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Record W4410775417 · doi:10.1002/epd2.70045

Continuing medical education in epileptology: The Level 1‐2‐3 experience of the <scp>ILAE</scp> academy

2025· article· en· W4410775417 on OpenAlexafffund
Ingmar Blümcke, Eva Biesel, Samuel Wiebe, Sándor Beniczky, Jo M. Wilmshurst, Man Mohan Mehndiratta, Ali A. Asadi‐Pooya, Christian Brandt, Alexis Arzimanoglou, Gagandeep Singh

Bibliographic record

VenueEpileptic Disorders · 2025
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Calgary
FundersSchool of Medicine, Emory UniversityPirogov Russian National Research Medical UniversityUniversité de LausanneHospital for Sick ChildrenSyddansk UniversitetHospices Civils de LyonSahlgrenska UniversitetssjukhusetSheffield Teaching Hospitals NHS Foundation TrustUniversity of CreteStichting Epilepsie Instellingen NederlandEmory UniversityUniversity of TorontoUniversity College LondonMonash UniversityEuropean CommissionUniversité de LyonUniversity of Texas Health Science Center at HoustonUniversität Bielefeld
KeywordsCurriculumPsychologyMedical educationContinuing medical educationBlended learningOnline learningMathematics educationContinuing educationMultimediaComputer scienceEducational technologyMedicinePedagogy

Abstract

fetched live from OpenAlex

The International League Against Epilepsy (ILAE) Academy is the world's eminent e-learning campus for epileptology. Its modular teaching content was developed to cover all competencies and learning objectives specified in the ILAE's curriculum for epileptology. The tutorless and self-paced entry Level 1 program for beginners offers an interactive case-based e-learning approach. A blended e-learning format was developed for the proficiency Level 2 with various learning domains and formats. They comprise a series of interactive, self-paced and case-based e-learning modules covering common, but also rare or complex epilepsy conditions, through state-of-the-art diagnosis and rational treatment decisions. Interactive EEG and MRI readers were integrated to support a tutorless online teaching format. An innovative adaptive e-learning format was applied for specific learning domains to reflect not only the proficiency level of the learner but also their self-confidence and perceived and unperceived knowledge of the topic. Our analysis of the completed adaptive e-learning courses revealed that 21% of the learning objectives had been answered incorrectly despite the learner indicating that they know the answer. This so-called "unconscious incompetence" should be regarded as a key motivation for building continuing medical education (CME) programs in epileptology. Level 2 utilizes a blended learning approach requiring 200 CME or equivalent ILAE credit points, earned through a mix of online learning with in-person participation in ILAE schools and congressional teaching activities. Level 3 is the subsequent step in the ILAE's structured learning path towards advanced proficiency and includes skill-based training in epileptology. Registered learners can apply for training visits in internationally renowned epilepsy centers around the world. Limited financial support is made available for selected applicants, e.g., to support candidates from resource limited settings. Designed to bridge the gap in knowledge and access to continuing education in epileptology, this unique structured learning path is open to all healthcare professionals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.341
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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