Education Research: Online EEG Learning Platforms for Resident and Fellow Education

EEG interpretation is a core neurology competency, but instruction and supervised review vary across programs. Online platforms may supplement training, but their design and functionality are not well characterized. We reviewed publicly accessible online EEG platforms for residents and fellows.

We conducted a scoping review of publicly available online EEG learning platforms using a multipronged identification strategy (June 2025 to January 2026) that included independent web searches by multiple reviewers, targeted screening of professional society and organizational websites, review of EEG education literature and conference materials, author knowledge, and AI-assisted searching using ChatGPT (OpenAI) to generate candidate platform names and search terms. Platforms were eligible if they were stable, web-based educational environments primarily intended to teach EEG interpretation or EEG-related clinical neurophysiology, with structured organization and at least 1 active learning feature beyond one-way media delivery. Two reviewers independently evaluated platform features using a standardized charting form covering educational delivery (accessibility, interactivity, assessment, feedback, and program integration) and EEG technical functionality (content breadth, pediatric/neonatal availability, scrolling and manipulation, and intensive care unit [ICU]/intraoperative monitoring [IOM]/quantitative EEG [qEEG] coverage). When contact information was available, creators of free-to-access platforms were contacted to verify platform features.

Of 16 sources identified, 1 standalone video-sharing channel was excluded, leaving 15 platforms. Ten (67%) were free. Feedback was available on 12 (80%): automated on 9 (60%) and personalized on 3 (20%); all personalized feedback required payment. Only 1 platform (7%) reported trainee progress to a program director. Among free platforms, all included adult EEG examples; 7 (70%) included pediatric content, 4 (40%) neonatal content, 4 (40%) EEG manipulation, 6 (60%) ICU EEG, 3 (30%) qEEG, and 1 (10%) IOM.

Online EEG learning platforms provide accessible, scalable foundational instruction but vary in functionality. Gaps include limited pediatric and neonatal content, restricted EEG manipulation, and limited personalized feedback or program-level integration. For training programs, these findings support using online platforms to standardize foundational exposure while integrating them into hybrid curricula that combine self-directed learning with supervised case review, expert feedback, and milestone-based assessment. Future platforms, including artificial intelligence-enabled tools, may further personalize EEG education by tracking learner progress and recommending targeted cases or modules.