What do we know about student attention in the classroom?

Learning success depends on students being focused during lessons but what is 'the thing' that attracts and maintains student attention ⎮3 min read
Published in Neuroscience
What do we know about student attention in the classroom?

Share this post

Choose a social network to share with, or copy the shortened URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

You are sitting in class and all of a sudden your teacher has called your name. They have asked a question, but you quickly realize that you have no idea what they have been talking about for the past few minutes, much less how to answer. Most of us have had this experience as a student, or we have been on the opposite side of this exchange as an educator . . . regardless of how exciting our lecture was.  

Student attention is important for learning in the classroom, but we know surprisingly little about it. In higher education, the idea that student attention lasts for 10-15 minutes has been widely used to inform the development of college lectures and classroom activities. However, this advice is based on “common knowledge” rather than empirical evidence. This is because attention is hard to measure reliably through self-report or by observing student behavior.  

So, are there things that educators can do to promote student attention? This is the question we are addressing in our newest line of research. Thanks to recent advances in mobile technology, educational neuroscience researchers have begun to use electroencephalography (EEG) in real-world settings to examine student cognitive states while they are engaged in learning activities. This allows us to explore brain function associated with processes like attention that can’t be observed from behavior alone.  

In this study, we used EEG to see if student attention varies based on the type of instruction. And it seems to! Specifically, we measured EEG from college students while they were engaged in an experimental lesson with other students. These lessons were designed to be similar to those that they would experience in regular courses – including lecture, educational videos, group work, and independent work. Neural oscillatory data revealed that attention was greatest in college students during group and independent work, followed by lecture – and lowest during video watching. This stands in contrast to student preference for videos . . . suggesting that while students might like to watch videos during class, this could be because they provide a good opportunity to zone out. 

We also had trained observers rate student attentive behaviors from video. These data told us a different story about student attention - the same students were observed to be less attentive during group work and video watching. This has us thinking about instructor perceptions of student behavior. Lots of students know what it "looks like" to pay attention . . . but are they? It may be the case that the behavioral cues teachers rely on to index student attention (e.g., sitting still, looking at the instructor) may not always reflect the actual engagement of students in their classroom. 

This initial study provides interesting hints about attention in the classroom, but it is just the first of many. We are currently working to replicate these findings and understand how they might be different with students of different ages. For example, is attention greatest in group settings for teens and young adults relative to young children? We hope to answer these questions soon, using real-world educational neuroscience to provide insights for educators that can meaningfully inform classroom practice. 

Learn more in our new research paper, Effects of context on the neural correlates of attention in a college classroom, published by npj Science of Learning.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Subscribe to the Topic

Life Sciences > Biological Sciences > Neuroscience

Related Collections

With collections, you can get published faster and increase your visibility.

Implications of artificial intelligence in learning and education

Exploring the transformative potential of AI in education, this Collection delves into the implications and applications of AI for learning and pedagogy.

Publishing Model: Open Access

Deadline: Jan 26, 2024