Teaching a large lecture course in a STEM course can feel like steering a cargo ship; you’re moving a lot of people in the same direction, but small adjustments can be hard to see and manage in real time. Traditional assessments (midterms, finals, projects) may measure end-point achievement, but they don’t always help faculty understand how students are learning along the way. This is where classroom assessment techniques (CATs) https://vcsacl.ucsd.edu/_files/assessment/resources/50_cats.pdf come in: quick, research-backed methods that provide timely insights into student understanding, enabling instructors to adapt instruction while the course is still in motion.
Why CATs Matter in STEM Large-Enrollment Courses
Evidence from STEM education research underscores that formative assessment and feedback loops significantly improve student learning outcomes, especially in large courses where anonymity and disengagement can take hold. Studies show that structured opportunities for feedback (e.g., one-minute papers, peer assessments, low-stakes quizzes) can reduce achievement gaps and support retention in challenging majors.
At the same time, as Northwestern’s Principles of Inclusive Teaching https://searle.northwestern.edu/resources/principles-of-inclusive-teaching/note, students often struggle not only with course content but also with the “hidden curriculum” or unspoken rules about what “counts” as good work or participation https://cra.org/crn/2024/02/expanding-career-pipelines-by-unhiding-the-hidden-curriculum-of-university-computing-majors/ . Transparent communication about assessment criteria and expectations helps level the playing field.
High-Impact CATs for CS, Engineering, and Informatics
Algorithm Walkthroughs (Think-Alouds)
Students articulate their reasoning step-by-step. Helps faculty identify gaps in procedural knowledge.Debugging Minute Paper
Prompt: “What was the most confusing bug/issue we discussed today, and why?” Surfaces common misconceptions in programming logic.Concept Maps for Systems Thinking
Students draw connections between components (e.g., CPU, memory, OS). Research shows concept mapping fosters transfer across domains.Peer Review of HCI Prototypes
Students exchange usability sketches with rubrics. Builds critique skills and awareness of user-centered design.Low-Stakes Quizzing with Digital Dashboards
LMS quizzes or polling tools provide immediate data on misconceptions while also scaffolding students’ goal monitoring.
Making CATs Inclusive in Large Lecture Halls
To avoid reinforcing inequities, instructors should:
Clarify criteria with rubrics for coding projects, design critiques, or participation.
Co-create ground rules for collaboration in labs and online forums, ensuring respectful and equitable engagement.
Balance rigor and empathy: challenge students while providing structures that acknowledge different starting points and prior knowledge.
Putting It into Practice
In a 250-student programming class, use a digital Muddiest Point poll after each lecture, then address top confusions in the next class.
In an HCI course, scaffold peer review CATs for wireframes inside the LMS, combining digital rubrics with analog small-group feedback.
In a systems engineering class, embed progress dashboards with reflective CAT prompts (“Where are you stuck? What resource might help?”). This makes metacognition visible and actionable.
Final Thought
Large-enrollment CS, engineering, informatics, and HCI courses don’t have to feel impersonal or assessment-heavy. By integrating classroom assessment techniques faculty can design courses that are responsive, transparent, and inclusive. The result: students who not only master disciplinary knowledge but also learn how to manage their own learning, a skill set essential for both the classroom and the future of work.
Further Reading:
Angelo & Cross’s Classroom Assessment Techniques https://iucat.iu.edu/catalog/20750208
50+ adaptable CATs. For large STEM courses, techniques like the “Muddiest Point” or “Background Knowledge Probe” are especially powerful.Nilson’s Teaching at Its Best https://iucat.iu.edu/catalog/16660002
Offers frameworks for aligning CATs with learning objectives—critical in CS/engineering courses where problem-solving, debugging, and design thinking are central.Northwestern University, Principles of Inclusive Teaching https://searle.northwestern.edu/resources/principles-of-inclusive-teaching/; and Making Large Classrooms feel Smaller: https://searle.northwestern.edu/resources/our-tools-guides/learning-teaching-guides/making-large-classes-feel-smaller.html