AIMC Topic: Educational Measurement

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ICMC: An Interpretable Cross-domain Multi-modal Classification model for grading teaching plan.

PloS one
Multi-modal classification aims to extract pertinent information from various modalities to assign labels to instances. The advent of deep neural networks has significantly advanced this task. However, the majority of current deep neural networks lac...

Comparative evaluation of AI platforms "Google Gemini 2.5 Flash, Google Gemini 2.0 Flash, DeepSeek V3 and ChatGPT 4o" in solving multiple-choice questions from different subtopics of anatomy.

Surgical and radiologic anatomy : SRA
PURPOSE: The rise of artificial intelligence (AI) based large language models (LLMs) had a profound impact on medical education. Given the widespread use of multiple-choice questions (MCQs) in anatomy education, it is likely that such queries are com...

Comparative evaluation of large language models performance in medical education using urinary system histology assessment.

Scientific reports
Large language models (LLMs) show potential for medical education, but their domain-specific capabilities need systematic evaluation. This study presents a comparative assessment of thirteen LLMs in urinary system histology education. Using a multi-d...

Token Probabilities to Mitigate Large Language Models Overconfidence in Answering Medical Questions: Quantitative Study.

Journal of medical Internet research
BACKGROUND: Chatbots have demonstrated promising capabilities in medicine, scoring passing grades for board examinations across various specialties. However, their tendency to express high levels of confidence in their responses, even when incorrect,...

Evaluating large language models as graders of medical short answer questions: a comparative analysis with expert human graders.

Medical education online
The assessment of short-answer questions (SAQs) in medical education is resource-intensive, requiring significant expert time. Large Language Models (LLMs) offer potential for automating this process, but their efficacy in specialized medical educati...

Large language models underperform in European general surgery board examinations: a comparative study with experts and surgical residents.

BMC medical education
BACKGROUND: Artificial intelligence (AI) has become a transformative tool in medical education and assessment. Despite advancements, AI models such as GPT-4o demonstrate variable performance on high-stakes examinations. This study compared the perfor...

The performance of ChatGPT on medical image-based assessments and implications for medical education.

BMC medical education
BACKGROUND: Generative artificial intelligence (AI) tools like ChatGPT (OpenAI) have garnered significant attention for their potential in fields such as medical education; however, their performance of large language and vision models on medical tes...

The role of generative AI tools in case-based learning and teaching evaluation of medical biochemistry.

BMC medical education
BACKGROUND: Medical biochemistry, a fundamental course in medical education, has a complex and expanding knowledge base. Traditional teaching methods often fail to meet students' needs for in-depth understanding and personalized learning. Students ca...

Five advanced chatbots solving European Diploma in Radiology (EDiR) text-based questions: differences in performance and consistency.

European radiology experimental
BACKGROUND: We compared the performance, confidence, and response consistency of five chatbots powered by large language models in solving European Diploma in Radiology (EDiR) text-based multiple-response questions.

MANIT: a multilayer ANN integrated framework using biometrics and historical features for online examination proctoring.

Scientific reports
Online education has become a globally accepted norm, bringing benefits and challenges. One of the most debated aspects is the academic integrity of online examinations. Without physical proctoring, the authenticity of the candidates' scores can alwa...