AIMC Topic: Educational Measurement

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ChatGPT versus human in generating medical graduate exam multiple choice questions-A multinational prospective study (Hong Kong S.A.R., Singapore, Ireland, and the United Kingdom).

PloS one
INTRODUCTION: Large language models, in particular ChatGPT, have showcased remarkable language processing capabilities. Given the substantial workload of university medical staff, this study aims to assess the quality of multiple-choice questions (MC...

ChatGPT Performs on the Chinese National Medical Licensing Examination.

Journal of medical systems
ChatGPT, a language model developed by OpenAI, uses a 175 billion parameter Transformer architecture for natural language processing tasks. This study aimed to compare the knowledge and interpretation ability of ChatGPT with those of medical students...

Automated grading of anatomical objective structured practical examinations using decision trees: An artificial intelligence approach.

Anatomical sciences education
An Objective Structured Practical Examination (OSPE) is an effective and robust, but resource-intensive, means of evaluating anatomical knowledge. Since most OSPEs employ short answer or fill-in-the-blank style questions, the format requires many peo...

Can Artificial Intelligence Pass the American Board of Orthopaedic Surgery Examination? Orthopaedic Residents Versus ChatGPT.

Clinical orthopaedics and related research
BACKGROUND: Advances in neural networks, deep learning, and artificial intelligence (AI) have progressed recently. Previous deep learning AI has been structured around domain-specific areas that are trained on dataset-specific areas of interest that ...

LecturePlus: a learner-centered teaching method to promote deep learning.

Advances in physiology education
A new teaching format, the LecturePlus, was formulated as a lecture followed by small-group learning activities. This study assessed the effectiveness of LecturePlus in medical education. An interventional study was conducted among final-year medical...

Two efficient selection methods for high-dimensional CD-CAT utilizing max-marginals factor from MAP query and ensemble learning approach.

The British journal of mathematical and statistical psychology
Computerized adaptive testing for cognitive diagnosis (CD-CAT) needs to be efficient and responsive in real time to meet practical applications' requirements. For high-dimensional data, the number of categories to be recognized in a test grows expone...