Rania Qais
The school of Psychological Sciences , Tel Aviv University
PI: Shlomit Yuval-Greenberg
BIO:
I hold a B.Sc. in Psychology and Biology with an emphasis on Neuroscience from the Sagol School of Neuroscience, and an M.A. in Research Psychology, specializing in Brain and Cognition, both from Tel Aviv University. I am currently pursuing my Ph.D. in the Cognitive Neuroscience Lab at Tel Aviv University, under the supervision of Prof. Shlomit Yuval-Greenberg. My research investigates the role of saccadic eye movements in the utilization of visual working memory capacity.
Balancing Working Memory and Perception in Learning Environments
Project description
Effective learning requires a delicate balance between working memory (WM) retention and perceptual access. In a classroom setting, students must often sustain information in WM while gathering new sensory input from their environment. Optimizing the balance between memory retention and perceptual access is essential for maximizing learning efficiency.
Traditional teaching methods often place excessive cognitive demands on students by taxing both WM and sensory processing mechanisms simultaneously, leading to inefficient information retention and cognitive overload. This issue is particularly pronounced in tasks that require memorizing equations, comparing complex visual information, or copying text from a board. In these situations, students may default to heavy WM reliance, failing to take advantage of perceptual strategies like frequent eye movements to re-access information. Understanding how learners naturally balance memory and perception under varying cognitive loads and task designs is key to improving instructional methods and educational materials.
My study aims to investigate the interaction between WM utilization and sensory perception, with a focus on visual processing. Using eye-tracking, I will examine how learners allocate WM resources versus visual input and apply these insights to real-world classroom tasks, particularly copying from a board. The findings will inform cognitive load management strategies in educational design, helping develop more effective learning methods that optimize memory and perceptual processing.