Fostering Student Success in Thermo and Fluids: A 2025 zyBooks Guide

By Dr. Adrian Rodriguez, Dr. Lauren Fogg, and Linda Ratts

Introduction

When 50 engineering instructors gathered for our September 24, 2025 zyBooks workshop, we focused on a problem that costs us weeks of class time every semester: students who can solve thermodynamics and fluid mechanics problems perfectly but can’t explain what their answers mean.

The workshop brought together perspectives from Dr. Adrian Rodriguez (Senior Engineering Content Developer at zyBooks and thermodynamics Lecturer at UT Austin), Dr. Lauren Fogg (Engineering Content Developer at zyBooks and former fluid mechanics instructor at Louisiana Tech), special guest Dr. John Hochstein (University of Memphis and co-author of the zyBooks version of Munson, Young, and Okiishi’s Fundamentals of Fluid Mechanics), with Linda Ratts (Executive Editor at Wiley) moderating.

Our discussion revealed two evidence-based strategies that have produced measurable improvements in student performance:

• Strategy 1: Systematic identification and targeting of persistent misconceptions using analytics and concept inventories

• Strategy 2: Implementation of peer-led study groups with same-level student groupings

The Arizona State University study we highlighted showed that students using peer-led study groups earned nearly one full letter grade higher than those who did not participate (Brunhaver et al., 2024). This finding alone justifies reconsidering how we structure student learning.

Fostering Student Success in Fluid Mechanics and Thermodynamics Workshop, September 24, 2025

Strategy 1: Identifying and Addressing  Common Misconceptions

Based on a comprehensive literature review of common misconceptions published at the 2025 American Society for Engineering Education annual conference, the top misconceptions are:

Common Thermodynamics Misconceptions

  • Heat vs. energy vs. temperature – Despite extensive coverage, students continue using these terms interchangeably and mistake the relationship between each pair.
  • Entropy – The application of the 2nd law of Thermodynamics is difficult for learners to grasp easily. 
  • Steady-state vs. equilibrium processes – With roots in prior courses, the two concepts are typically assumed to be the same, which cascades into complex problem-solving.

Common Fluid Mechanics Misconceptions

  • Bernoulli’s principle – Students can recite the equation but struggle with application.
  • Gravitational effects in fluid systems – Students get confused about when gravity matters and when it can be neglected.
  • Fundamental fluid statics principles – Failure to understand basic concepts like pressure, Pascal’s Law, and Archimedes’ principles that cascade into further conceptual gaps for more advanced topics.

Example classroom data from a 60 student sample confirmed these common issues, as students spent the most time on the activities in the sections that covered these concepts. 

How To Address Common Misconceptions

Instructors can catch student misconceptions by employing regular quizzes and assignments in two ways: 

1. Employing questions from validated concept inventories, such as the Thermal and Transport Concept Inventory (TTCI)

and/or

2. Developing their own conceptual questions based on patterns from student performance, or using conceptual questions from another source, such as a zyBook.

A critical insight from our discussion: students often perform well computationally without conceptual understanding. Given a formula and calculator, they can produce correct answers while lacking fundamental comprehension of what they’re calculating. This disconnect between mechanical problem-solving and conceptual understanding drives the need for targeted interventions.

Good questions focus on not only the computational components of a problem, but the reasoning behind the assumptions used, selection of equations, changing parameters, and the results. Such questions can be asked via multiple choice or open-ended responses to allow an instructor to easily assess students before and after an instructional intervention is used. 

Strategy 2: Implementing Peer-Led Study Groups

The ASU implementation of peer-led study groups (PLSGs) produced remarkable results. Students in PLSGs earned nearly one full letter grade higher than those who did not participate, with statistically significant improvements in both final exam scores and overall course grades (Brunhaver et al., 2024).

Importantly, students in peer-led groups performed similarly to those who had additional TA-led recitation sessions. This demonstrates that peer collaboration is just as effective as traditional teaching methods—without requiring additional instructional resources.

Successful Peer Group Compositions

Our collective experience across multiple institutions reveals a consistent pattern: mixing high and low achievers often backfires. When top students are paired with struggling peers,the top students typically take over the problem-solving process. Students who need the most practice don’t get hands-on experience, while advanced students become frustrated with the pace and want to move through topics too quickly.

A more effective method is to group students of similar achievement levels together. When students work with peers at their level, every student must take ownership of the problem-solving process. This approach works better because students can communicate effectively within their peer group.

Implementing Peer Groups

The PLSG model follows these essential steps:

Step 1: Problem Selection and Setup

Select moderate to complex problems that require genuine collaboration—easy problems won’t generate productive discussion. Provide students with key equations, assumptions, and solution strategies upfront. This scaffolding allows them to focus on conceptual understanding rather than getting stuck on setup.

Step 2: Strategic Group Formation

Organize students into groups of similar achievement level, ideally 3-4 students per group. Use engagement data, performance metrics, or time spent in course materials to identify appropriate groupings. The goal is to create groups where all members can contribute meaningfully.

Step 3: Collaborative Workspace

Provide each group with a common workspace to work out the problem together. Whiteboards work particularly well, and each student can be given a marker to ensure everyone has the opportunity to contribute. The physical act of writing and explaining reinforces learning for all group members.

Step 4: Facilitation Without Intervention

Step back and observe. Resist the urge to correct mistakes immediately. Only intervene when absolutely necessary, and then use guiding questions rather than direct answers. Let students discover and correct their own errors through peer discussion.

Using Analytics to Form Groups

We demonstrated how to use learning analytics effectively for group formation. For example, if students A, B, and C are spending 270-290 minutes on course materials, they likely work at similar paces and should be grouped together. Similarly, students spending 200-220 minutes form another natural grouping.

This data-driven approach takes the guesswork out of group formation. Export data from your LMS, map it in Excel, and identify clusters of students with similar engagement or performance levels.

Problem Selection Using Performance Data

Performance analytics can also guide problem selection. Section 2.2 on energy concepts, for instance, showed high struggle rates in our data. These sections make excellent candidates for group work problems.

To maximize conceptual learning, modify standard problems by adding parts that require explanation. After solving for a turbine’s exit temperature, add: Part B asking what would change if the process weren’t adiabatic, and Part C requiring a T-s diagram sketch with explanation of the area’s significance. These additions shift focus from computation to comprehension.

Conclusion

Our workshop confirmed that engineering instructors nationwide face similar challenges with student conceptual understanding. These evidence-based approaches—systematically identifying misconceptions through data and implementing same-level peer groups—are producing measurable improvements across different institutions and contexts.

The key is flexibility. These strategies work broadly, and instructors should adapt them based on what they observe in their classrooms. Emphasize elements that address your specific student needs.

Whether using zyBooks, traditional textbooks, or a combination, these principles apply. Start where you are and build incrementally toward fuller implementation.

The Evidence from ASU’s Study

Documented Results:

  • Letter grade improvement: +0.9 points
  • Statistically significant improvements in final exam and course grades
  • Performance equivalent to TA-led recitation (i.e., more instruction time)
  • Time investment: 1 hour per week
  • Additional cost: $0

Resources

Research References

zyBooks Resources

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About the Authors: Adrian Rodriguez, PhD, is a Senior Engineering Content Developer for zyBooks and Lecturer at The University of Texas at Austin. Lauren Fogg, PhD, is an Engineering Content Developer for zyBooks and former fluid mechanics instructor at Louisiana Tech University. John Hochstein, PhD, is a professor at the University of Memphis and co-author of the zyBooks version of Gerhart’s Fundamentals of Fluid Mechanics. Linda Ratts is Executive Editor at Wiley.