Eye-Tracking for Diverse and Advanced Learning Techniques in Chemistry Education

Eye-Tracking for Diverse and Advanced Learning Techniques in Chemistry Education

Eye-tracking technology can objectively measure students’ cognitive engagement in culturally responsive learning environments. However, this technology still has not been fully used to improve the learning chances for educationally low performing students who have been subjected to deficit-based descriptions to characterize their learning.

Culturally responsive pedagogy (CRP), not deficit-based descriptors, is essential to preparing students for academic success. Unbeknownst to many, deficit-based social determinants do not carry as much weight in the actual learning process as educational researchers have claimed.

Culturally responsive educators, in one voice, and cognitive and behavioral neuroscientists, in another voice, both clearly illuminate how people learn—even people who’ve been ascribed varying social determinants.


A learning context that doesn’t apply the knowledge and technology of cognitive neuroscience further limits students’ academic performance. Albeit the intellectual resources exist in CRP and cognitive neuroscience separately, the two domains of knowledge should inform one another to improve the educational experiences of all students, but they don’t.

Both fields should apply the appropriate label to all students, regardless of other social descriptors. That label is a learner. At the core, learners are learning. Learning is about strengthening the connection of neurons in the brain. The environment to facilitate increases in these neuropathways must be culturally responsive.


Strengthening the connections between neurons is called structural neuroplasticity. The relationship between neuroplasticity and learning is an easy one to surmise. When learners learn, new pathways in the brain are formed.

Many of these neuropathways, located in subregions of the brain, are involved in visual processing. Learning attention is driven by an interplay of visual features. Examining this visual pathway in milliseconds of time provides insight about cognition. Eye tracking, a technology tool increasingly being used in educational research, allows researchers to investigate many aspects of cognition and learning along portions of the neural visual pathway.


Your eyes don’t lie. This is exactly why researchers use eye-tracking technology to evaluate students’ focus and attention.

Eye-tracking is a tool used to study visual attention in a variety of science, biology, chemistry, and mathematics educational settings. Eye-tracking is being used to provide an objective way of monitoring cognitive processes using the eyes as a window into students’ cognitive learning processes.

Objective measurement of eye movements gives new insights into the cognitive strategies students are using during the online learning process, specifically critical thinking and problem-solving strategies.


Here’s how one type of eye-tracking apparatus works–the eye-tracking glasses. Students wear specially designed eyeglasses that track exactly where their eyes are focused during online learning sessions. There are other hardware devices that are unobtrusive and easily placed along the edge of a monitor to track eye-movement as well.

Eye-tracking measures the following attributes:

  • Presence, attention, and focus – by calculating time fixated on specific areas of interest
  • Drowsiness – by calculating blinks or percent eye closure
  • Consciousness or other mental and physiological states – by calculating pupil diameter

Each of these areas is pertinent to a student’s success in online learning environments. By measuring eye movements, studies reveal that we gain valuable insight into the cognitive strategies students use in online courses to solve multiple-choice science problems. Thus, eye-tracking technology can illuminate problem-solving techniques as well as difficulties.


So, how does eye-tracking work and what can we learn from it? Eye-tracking research conducted at two historically black colleges and universities showcase crucial insight into what students are looking at during exams: When students encounter word problems, they spend valuable seconds looking outside the optimal area of interest. They especially default to this when encountering problems that they’ve not seen in a while. For timed exams like the critical standardized exam, those seconds matter. Seconds amount to minutes, and ultimately dictate whether or not a student passes.

Eye-tracking effectively studies visual attention in a variety of science and mathematics learning settings. With this tool, researchers explore problem-solving methods as well as difficulties students face solving certain problems. Understanding perceptual properties can be used as a guidepost for learning attention through eye movements, according to studies. With this data, we can enhance students’ ability to problem solve quickly.


The insights that eye-tracking technology provides allows our research team to build an improved online learning system. This information can lead to improved reasoning, critical thinking, and performance on standardized and timed chemistry exams. The structure of this system is designed to generate and expedite critical thinking.


Students will be trained during practice sessions to look in the appropriate areas of interest for a variety of chemistry problems anticipated on the American Chemical Society exam. This enhanced online learning system will offer practice in an online environment that will detect and guide students to look immediately in the right area. When they learn where to look, they can solve certain types of chemistry problems faster.

This approach prepares them to gain valuable seconds that will increase their performance. Furthermore, our research shows that we need to embed objective measures and technology-based strategies into our students’ learning experiences. Doing so will help them redirect their focus and attention within a span of seconds while they are in online learning environments.


This research study enhances the literature base on distance learning in chemistry education and improves the success of undergraduate students enrolled in general chemistry courses. The study is innovative and advances the literature on artificial intelligence (software design) and educational technology strategies for improved learning of diverse populations of students (particularly those with varying learning preferences) especially as we bring the behaviors of instructors in a blended learning environment to an online learning management platform. An analysis of data will inform the instructional approach of chemistry professors, particularly as they design blended learning experiences for students.

Researchers have collective objective eye-tracking data illuminating students’ cognitive strategies while solving chemistry word problems, particularly word problems that students find difficult to solve (e.g. rate of reaction and titration for instance).

Additionally, researchers used eye-tracking metrics to understand students’ problem-solving approach and confidence and perceptions of academic self-regulation. Our thinking is that the convergence of appropriately designed blended learning experiences designed to increase students’ perceptions of their problem-solving confidence and academic self-regulation will increase their science identity and engagement in any science or engineering discipline.


The use of objective eye-tracking data will allow researchers to develop improved blended learning environments and online learning platforms and learning management systems with embedded assessment strategies to enhance students’ word problem-solving skills and confidence. Data collected will be used to build a responsive online learning system where students can practice problem-solving with auto-generated feedback based on their online behavior. The learning management system will provide students with practice opportunities with automated feedback to increase their resilience and performance once they encounter time-based chemistry exams. Additionally, insights that eye-tracking metrics will allow our research team to build an improved online learning system to enhance students’ problem-solving skills which can lead to improved reasoning, critical thinking, and problem-solving abilities.

This enhanced online learning system will offer practice in an online environment that will detect and guide students to look immediately in the appropriate areas to solve certain types of chemistry (or mathematics) problems. This approach prepares students to gain seconds during task performances. Another way to say this is that our research is showing that we need to embed objective measures and adaptive technology-based strategies to help students redirect their focus within the span of seconds while they are in an online learning environment.


By understanding how different aspects of the learning process shape educational outcomes, particularly for diverse student learners, researchers can effectively design, evaluate, and improve online teaching and learning specifically in gate-keeping high school and college science and mathematics courses.


Blackmon, A. T., & Castillo, B. (2019, July). Using Eye Tracking Systems to Assess the Impact of a Hybrid Problem-based Distance-learning Environment on Chemistry Students’ Problem-solving Skills.Paper presented at the IAFOR European Conference on Education.

Cook, M., Wiebe, E. N. & Carter, G. (2008). The influence of prior knowledge on viewing and interpreting graphics with macroscopic and molecular representations. Science Education, 92, 848–867.

Grant, E. R. & Spivey, M. J. (2003). Eye movements and problem solving: Guiding attention guides thought. Psychological Science, 14, 462–466.

Liu, C. J. & Shen, M. H. (2011). The influence of different representations on solving concentration problems at elementary school. Journal of Science Education and Technology, 20, 621–629.

Merkley, R. & Ansari, D. (2010). Using eye tracking to study numerical cognition: The case of the ratio effect. Experimental Brain Research, 206, 455–460.

Moeller, K., Fischer, M. H., Nuerk, H. C. & Willmes, K. (2009). Sequential or parallel decomposed processing of two-digit numbers? Evidence from eye-tracking. Quarterly Journal of Experimental Psychology, 62, 323–334.

Tang, H. & Pienta, N. (2012). Eye-tracking study of complexity in gas law problems. Journal of Chemical Education, 89, 988–994.

Williamson, V. M., Hegarty, M., Deslongchamps, G., Williamson, K. C. & Shultz, M. J. (2013). Identifying student use of ball-and-stick images versus electrostatic potential map images via eye tracking. Journal of Chemical Education, 90, 159–164.

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Blackmon, Angelicque Tucker, Ph.D. " Eye-Tracking for Diverse and Advanced Learning Techniques in Chemistry Education." March 17, 2020, https://www.ilearningcenter.education/eye-tracking-for-diverse-learning-advanced-learning-techniques-in-chemistry-education Blackmon, Angelicque Tucker, Ph.D. (2020, March). Eye-Tracking for Diverse and Advanced Learning Techniques in Chemistry Education Retrieved from https://www.ilearningcenter.education/eye-tracking-for-diverse-learning-advanced-learning-techniques-in-chemistry-education