Document Type
Abstract
Publication Date
1-2020
Academic Year
2019-2020
Abstract
Purpose: This project aims to create an Electroencephalography (EEG) curriculum that synthesizes the teachings of current publications and faculty expertise within a single digital platform. The goal is to remedy the unmet need for a centralized resource for learners to use when learning EEG interpretation.
Methods: The target learner population is epilepsy and neurophysiology fellows. The platform will be accessible from any computer, tablet, or phone, allowing for mobile, self-paced learning to take place. To date, the curriculum outline has been designed with extensive literature review and collaboration from other institutions, and two pilot modules have been completed using the story-board platform Articulate. Data about efficacy and usefulness will be collected via learner feedback forms when the program goes live.
Results and Conclusions: We anticipate that fellows will appreciate the streamlined approach to learning high-yield topics in EEG interpretation. The hope is that the platform will save users 2 time currently spent sifting through textbooks and publications because it incorporates a conglomerate of resources, including qualitative input from experts across the country. That time, in turn, can be spent with more targeted interactions with their teachers (the platform serves as a complement to the existing face-to-face instruction). Learning activities for progress-evaluation will be embedded within each module of the platform with the goal of allowing learners to self-identify areas of improvement to help focus studying efforts. Further results and conclusions will be recorded and updated as progress continues to be made.
Recommended Citation
Woehling, Anne; Hancock, Brooke; Lee, MD, Nathanael; Tang, MD, Connie; Pickard, MD, Allyson; and Fernandez, MD, Andres, "Developing an Online Critical Care Electroencephalography Curriculum for Epilepsy and Neurophysiology Fellows" (2020). Phase 1. Paper 3.
https://jdc.jefferson.edu/si_me_2022_phase1/3
Language
English
