The paper is focussed on the assessment of cognitive workload level using selected
machine learning models. In the study, eye-tracking data were gathered from 29 healthy …

The paper offers insights into people's exploration of creative products shown on a computer
screen within the overall task of capturing artifacts' original features and functions. In …

Background Medical trainees are required to learn many procedures following instructions
to improve their skills. This study aims to investigate the pupillary response of trainees when …

Background Six nursing assessments were studied to determine if they could differentiate
expert (sensitivity) vs. novice (specificity) nurses: Lasater Clinical Judgment Rubric (LCJR) …

Purpose: The primary objective of this study was to develop machine learning algorithms for
classifying mental workload using eye tracking data. Theory and Methods: This study …

It is essential to understand the effectiveness of any training program so it can be improved
accordingly. Various studies have applied standard metrics for the evaluation of visual …

A significant limitation of current smartphone-based eye-tracking algorithms is their low
accuracy when applied to video-type visual stimuli, as they are typically trained on static …

Assessment of cognitive workload level is important to understand human mental fatigue,
especially in the case of performing intellectual tasks. The paper presents a case study on …

Bu çalışmada, göz izleme verilerine bağlı olarak zihinsel iş yükünü sınıflandırmada makine
öğrenmesi algoritmalarının kullanması amaçlanmıştır. Dört katılımcının (iki kadın ve iki …

Ensuring the reliability of time estimations is vital for industries, as it establishes the basis for
effective planning, resource allocation, and performance assessment, ultimately improving …