AIMC Topic: Educational Measurement

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Accuracy of latest large language models in answering multiple choice questions in dentistry: A comparative study.

PloS one
OBJECTIVES: This study aims to evaluate the performance of the latest large language models (LLMs) in answering dental multiple choice questions (MCQs), including both text-based and image-based questions.

Exploring the significance of medical humanities in shaping internship performance: insights from curriculum categories.

Medical education online
BACKGROUND: Medical Humanities (MH) curricula integrate humanities disciplines into medical education to nurture essential qualities in future physicians. However, the impact of MH on clinical competencies during formative training phases remains und...

Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework.

PloS one
As education increasingly relies on data-driven methodologies, accurately predicting student performance is essential for implementing timely and effective interventions. The California Student Performance Dataset offers a distinctive basis for analy...

Claude, ChatGPT, Copilot, and Gemini performance versus students in different topics of neuroscience.

Advances in physiology education
Despite extensive studies on large language models and their capability to respond to questions from various licensed exams, there has been limited focus on employing chatbots for specific subjects within the medical curriculum, specifically medical ...

The ChatGPT Fact-Check: exploiting the limitations of generative AI to develop evidence-based reasoning skills in college science courses.

Advances in physiology education
Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenge...

Performance Evaluation and Implications of Large Language Models in Radiology Board Exams: Prospective Comparative Analysis.

JMIR medical education
BACKGROUND: Artificial intelligence advancements have enabled large language models to significantly impact radiology education and diagnostic accuracy.

Should oral examination be reimagined in the era of AI?

Advances in physiology education
As artificial intelligence (AI) continues to reshape education, concerns about the authenticity of student work have escalated, particularly in relation to written assignments influenced by AI-powered tools. This article explores the role of the oral...

Effect of feedback-integrated reflection, on deep learning of undergraduate medical students in a clinical setting.

BMC medical education
BACKGROUND: Reflection fosters self-regulated learning by enabling learners to critically evaluate their performance, identify gaps, and make plans to improve. Feedback, in turn, provides external insights that complement reflection, helping learners...

Machine learning approach to student performance prediction of online learning.

PloS one
Student performance is crucial for addressing learning process problems and is also an important factor in measuring learning outcomes. The ability to improve educational systems using data knowledge has driven the development of the field of educati...

Performance of 4 Artificial Intelligence Chatbots in Answering Endodontic Questions.

Journal of endodontics
INTRODUCTION: Artificial intelligence models have shown potential as educational tools in healthcare, such as answering exam questions. This study aimed to assess the performance of 4 prominent chatbots: ChatGPT-4o, MedGebra GPT-4o, Meta LIama 3, and...