscilloscope measurements of the same circuits demonstrated essentially the same degree of completion. In total, 37% of the students documented the modeling process for the entire activity (all four parts). Rows represent different steps in the modeling process and columns represent individual students (the corresponding column of each of the four diagrams represents the same student). Each gray box represents a documented instance of the corresponding modeling step for the corresponding student. The diagonal hash marks indicate that the two different initial predictions represented two separate modeling pathways and thus no student would do both. Rightmost column represents percentage of students who documented that step of the modeling process. The percentages for the initial predictions are based on the total number of students who chose one of the two modeling pathways.

Figure 6

Two examples of documented comparisons for Activity 1. The top example demonstrates the type of quantitative reasoning students used, while the bottom demonstrates the type qualitative reasoning. Note that a proposal to refine the system is also stated in both examples.

Figure 7

Coding results for Activity 2. In total, 53% of the students completed the modeling process for the activity. Rows represent different steps in the modeling process and columns represent individual students. Each gray box represents a documented instance of the corresponding modeling step for the corresponding student.

Figure 8

Two examples of documented comparisons for Activity 2. The top example demonstrates a quantitative comparison using percentage difference. The bottom example makes a subjective qualitative statement (“a little less than predicted”) as a comparison.

Figure 9

Coding results for Activity 3. In total, 68% of the students completed the modeling process for the activity. Rows represent different steps in the modeling process and columns represent individual students. Each gray box represents a documented instance of the corresponding modeling step for the corresponding student. The $X$’s indicate comparisons that were evaluated to be in poor agreement. Percentages (*) for proposals and revisions were based on the total number of students whose comparisons indicated poor agreement.

Figure 10

Three examples of documented comparisons for Activity 3. The top example demonstrates the type of comparison plots students made for a model that directly measured the $B$ field. The middle example demonstrates a proportionality comparison to their model, $B\propto N$ and $B\propto I$. The bottom example demonstrates a trend comparison where the model addresses only the increase or decrease of the $B$ field.