As educators, we assume that students are learning what we teach. But students often do not learn as much as we expect, and high-stakes assessments reveal their knowledge gaps when it is too late to do anything about it. Thus, many instructors use classroom assessment techniques (CATs) to provide instant feedback while students are accessing learning content. These assessments also allow students to gauge their comprehension of content so they can seek help before the summative assessment (Cross & Angelo, 1993). This information can be used to adjust course content or teaching methods to assist students in making their learning more efficient and effective, such as speeding up or slowing down the pace of a lecture or explicitly addressing areas of confusion. Proper use of CATs provides concrete evidence that the instructor cares about learning, and it is particularly helpful for checking how students are learning early in the course and providing information for improvement when learning is unsatisfactory.
I have developed a traffic light card to assess learning in my classes (He, 2019). About two minutes before the end of lecture, I distribute a card that lists the most important topics covered in that day’s lecture. Students “traffic light” these topics by checking whether their understanding is high (green), partial (yellow), or low (red). I also encourage students to write down their specific confusions or concerns on the yellow and red light topics.
I use the results to review the yellow and red topics at the start of the next lecture, which helps students gain better understanding of the content. Students report thinking favorably of the traffic light card, and it has also been proven to help establish rapport with students as this technique demonstrates my commitment to their learning.
While I designed the traffic light card for face-to-face learning, it can be adopted to online courses as well:
- In asynchronous online courses, you can collect traffic light responses on a weekly basis via online survey tools, such as SurveyMonkey. After analyzing students’ responses, you can record videos or post other types of additional material to address those yellow and red topics.
- In synchronous online courses that use videoconferencing tools such as WebEx or Zoom to deliver remote lectures, you can use the tool’s polling function to collect responses. You can then cover the yellow and red topics at the beginning of the next online lecture.
The traffic light response overcomes the drawbacks of two commonly used CATs: muddiest point and minute paper. Muddiest point is a technique in which students identify one point that they least understood from class; however, focusing on the muddiest point too often can be discouraging for both students and instructors. In the minute paper, the instructor asks students to write down responses to an aspect of the class session, but student comments may often be off-topic.
If you have interest in using the traffic light response in your classes, you can expand this technique to ask students to list lecture topics that inspire them and that they want to learn more about or ideas they get from the lecture (see Cross & Angelo, 1993). In this way, you can learn what intrigues students and use this interest to improve the course.
Most courses are set up to assess learning at the end of a module, with a new module starting immediately afterward, making it impossible to address gaps in understanding during the course. The traffic light response is a great way you can improve learning by identifying gaps in understanding early enough to address them. It helps to foster bonding between the instructor and students. Students feel more positivity and inclusivity and gain confidence in themselves as learners, which increases the efficacy of teaching and learning.
References
Cross, P. K., & Angelo, T. A. (1993). Classroom assessment techniques: A handbook for college teachers. Jossey-Bass.
He, Y. (2019). Traffic light cards: A cross and modification between the minute paper and muddiest point. College Teaching, 67(1), 70–72. https://doi.org/10.1080/87567555.2018.1522612
Yunteng He, PhD, is a chemistry instructor at Central Community College in Kearney, Nebraska.
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