Evidence-Based Classroom Assessment Techniques (CATS) for STEM Courses

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:

1. 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.

2. 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.

3. 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

Pre-Course Survey

One way to improve engagement with your students is to learn more about them. A precourse survey is one way to help develop a connection with your students, and get to know them beyond what is shared in an introduction discussion.

What do you want to know about them?

Diligent student in college with classmates, taking notes of teacher lecture.

A survey can help you conduct a needs assessment about where your students are at in terms of prior knowledge, demographics, mindset, learning preferences, goals, content confidence level, preferred feedback style, and/or access to technology.  Because this takes place “behind the scenes” and is only shared with the instructor, rather than in a public discussion forum, you may be more likely to receive candid responses.

What strategies and skills will students need and/or develop in your course?

These kinds of questions can help students flex metacognitive skills and become more aware of their learning habits. As an instructor, this can help you provide more specific feedback on student work, suggesting similar strategies and stretch goals.

• Reflection on Strategies: Metacognitive reflection questions ask how students get things done. Do you take marginal notes or highlight as you read? What conditions do you need to do your best work?

• Planning Ahead: Beyond what has worked for students in the past, you might ask about strategies they will use specifically in this class. What times each week do you have earmarked to work on this course?

• Setting Goals:You might ask them to review the learning objectives, asking what they will commit to accomplishing. And beyond the learning objectives for the course, are there other skills or competencies they plan to work on in the course? Do they have any suggestions for the instructor about strategies for helping meet those goals?

During the first week of your course

Providing students with an opportunity to quiz themselves not on the course topic but on the course itself–how to get started in the course, how to navigate the course, what the course should help students accomplish, and how the course is structured–can help instructors send fewer emails saying, “It’s in the syllabus!”

Given multiple choice or true/false question types, these kinds of pre-course surveys can be automatically scored. Don’t forget to compose feedback for incorrect responses and allow multiple attempts!

What tools are available?

IU supports the Qualtrics survey tool and Canvas includes a dashboard feature that allows instructors to create a type of quiz called ‘ungraded’ that can be used as a survey. In Canvas, once the survey, or ‘ungraded quiz,’ is published online, students can login to their Canvas course page and participate. IU also has access to Google Forms and Microsoft Teams (Microsoft Forms are Available in the Channel and Chat features) for quick survey and quiz creation.

If you’d like support implementing a pre-course survey or questionnaire in your online class, or in any other aspects of teaching and learning, please contact me at your earliest convenience with your availability.