Taking the Temperature: Gauging Student Affect in Labs

What was the teaching problem/issue/challenge you faced?

My main goal for the labs in this large module was to provide a meaningful learning experience for a cohort of non-physics students. I wanted to move away from the traditional, recipe-like experiments and include skills like communicating science and designing experiments.

The challenge was to get real-time, qualitative feedback on how students were experiencing the labs. I needed a way to gauge whether they felt they were learning and if they found the labs enjoyable, but without creating an administrative burden for a class of over 350 students. I also wanted to ensure that the students understood what was being asked of them, as I had observed that a lack of clarity was a major source of frustration.

What specifically did you decide to do?

I used the Loop quiz tool to create a unique, two-part, low-stakes weekly assessment that I call a "temperature check." The quiz was designed with two main purposes: to gather feedback on the previous lab and to prepare students for the next one.

• Affective Feedback: After each lab, I asked students to complete a short, three-question quiz with a Likert scale. The questions were:
  1. Do you feel you learned something?
  2. Was it enjoyable?
  3. Was it difficult?
• Formative Pre-Tests: The second part of the quiz included a small number of questions to prepare students for the upcoming lab. These were designed to get their minds "prepared for what is coming up" and were graded solely on completion, not correctness.
• Open-Ended Feedback: I also included an optional open-ended question that asked, "tell me anything you want to share with me about your previous lab."

“The quiz's main function was to inform my teaching and course design. To ensure students gave honest feedback, the quiz was graded on completion only and not on the specific answers provided.”

How did it work in practice?

The quiz provided me with invaluable data that directly informed my teaching and lab design.

• Actionable Insights: While I didn't necessarily trust the absolute numerical values from the Likert scales, the relative trends were highly informative. For instance, if the number of negative responses for a particular lab exceeded my arbitrary threshold of 15%, I knew I needed to take action. This often meant checking in with students to understand the issues. I found that students weren't upset about a difficult lab, but they were very frustrated if they didn't understand the task itself. This insight led me to focus on improving the clarity of my instructions.
• Informing Course Design: The pre-test questions helped me gauge the students' existing knowledge. If a large number of students already knew a concept, I could adjust my teaching to spend less time on it during the lab session.
• Generalisability: This approach is probably not specific to physics. The method of using a quick, low-stakes quiz to gather qualitative feedback is a simple yet powerful tool that should be applicable across many disciplines to gauge student affect and inform course design.
• External Integration: I also make use of other online resources for grading. I use Learning Tools Interoperability (LTI) to link Pearson and McGraw-Hill quizzes directly to the Loop gradebook, which helps manage the grading load for such a large class.

What are key reflections on this approach/process?

• Align Goals with Assessment: It's crucial to ensure that the assessment format matches your teaching goals. My goal was honest feedback, so grading the quizzes on completion rather than correctness was essential. This prevented students from simply telling me what they thought I wanted to hear.
• Trust the Trends, Not Just the Numbers: In a large class, the real value of a tool like this is not in the individual data points but in the overall trends. Seeing a spike in negative feedback for a specific lab is a clear signal that something needs to be addressed.
• The Power of Clarity: Students are often willing to grapple with difficult concepts, but they get frustrated when the instructions are unclear. Using the feedback from these quizzes to improve the clarity of lab instructions had a direct positive impact on student experience.

Further Reading on Formative Assessment in Large Classes

Tanner, K. (2010). "Promoting student metacognition." CBE—Life Sciences Education, 9(2), 113–120.

Tanner describes using techniques like "exit tickets" to make large classes feel smaller. She suggests that even reading a small sample of student responses can provide valuable insights, a method that aligns with Paul's approach of using quantitative data to prompt conversations with students. While not solely about quizzes, it underpins the value of using a systematic method to get real-time feedback from a large cohort.

Cohen, A., & Sasson, I. (2016). "Online Quizzes in a Virtual Learning Environment as a Tool for Formative Assessment." Journal of Technology and Science Education, 6(3), 133-144.

This study examines the use of Moodle (i.e. Loop) quizzes for formative assessment in a large physics course. It investigates student attitudes and learning outcomes, providing empirical evidence for the effectiveness of a strategy very similar to the one described in Paul’s case.